From 16c80d5fbae30059f27a9551b53bf55b1114ad7c Mon Sep 17 00:00:00 2001 From: linyiLYi <48440925+linyiLYi@users.noreply.github.com> Date: Sun, 2 Apr 2023 00:16:57 +0800 Subject: [PATCH] learn from level 1 --- .../check_reward.py | 1 - ...fevents.1680176551.DESKTOP-9E17TO7.25984.0 | Bin 13771 -> 0 bytes ...fevents.1680180303.DESKTOP-9E17TO7.35284.0 | Bin 29033 -> 0 bytes ...fevents.1680180514.DESKTOP-9E17TO7.11796.0 | Bin 14007 -> 0 bytes ...fevents.1680180894.DESKTOP-9E17TO7.20548.0 | Bin 50276 -> 0 bytes ...fevents.1680182153.DESKTOP-9E17TO7.30948.0 | Bin 57294 -> 0 bytes ...fevents.1680182468.DESKTOP-9E17TO7.30948.1 | Bin 57867 -> 0 bytes ...fevents.1680182795.DESKTOP-9E17TO7.30948.2 | Bin 8507 -> 0 bytes ...fevents.1680183136.DESKTOP-9E17TO7.30948.3 | Bin 53172 -> 0 bytes ...fevents.1680183432.DESKTOP-9E17TO7.30948.4 | Bin 10538 -> 0 bytes ...fevents.1680183612.DESKTOP-9E17TO7.32692.0 | Bin 49623 -> 0 bytes ...fevents.1680183923.DESKTOP-9E17TO7.32692.1 | Bin 20885 -> 0 bytes ...tfevents.1680177234.DESKTOP-9E17TO7.2364.0 | Bin 2971 -> 0 bytes ...fevents.1680184256.DESKTOP-9E17TO7.32692.2 | Bin 43434 -> 0 bytes ...fevents.1680184590.DESKTOP-9E17TO7.32692.3 | Bin 18129 -> 0 bytes ...fevents.1680184934.DESKTOP-9E17TO7.32692.4 | Bin 30495 -> 0 bytes ...fevents.1680185250.DESKTOP-9E17TO7.32692.5 | Bin 8507 -> 0 bytes ...fevents.1680185584.DESKTOP-9E17TO7.32692.6 | Bin 251 -> 0 bytes ...fevents.1680185591.DESKTOP-9E17TO7.32692.7 | Bin 41379 -> 0 bytes ...fevents.1680185938.DESKTOP-9E17TO7.32692.8 | Bin 59922 -> 0 bytes ...fevents.1680186251.DESKTOP-9E17TO7.32692.9 | Bin 19507 -> 0 bytes ...fevents.1680204062.DESKTOP-9E17TO7.19212.0 | Bin 0 -> 1044006 bytes ...fevents.1680177334.DESKTOP-9E17TO7.35060.0 | Bin 60611 -> 0 bytes ...tfevents.1680229915.DESKTOP-9E17TO7.2720.0 | Bin 0 -> 104019 bytes ...fevents.1680177771.DESKTOP-9E17TO7.35060.1 | Bin 46983 -> 0 bytes ...fevents.1680178207.DESKTOP-9E17TO7.35060.2 | Bin 12629 -> 0 bytes ...fevents.1680178663.DESKTOP-9E17TO7.35060.3 | Bin 39428 -> 0 bytes ...fevents.1680179100.DESKTOP-9E17TO7.35060.4 | Bin 8507 -> 0 bytes ...fevents.1680179576.DESKTOP-9E17TO7.35060.5 | Bin 16763 -> 0 bytes ...fevents.1680180040.DESKTOP-9E17TO7.35060.6 | Bin 5751 -> 0 bytes .../logs/monitor.csv | 2255 ++++- 000_image_stack_ram_based_reward/test.py | 8 +- 000_image_stack_ram_based_reward/train.py | 97 +- .../trained_models/training_logs.txt | 8951 +++++++++++++++++ .../trained_models_level_1/training_logs.txt | 3144 ++++++ 004_custom_policy/custom_cnn.py | 35 + 36 files changed, 14401 insertions(+), 90 deletions(-) delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_1/events.out.tfevents.1680176551.DESKTOP-9E17TO7.25984.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_10/events.out.tfevents.1680180303.DESKTOP-9E17TO7.35284.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_11/events.out.tfevents.1680180514.DESKTOP-9E17TO7.11796.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_12/events.out.tfevents.1680180894.DESKTOP-9E17TO7.20548.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_13/events.out.tfevents.1680182153.DESKTOP-9E17TO7.30948.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_14/events.out.tfevents.1680182468.DESKTOP-9E17TO7.30948.1 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_15/events.out.tfevents.1680182795.DESKTOP-9E17TO7.30948.2 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_16/events.out.tfevents.1680183136.DESKTOP-9E17TO7.30948.3 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_17/events.out.tfevents.1680183432.DESKTOP-9E17TO7.30948.4 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_18/events.out.tfevents.1680183612.DESKTOP-9E17TO7.32692.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_19/events.out.tfevents.1680183923.DESKTOP-9E17TO7.32692.1 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_2/events.out.tfevents.1680177234.DESKTOP-9E17TO7.2364.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_20/events.out.tfevents.1680184256.DESKTOP-9E17TO7.32692.2 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_21/events.out.tfevents.1680184590.DESKTOP-9E17TO7.32692.3 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_22/events.out.tfevents.1680184934.DESKTOP-9E17TO7.32692.4 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_23/events.out.tfevents.1680185250.DESKTOP-9E17TO7.32692.5 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_24/events.out.tfevents.1680185584.DESKTOP-9E17TO7.32692.6 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_25/events.out.tfevents.1680185591.DESKTOP-9E17TO7.32692.7 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_26/events.out.tfevents.1680185938.DESKTOP-9E17TO7.32692.8 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_27/events.out.tfevents.1680186251.DESKTOP-9E17TO7.32692.9 create mode 100644 000_image_stack_ram_based_reward/logs/PPO_29/events.out.tfevents.1680204062.DESKTOP-9E17TO7.19212.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_3/events.out.tfevents.1680177334.DESKTOP-9E17TO7.35060.0 create mode 100644 000_image_stack_ram_based_reward/logs/PPO_30/events.out.tfevents.1680229915.DESKTOP-9E17TO7.2720.0 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_4/events.out.tfevents.1680177771.DESKTOP-9E17TO7.35060.1 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_5/events.out.tfevents.1680178207.DESKTOP-9E17TO7.35060.2 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_6/events.out.tfevents.1680178663.DESKTOP-9E17TO7.35060.3 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_7/events.out.tfevents.1680179100.DESKTOP-9E17TO7.35060.4 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_8/events.out.tfevents.1680179576.DESKTOP-9E17TO7.35060.5 delete mode 100644 000_image_stack_ram_based_reward/logs/PPO_9/events.out.tfevents.1680180040.DESKTOP-9E17TO7.35060.6 create mode 100644 000_image_stack_ram_based_reward/trained_models/training_logs.txt create mode 100644 000_image_stack_ram_based_reward/trained_models_level_1/training_logs.txt create mode 100644 004_custom_policy/custom_cnn.py diff --git a/000_image_stack_ram_based_reward/check_reward.py b/000_image_stack_ram_based_reward/check_reward.py index 7f46495..3fee3e3 100644 --- a/000_image_stack_ram_based_reward/check_reward.py +++ b/000_image_stack_ram_based_reward/check_reward.py @@ -1,7 +1,6 @@ import time import retro -from stable_baselines3 import PPO from stable_baselines3.common.monitor import Monitor from stable_baselines3.common.vec_env import DummyVecEnv, VecFrameStack diff --git a/000_image_stack_ram_based_reward/logs/PPO_1/events.out.tfevents.1680176551.DESKTOP-9E17TO7.25984.0 b/000_image_stack_ram_based_reward/logs/PPO_1/events.out.tfevents.1680176551.DESKTOP-9E17TO7.25984.0 deleted file mode 100644 index 9096b7c311fabeb783082142855e0dc9e7d44d91..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 13771 zcma*tdt6NU8wcTaDMU&Lzx}tT7UF)t^E?Jw)y8PBOulD<#IX8cLeLwU0KF_?Jn&QLj`13K_XPd$G zcYny{7&J|?Gz?ctWC~ZW1gRo!{HQ=z{;)WyA~sqX9xYKuxW>juMM;!PToaYDIH}TA z`uUVNQYM#*JN^b+Gq#V7_H_e%adU%4=kkT0U$^fW17~Bt5x-}gEK2GY853*DOF1Tb zdCh2{v-WuL+N{3~X7;s|YmTosaURIGd{A#& zE6z!!G*O#;a8@lD|EC4GBHBs1B5$>5pd=)9i1v!H)9&-Y70vl(e51I}3v-ji#3-W| zi@%kd>gW3kt-Il0Fki1DHD4}^5l1Q|^W$XE3R9oEqp`a5UpyVPeU*1hCxbo<{s4Yo zB&n1r7D!F&i3%*}t7qRhX=7tPiQzS^_!j(r9kGAkFJ*Mh60tlwHrBL6+3l3mm%ba_ zw85x3*3&_sE#HQ3t_?1Zk^eiVG(wypQOYEW`BGC}Zu*3ea>-pTgUY26r9!4yAXZA^ zq^2il)sCHYxh>yTTihk7wH*|j@QwNWj$+MCyST%8l*P{ zG9c}{1t+>BV4RcxA>Daf{mE~v03by>$wK>djs1f&fx9$bvNF-nfm1?|$bps4mj* z-B(HhQnZ+iG$-(omrM73YJe0CupvD%+!RaRxFn3rY7wL_e?Lq-Rn0F1BlO)OJ?86C zA$6MV;_<81ly_j0XdgXNcm3|J04W-yL%QKrt17tUfd@c}2APpoU*04z%e`&LWl&wD zX)_w408+G=jP#qWp5EpwW99>-Xn+l=aM^j`<4O7_xvUmJsyDQqc-WMG2#mPZz$-?B zwAqar>Fd2Em7J3R>CjjEj{&4;CmCt9=oWADKL9CuoDymI$XVE>QO1qT*P}uj8JUJH zZf`RLn?(EQk?NVga{x%u7#&jLK#=N5eEtZ46b&*XHILXM%*&|FoyYP7jfQ2uxCBrdB(kQzjm5Wcn{@QZe&>Fz}uq=&{aAmtU} zXR+`=upFjjC(<7;m8sh^re*@9Xp)RnE{gASG6*0=k5eMGYYxTqKh_Ooz8)3Q>$}Xb zkk)5#lV~43(){mB#{;Bjj1H-Ie~PNdgtA=#DH>!(`my-}R$=10lgpsGNQL6Z;Q%RG zOh#JoZ;cB4N4BYMy(_i_NYNlO(u_wNu&9;uYPbxli}d8o z_d5Vmw3v)^RnM*>|L9Ze08%u-hP33m{KR>l_h~MxMUWo)DFXj1ZP`dL;*8yA;x$Nr zm`RV62t10UieR=|<=y6J<*Ou8} zR|khCFkg=f=^|ko_J?gCA8Zosqept#dmDU`qA@z83&L_#1rrO;0i9tImW!<6%m6BIPw#sry%F1_GpLl8iJ$G;de97$8NDQzE_S zc^!)(-g+_*Mujw~{}$}3*lz;ZB-%%hv>`w20(g?5F*>9cZe^Tl@@kfH%Lq#x|}2o~lpgg-bzUjSJxg48*E zJaIjD=w>kD*!6))8l*oZ(<5C|T!gRM+N+IovJ>fm`zp1(oBAO@iguEb&KF&M{O~P6 ziXNv#sz?%GcPkY<=Ic=*UHK#yGdhRs0if3zGMf>a6bgR?82K%cjk~K(Qtn5OsH27f=?%eC}0`AdHrY>LAsDB>rKY5V0 z)#>TJ>9AGTDZgyx6fhjPB_-5|)jn8LZKE&C4XLDN)?{P)8!o>ds=eW-7_%wxhV)c_ z{Wz%rkO4QPv#NjKf2vT+n#2*>#@xRf#ITVWYu>3;;qyt>!JLNG)f!#9G1yL9z1Udz z0alZ_UYz^@U$Zx*b(A(?Z!xnKCfK~De$W@#$cRc#3r4_BZ{JT$PY!AWV+QWC{!Rn- zcqRkbgn|Qj@yoS7+@qaf9f#Ja72oCY25INjfCa5&u;C($W5C{lGp!BRyF0QnRlCSdgOw>*!~!T3S+=1HghLGuY|1+l4pp{i(-k zSY5Eod)>4HU_mt*?D?E)UQ3c|`vI^Z!3K6q%3ML+zIA&zEf@ityS#~TKabUcF;C~E zey;(WvY7#FcK?I85C2jv_h=_r;>~IGyl;=10I;A{7i_nH7hwP_I8O=I&U~|n$+{x8 z8&ZMg@lIh=d4*5FK0zZr*yz>%MF1?w(SdEaF-a9LZ}D&d79^R$9y*mRlx^9Cv%DQ0 z!|H-Hx^-m-01K+gU@cF%c&#Axt^%+i!3H+I*BIfr<^mH=3r4^;6ju?)-5N%KG3|UG zq-emNDPRDbn7ALew>W%(d$bem^Fj6M!Ob#%02Z|Bf;|!YX%7Gk&QpRNF+=Jx(>Xns z<%U#XXJ`I`U0M@78tfA^(u2(kdwvdp1vxsfH9&wiYS z)dhPqZPgI~7F3hLjj*(ShAYtWxb(8D;>mAju5&T0u1y zqL_1>7|YbU_pWntROO17&iWk3Qh|~z|Om6?&UT% z>lPR@aHjQ24cHwj2C$7+O7Y~uQOVq+onY^+s#m{w=9UV;f>vFy4{x^N04z993AP|7 z)Z>e7#RSU@sh+Uz?v2>{X*&gApP-Q*Y|x@j4&Vt3a&%zrvu3L1zAWAaz=9+**gJX8 zg-?o4uH-bV?i1FarPUfdVL>$+th@J*UT;&fM**-P!3MUV?TNtAXcqjC0A2xEFaoyv z)ptZf+n&2%Oqq3Bx(00X83wT9o*l#!4h~$$J=zI&VB1;s=pP%y09eqf3pTx_We5NZ z&QpS2S{ICES`D*jxgizU%$jkSYObm)01FzCeUiQ<$Q4hW0KkGA9ax*U^;M};%{BqB zAju52IWA4OCu5lqTA=wHgl$1SM$P)F;R5O#MkYgvOLJ_S~*^Z?o%AQ@mwxkfERTL9r zSN6)jZ;>VY+V7mvYkv3VnP>B-*ZrC6zOH%C-SbS-^cVg4_j`5!E%l0`Z#DI+chj|H z!wCw%zz|#cbpMdZzTN+_HRu}Y9}*F&m=Nlxm}DCf6&&oRm}NUd5g6&Ou=W3Ml}|um zkiXBL|M_szXMlCh;~rR^_^Dp&)f<}q_qc}V^sUVdS{gJ}ga!qLMn&5Bhxr8ghxi2h z`-K>bT;gP7($4e}oK*PFs7Xd!s|?3_?Xjq-In+aD3N?)k8XM?G1_t}v1%yQyi=y+T zZqGBeWV#({I*J(bSX7T( zZfam+&^YqHC&|t)EKCtP(`QZq;a zgyql9cdV&*^x+|QsMo@vxq%^(RQQEV_BW1M=qXNf-8Q*%O{{md4{o!SK?{Q>e`5a{ zQG|xg@(Bu!h%mM|u2+;hbNC#)nqcsFb1$f8X<%VsS`(ZZ7W8kQ{*!#B`zZqbLMHnE zOC|sC5zm#OLK+S7_fv!fhD`QR_(l2~%dakQ%rV;MWm!{L=bzV~p>R_JBLjm!h1EL^ z>b}n1K6U5VZZ&}|v9T{9(AL1xpyi)HSZGk-#92O*6@HTf|9eTOAD~%cqk<<}dv6mm z+Ub5lQT~5oXTP76{hBnhE41kQ`L>A~>FpLANW<32!qWEz2~KK|76-{y7Z2_{3P{PC zG^Ek-(#^IPCIV7&IU`aJ_M0$S&toQ^|Yn!0Vx?{ zLpsX;U!+?;4FIHMkQ=G*obtlt*iN}Z8r4QR#mX=XkdlSzNDICdh`YVi`vOSG03TAT zs~Jak?!9$J$Y=?qcgM_i{c_ME23p)>gMPBqV#k|+ zlnn48P2OijHF1A2UdU((q@H_9GY_x6~O-aPe7oao!r5GG01V@G=5 z@nt9=C1Y$z*I&^onsMB&1dx(JZlt2wld0*$l#_%ss*Ut(;i^`Elq^g~y79{~Y4PRn ze*sc5z=!nxV`FFY11`UWjFvzu_FLdyZlW@U7RPs7+e(eJ+KC%!l#%sb!AU?mc31vW zKuXr6Bb_O&d|lQPkdn(8k!~s&O%-hTRnEOVCZzQ$btPBYX7q+hlJ(e;ejYF`9*~~s z{r{6>LrR?%6@|aQIv9|WL2jhJR;7i-O{)W;Q8KQ+J7+sdb*v`p08%nZN9yoDS835; z)A@ju4DcZxe#3w=fA2F7MoT^bFGq*3jYbjgIO zLO@CurXv;qobT$;El(eik^w%X2i+%96(irY0i@&u5ThlK8XxTAcH?z+F|>H}P?fnF zY2qMuq$2Mnva@^UUlW|vAWfRJOJzW{`UFVHnslU*QnL*XuK+2zoDu1`I9;mxeZDRC z_Lz`<_d6x-aBX1feOp=DQ$2u1UASGjLNbUE2Q68Q){sjJDLPkpxh-{@%f3R<+t zwy;nmy)}XzX+Y{?nM=-u6v0Ui(!=6Cs>^fhwgIGMO*+yD>0(7*3LqtyGa}7to=9DG zI;qdSJtm~5Up1FhP8zWSCP~&~M>_OH{hNT4jIklTS6!uyk9%kgNXZ~KQqi?dM+2N~ zgM~DzjkM$HmbrkGEKEl#j%zJ7KQnYXASDBQNQs zl9v73sFCjcn;YqPqjoa|Cjn{Yl)0XOl&ncds*oD!oyrHK|Q}r0V$cJBfVp_P2S+w0x2LR1AIvLy)~ia<{Li?87+bI%ENZ<@q+^D!E@=hI@(f= z^mPC`((%Jr%2w`+8zeZXK`K(FsN~0&9l*e}2mCP~&~M{1qI)Uy8HVG87+ZyQ_?lJX6u&PL5sV4 zZ?#e*%?V{kD)L<_^Upek7wpyj*pnKhvN>rg`-LVkfRs#XBhB7nfD*?%)79VSU8*^w4nM%4kNWQ+~zw){)V;~ggK1*Bw<8)*aM zM&fJAS|^1xs*Ut{`k-}ylq^g~TFb1Fbnxo~j{qqd;6v)ywj)($=Jis@XbGggk9y0a z7C(IhEk6Erx~&@N?-}e!of4PJY8zc~7M#=|-PLQiDlC2eEkH`v)J7Wr&7&(IC6_ZI zof2&=9hV<6%Vr4{Ohev>v400n~ z)$IW__t#Jrk|NuJm5vBAHqG)0V=c8m7U%dsQd=wi&gl zsoJ@6j~7szEjN(tHVqN;ttuV zUf3Mp0bU!hQ#Py9XB}5&WOeFoUsG}2r^`NAksIsi`w7(gj5=|Gn$^~t@$~5vtD4d? zji_H(n$9(|Jj3-bm!gf`YZC2RjC_p=KCg5Cv7*Y_pX?@Rzy#P{ekt;<78T~urf0cM z2Q}DL2^?TW%K5U_bMBoH9@T&qx$ILZb*z84sp(e@7OHB4J$@y<2*AR6MzFI>T&Vt| zY@B#@$ON{|)@Nd?(LE@bCsbqyn<48l5Wqr?4eXSPT;;BC$6^2rNp7$o%`L^L;t`(& zHLDGFT;ZnY02WHq!LGMk({I(j2d@AuB>2FV$i_K$Pp~>7Xut&6=AG=_kMtS#9@^|M zp>;I;u*z+T;ut{UIy-WdQ3RkgwXdh#+4z`}Y)u$vWGROzZ( zRXjUn0-HVji8%U&X(N~?RAdMHy^rH101G)bu&E{a%5y&LJOC^txxxD0dri5#dFLjm zS#7YN&)l;Buuz%~*5cqtsa3aDRsa?fd|(#@Eq2b?5@sc6zy#PGLn-%i{pbQ{Q?cBq zlNxMt5(n6T)JU0Op7(FzQ4QDwX&I`yt!}gfuuzo_HcXnB>M#nx!g@xqO+vCLkIn7z zk^o}FH67kz85!wI8jVPM5A%d5JJ?Si$F~4j$gzRFHY`QyFy&E001HWOu&eZbP)|-S zI>z&K{CRb1gDvR#=ox^8(sZydCMQYHTYKdKSV-`JO-!zGw)iyRil6}#U~iVskT;po zc`CH&>bs${8tkiN4zQ++rppeM+M5cGYQXOAc1Wct)Jp-dP?ZigR9g3C)oTC?>lwkW z>m5e9uYIWG*&)*jJKFD#INr3m8_W|bvV%3qnuMQ=ha4N&HIbW?#g&a+04yZA!T$W{ zA>Pung+x%Z+F*CCDqjX*p)?)rdvR@9pZKI+02UH_VEf)$?A)|g!`^}hOn}Yx^l-0j z{<{{m>D=(DwHj=8ItSQ_;;FLC1s%r;k7~d!Da}$1K0Hzfz(Q3z*bwQNSKi407S=O@ zt(*MPc~F-NK0G^Q0$Z=LSbTWw`GGJ`sK^f1@=GNCl?3G2z?!aKrVP6zy#rt&$qjb9 zs)aZ=GoYEEX0^dSI@MAHV4*Y}YK^=8RKm?uCfx02UH_V9PH{ozEFZmkAm$0akjMa<43q7ekvp{9J6* zU{4otfE9_tWihU9lY~b#V2z5iQ~@K)Dgi81rGpKYc5x360I;y05p09W->B%#s=7Qo zWCFWC*FZAjdG=tKCsbqyd+b77KL86kHn4Lx2P@C(_tXKfkmLqi9Z*X-<*xA{LCtD| zeKK@pBLEAf>0mnyy6*D8dGI9w3kg23XZr7TK6g=mU(kRFu;Ul(knYI){WrAf=`h4H3Q zhp7#=b-gET04zl5U_%@0$d;@0&Hz|Q@PYNnzU5r~z${GAfC;dxVq)Y6JB#kYb2{!w zik%v4c`*mrdcnc6VQEEYg-11DZ(YbyJt{vj4ZuQGZLmW{dzt}QSkDM{qf0UMcT%B0 z&kmWuI(k%#3q#(d!aSiOJJ{T*&AR|t$gzR7xIIr9Fnhxh01HWOu*!w~slx4Ldj&PC z4R*Ohv@U>!(sZ!J;-gaOQN2L`77~15cg5LJ{T6MwCuqO~*yO36?jtOcr$C$Sn_sY3 zgWXZe0d}>XLblAOh!P&vfSvOzSM}F%~&Mo1A3)B{k&Oz&7w&p^VbK`xC%Ik{fLFyWoNb7Ekj9HLDHw zmu{&mfQ8a@u#>AtNUu3q$pI`R_`uHS5llroHohTfzy#PM(@)Dicbuq%HlLq=-AxU) z;vNUsLw6!&@t(W!2QFt+1GaQVo@#~F$i4s;qI9tTUc+v(>Iz_CJtJ6q>roP$V@vRQ z2V%reNqir6?#iB$0_W=OFi(iGgLNMGZ5W)ekYfY8I(nMY^`9Tt04yZA!HTY07TikR z^nmA?{PXJ62AjS+AP2xgX*$>y3Er~1`*uzPu#n&bYq$FlRkv%lfuI2sU=LN_mOngk zyf?HNUtP~Z4L0jJ2Ux4*NSSqr%YNZe4cNY0@>FwgB-H`1P*of3u4+dKfQ9vpVBb}L z7ypdCK8I(AOebvK&Ows4%FIhJPpHTacG>$!BLOVr*uXxv9H2bv(9HqBLXsP-p}nox zCAa58LCtD|Z8~>vTL25C>0le2Sm>sETXYb>LV^$MTHTIfKf(A^0ZQ3eTE*^by z0ko-%>e)jL_UBs;ux{}YGK<=OmkEz*z`msptL8N}-VI=(sy5io2iD{OSXj>pwxoX_ zv7J$qK%N~kfo*!LyQFvW&UBb3RAdLcsQ<%L02Xp=U}p@8Rjxf#7!F_|$qiQYPMM$Y zd)QV`v)W+qHM8jrV4*Y}tjU-auGwLmmjGBu@PQq(DVlmS*a~kF;1P%c6JT%mJS#UT zXyFKL{wnk8sRn!MD+gH7*C?69*z&6Is0OSkDNp5N-rx~{g{seM#LqFgJJLHLGwZS%X^qd1=Axa0UThK#le8Acdz(Rr#Y)fY|>Qd*lVmJ}t5r_d3 zV8IKzw5(1p&~I)8d#fec?|$8l%|8NJ1x>J?bU9)B!C1T*vQ69r~&K8Zxu9P0<6L8 z9df(hMctsy_|l!d)nLmKc)-r@dA^hID1fz~t~ml&sHzQCk(K@zfQ9vpU|;C$7fa1M zU*_2%6WGPa%_V0$jJgT)go^B76O9uy0W9R$z&1zZePs-HZ?9<)?|tS9?qOm4cL#h@>J$IoxTBBh-!nKV}E52fQ9vpV3P|L zQC>q*@QpW!5kDpIU4k^zYH_5>!4<$ll$a;&gpGUQjo)qqIX1BO#@Z`eM!GHru#n^i zyJ1j{?}p%yH8JEL7D7yS{xz+#{O4Grfxnm>MIWWi+PFP6rf!#N;1+}AMA%dN|nt(?Pm;f6V*1>)H zWvT+&ls2+=QiILh$pLn>S**<7=EFJsb1vkO^#;i~5q@Ipq@pEL0@sNjqVaPmX&6U?Il__C=F_lr7WpOaLq-xxt>O z>ZY{pD#3RdAy51`(FR*NE<6puLX-}6Ui(m&?Qvle01F8|u#ep3lxxBFNrDDUfNc<0 z;`ZjlxySIFMkGvdR)hVK&H?sJi&)u`x+nV!k7~dM9LrK=#G51lSg1+|8zg-m_7K0= z3)VA&-Dh-x+LJg`muH7eV4L|q6Z=FJynuN^MRu^eJ5THjU?Il_)+2tR@@&=dX8;zG z++e*H2U3=sSKu3zkmm%u@lJ6#fQ2X>Y+NNfzpU*#Pr|itJ!TPQw)d7IJK0SDcSgwx7LZFo1<5 zH(1en%Yq-DcfAwTto8}JrmNR>01Kt*VB3yr=yo>t#2Ww$2|lp;zjdg`|NH1CXut&6 z7f)^Eot>Msf;LZ&$`z}@E-&N&`_zAd%zH_QN_bQQ)?rw-%5Zpm3jhmMwZWRi&AJO< zVLc<*K=WVJKh4_WTObf44jsJd3MzUazBoU2Kg<)N>|l3|X!;SrLXHh={>?C@f5M3h z01HVTuq~cBS5}N1!t-?ed39=ot>d--3V?;ubg*k9mdb8YlZpT=B>2D%eo%|*dSlW; zK?5ehCN0aAH=CD@pAjq?dt0IgTY8EIY?7QPtjntLz{e>DpUKCl*VuR7Uez6ljHU;^ym zO>?A=D$f){o93h1x~ajwDCGc~6c{htmT-T&@TdmtKW5pgln*@-EL5d~4VKz?SIq*j zu$~cYl4!K#Y>V`fJUe6p`zGB|vh~KXH84-8$PTv8-Op#?k^pjSU_19}r|gwe(FMRl zk{hfj^U~4iXE!qiHLDFabj{aV02WHq!J4(qb*;VA@eo`RK!Oi!eEVaRTsE&r(0~cB zih$NSF|3R0Fo-_8ir*kKSA0goUU!*wUop zMgSJpGlI39c2m5;{H-U?4w=Aa%y*D%-CFtu<_Q(q!76WU$7@)~v4Qpd+fw;3($OEl zLXsP-%f*<2hxa!=6V$9W*xJKitpTu5nhv(YEKW9Yns+9Eg#;hib8XgA^_nKF7BpZ2 zY>wo;{OrsO`~+Uum=Kv7?Dyv!U|(h~kh$I&gV(T}Q4Ls2i#*lODC++pHcV*?U?ER5s|~hJ(9n4R7NT^pQTy#=;jMp<0Cd!itT?iyw9^krW5w=sOFL%W=A{00RR<=dD4DyFus{& z2wW0Cjty+_dn4s-%buA47LwdxPp2&tkAAMZPEfPjVDm>yP5@XaO$U3uwz2fp+NLi6 iEF}2ACfZ(cZmEAA|7Z>#ffz6W_R>Q$_kkZuH~$|Cxf(hE diff --git a/000_image_stack_ram_based_reward/logs/PPO_11/events.out.tfevents.1680180514.DESKTOP-9E17TO7.11796.0 b/000_image_stack_ram_based_reward/logs/PPO_11/events.out.tfevents.1680180514.DESKTOP-9E17TO7.11796.0 deleted file mode 100644 index 6fab041903adb474c11c85979bfdc8d7c4e6475b..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 14007 zcma*td0fo-9|!PIXnwBPLDrFw$d=<*l;&%i8MGU_uCNxfLnEW9$&?7|sy3+{Icg)) zE^@W9)Q?)G2DP>lI!IcDoY~eHYxUcm<}v$yedl}m)8q5%^?ASN*|+KNwrKhHA;CMv zI=$^FZ-w`aiW8ye_ZzA&3|CAQGhZ?2)<&6UOuQrSr0I&;4ORNQpas9c70I2{D}E<^ zEVR-%7$*w(;;w}?`FKx3cR}aSe_kXPMR2fIvqB!A7HWjkMcq{DY3$c)Ni9^Xg5`^} ziiM#nO^~pxvMte3ujw?{*q2kAIRW}?1w8~^NJ*_C$X_W;KB6NQ|mU*h7E|Xo1!N7Tara)hRK|euHV{k>V`tLcFe)2Gd zR;379s1#c0(%g3}u)WP^P_gaqwxE?uWctEr)6p^mE)0wzfwWb+1Nlr2& zjd&gLIUps+n2<^wE%WA$se21Z$w79c!QH2ecAgb_@EOz`>CMmwJpd`Wn2NMr)+{ge z(-dz&N)B)#wW{&T4Uhco7@yUWknY~zU3&S9&s`_uC&#xR>wT;pI!u{uK&o5UidkvG zy*SymUeP7|qb8=GUaQm}_blyeXKWqPaCi!~Qk<@fklw!9$r6TxThc_-WFcNnrmHBZJA?ltX^Rw`U|V6T(A0Qy*3LDJRE6E478p36cb!tm-`3j zUj1okI4n4$HwhkT!6dLvz1vGe(_f5$G53G+%UlE4(o`0(N6*H{Tm=h7{G%qY+C7!} z^)3O9cE))PV4;-))?%&nprif@fQ9q4U<28un03)NJx zC4Jg>Jvyng0I-nY0{iu(*||SPrF!vNFbQnkuY;wE$K}Ie%(&n5N(0!&J1k(Io{Eu8 zZL*usKWYNI;83~VyWajNfQ42n*yU2EnH3oT7S7Xxt#--~6{WS>$Z#)w|dd{M`1SaYydqwb9Yuux3} z+j*?W>(BO@y#N*xTwsgtbjV%h)bL+k3nqb0YTr{D*494&##S?csfnVBtJ1*lDu|5Ziau;y2C^WBhs6S<54Y zWlw1!>=UBQU}Jo?WdK;nF@YUe_EfiMUqc;$g(N%J!rd#0YwtV1<9H=oK0D39UX8T; z4ZuP*6>R35cH&8kQsw|yNN|CDlU9~9CBDp+*Mdo4PfqM7jro1?bQrVIUccM`_CzfU z*ksiv*>UwC`~d@N)C4x!wn9JK_CGZM7NS(J!P0`Lp=kgX&eMWzv${QDwRTT2$8dB{ z*z7TlER5x$Mz&E_?%IoPRl zOY#9MR8zsq+B$mWdtX7Ykl+HlWN%i^n_ovB;k95A*us6y67i$o5@5_$Du>kuu)6ha znBT)zFO8KAdgkx2@44>usL5gdkicX^P1O!Nnl51H%QbQ?~Z{nwiawZ zz(O?@>_nG2;)hR!mjNs!xWM|ZYR-w8Q-Hsjd2xgUkF;PC*k@V0B@t~x8ezLgUlmw5oU=r9}xo;&i%AV|m zF*VQD#u&gh*0O;0y%;AGOjI6$=(P_lQ4?6}z;eBXn_vfkg(wwlptRTAgbDx)=V`$n zec?>#n>y!n+>j3JcwsFOcSx>)eL^E?pA@j$S`YdHz(S4*Z2a|d-TB%7s{yc(WCy#r z`d31DUV~pNAy4`a(;Te$Q;`n9LX-;jedb#6koV)R0a!?IferE-=K0M`=gYhnOalAF zwOrEeReKwFO(zD|#2dh_+hEE39@g$0{ zABv6uuyCFh?ERmWME05epK#oe?g{IEvx!g#ufZoQG%|y={{F%&01G)Lu$Et4*6mxI zdkDZnk{#@wY^!nBnGRif4QmcI=1Kol01MSru-hLbi@z-o@dB`r-~#JBsJ-W&nU8z{ zEPMpgf=OWSgq)BhwoOffG1t^Q-emxrn$H4u$-6Bww;#9Z`A1D)!)}-BD{CM60a$3I zf>ld>_3P&XSU67$_N-zM(br=>{*W1Bj89luS`E>3y^j^_6QZPjQr;2_+~#l|z(S4* z>~rN6op0KtIRF-t>|n)yX+)o}q0cy84yGsUv`)K609dG|g1yvcy?Acj6ng**2`;cp zug8q-8K8{iwO|t1GRYfBV&xh94RnF+oZSYnC+b+h?k-A@^<4Us6>Nw#Y62TLvO@n+ z^6L=*7NX{0w6FsbCk3sTp_Ny3!xOLV^pd z-}?#fYqh60@LDhlY|bcqN%ND4cojO6fScsZ~tzJFmM*s`wX~EWgZ%0I4FSy2WL%JtyW19lvovYge*e5hHgRP1l z5+xW> zQ0$0c!-f@m@87;zuYBj8zJKm@?s?96=Euool8i(3{`>D&^3aV2h0a+!oDIt5ruAI{ zoV|Rl2F-Q%4I0?f-pa6Rkh^c7Ux16BbAX#wVDRkO&H-UoApu@N?g3Wr{~I;K!^_8g z#()2(>x~@;TK_rjxDiSd17(ZQo&P&-qgQo08yPk<1Ki1aKM zoeXdf`IFSM*4X8Q9fc{9HEB}}Uu_rPZ{B3fKT`}G^H2|_XkysZuwl^u8rI#}-#@@F zbjB>7COz-ROG1WS_vD}6e<@cVFaH@H0nV;LUVgq!eogbIqRV5pclc8;_x{1bP_MaR zGs8wiGQio_)4j>KS0^Z&Qn$vP{>1wIo`KVBVc6WT@qe*@&sTt-f7lEkzresIO>JxD zf4UfOy!)Tv>}jpWLOpZC)`lj3f}#FC|E|;BZN^;Z054}>SNA4*s?RwcC$y);EY!!{ zIl$M;*KA+8UZ0n*JB?_w(^`4V&Q^;Oyr0Kc3nHwA^z+HE`a5dtzEU*V!l7{lD1c{)^== z>xLG?5<|ADc59KIGvz^=c~Pm_*ttM-l0a&!c`^EKBS1>lq$6Es*I@IRqkxng&WhBx zt*K=3)tSTjr}tk&5$TC%O{l`l-jkq{WIb-A>h`0i0#Y)@g>=&38u_gn8%+hIWRM?e z_|&GV54P35idiTN((9|k0V!FSj#Rd`t~|tNuQ4Dc142kYd#_gIFP27$X)S?tQu`vg z#UxDxEYUUZ;T|p0thW3}@5e5v6rBX5rM+S^0V!FNjx@&Zc$xWcKuQj0MLMJJNJ)VE zuHO99V?+9Vx(_8yebo{=N!H^=`sv5~1VBp0xRAz|R?kl~Om+dJWRM?eX7yE)9UFXi ziCHKUsr$hTPJomwOh+1+dRuB-`1w5`B?Cf8O*^z#?U`$kDyFpr(q+nH^7@q~Ca}c$ zdQJCfk!Ez|M(Pk;q9HYgnVCTyv$n*Sd$Jxk(%6doazIMPxR8Eps+Zq>UDgLcN(T9n%6^7OylVBU zEoPxiq|4GD3q+~z{siTRlYQihS3_waAfM_j&w0GCx@wDlfzl`8?^4mp|3@nG)P%2SSp$%gHR(tr>{51_n*maCI4jZx zPa08f!yKyfPmc|$g@uZ0^{8(!bdsz`bW(ev@c-AOx1~Qe15z@^h4f1NH}!`nOD6zQ zGRTj#&6>~?zvrLrDQ2Neq@A5J4FM@xn2t1~Mw~o(ZtKl}lne+Vm8g&U4(tC%L<4(MsCOY~5NcG$`t(!l-2}sGBbfk;zYClkI z1f=9}R-{LoZgi~=2Vz=F zAnn}SMDd~8wtcX~&`CL&TBL6Vb0c;5ctlw}W%E7JNdl>dX4D4xbwEniq$8bg7j|g# z3qVQ^XGOZ&(nnGhY2BQEdTdAs2Y67u8ppapC&_x;NUhE7>jP3U#)Y)L<#)CB=Ore9 zlnnACeJXXO`p;?>Bxa#Zq~%9$?gOM`VFpsK4T{I^OZe zt=4Cm*)dgvL+L0SyjF* zASH*hBAxZkU2@d=E51aKDeb*AHl#gTEu|V#i}yh%$s{+@54#4X0#Y)@g|w{A7q!$y z>Ig{5AU{&K&i_z>#?PJj&%=KUWg`7JHNhH?l7;C=+t-SgW!zk#0HkC<2W04Z6Mjx@|}q@V9{ zKuQj0MLOIlO|rIw-6HiGO=KjN6Yqqku(6LWIzb%tF{eQ z5kXCEL2Jna5UnMUCL9lvhtIahd*1J^Cm+=!-RaGb^l$sUS8=p=p^mkecp@f=K(1h<3idq z=$E=iLe^J6N(T9n8kSa3M>5V@idiUgC$;Yx@)nSih3QC5vk%GAj}JHmNXdW@Qir&4 zHY1l@Y9pq#1kyS68!C)CMWn+LmpW%3(;{6J$c@yYiCQ^v+DQ-5NgYxL2RF^N{_TbX zQnDr!X?8)vEI>*QXGL1!VJorh`|uk7^w^NL85l#Q)H26wQnDU5(&PTWX9H3)#)WiJ z&9~~%%J!20DH-HPy2a%l^}CVsu9$@~k(Q=9wg;qSVLH;wzY1k3rcd+$DH#w#dMBu( z%A-NwWI#$DfM_j&bmx^)`Nd5Gufh^br{6xVMY?nWH_{6}dCKWoV~Rv4bx1Fa^wXRi z`fDB_C2KN~F8A5|6p)g`S&`bNDkYajHP7Uq9vjk#EfLhLCnJwSC&_w5Cuuur)}*rG zfRv1JA-(e9o%-H9HzPnw2KkYOn*N}yF300rUouX-Lu4ZDpElbWkdjF{QjhcV)@0M2MS9;}E zi-+Q)z;w=tLr!h}RPFR~*I2AdcN+BXt5O#TKg0 z&68(3{+Z!#|E9xnhTK$*>)IWIzYUlvm(^=OUZ^M9)$Q8jPsOy4muFx_eymOh*Hg-d z_uND+mZ|k~gnYimpVFa5lAl{i|4fR0np?^8ihF$25yJf7Yu73ssq5 zRdJK`;ja0pm{e<1x3vtl`bg@h1Tuea-MFDRzJ z5Y=D;?Dtlwa_?jMJz<$8H9~T=U@xxX0h?ZSTxoVfsV_dN1N)cF9L?$QPj&znsxrYU zGmgpuER1IbJG$O>iOsJHQ-K+>f%O;@L3LjKmk;z4DsqDza>K1VfQ1|vSjz_w)s_uS z#{yVL@`G*DKf~7CIhz(Q#{Shbs;Ji6*be*g;!A+Se_rM8Rv4819; z!35aHURjEYF-fOknbqvpsI*{Jn|Q$9vOKK3U)^qj_^1x-u;gHk`_D zH4(tVcvi6OSH6;zRt%U9dJ+G;_tHO z02Y$`U~8WINKLo?SS4z)Ot8O-n@|82O4GsWr>~H$+P60dz(PU@>?Et^s*v?ND?~Mz z09)1MwLJVv-Ue9abSKI72zh-xIH4d80b8dW{xnDmska2Vfz}1bbxA z1>9j_JS*5OmrqJ;@*)olERGFq)Aec8D=Vjd&`+qy4R)ly%~${nIWDkQ2VPT8AHJLd zu#n^j`=#kaYH85AMxqwW1p9fFg+G9W(sZy_TiVJir^?R&SV#zgec8xc_4WBeXHg9% zz~;^Cst6qE6$Q&YV^S?o3wF&x9s)Bw(MQ*SWb8q9<4Isw_w&$n3u{kmI-#=jftNCER?2$olvcg!fW02)&Ld~LST=(v{$XDxj9=@ zg9)(fO>ZljPBO;V^~eDu)LO97IXqxv4y{+p7MUeNhj^npu;*SxYO-8*x&l~;(!mDU z)i9d(2Ef92R

&J0xM<_Wdm|LpHEq=dPeGXO6fC{e+6#V6WX+mjOF0V^SWsLBL; zKL6DL01M+;!M>T)oN6-YwU@vQ*}w+&%A~$E9RC6O2^G1)dUQ6%k4+%Q1-8kOu zmiVR%lKf!R-8x8vbKaj7wOA(DwM(tm!ww6j>0mQWhsr0K@AL$)kPrep%#^aV{j%!3 zs0I^YAK%%b2>Z6|DlD_+kAhQLun*4jfL(SnNg28!wvG6x4(yd$(VDfPd2#>?Rq0^o z*j-)Wu^Yg`cvi5@=N^~%Jbq0H%#aQ2^W70tcCF_BKtG`(H(0MuW%xaO$Z>&f*KfZ% zs{4#e*kK{b4|d@~JE>>O4`HGf%LF^V?3NLLh0=7ei80yoS~DFC04yYgz}hJCa|e7F z@>o=Z39yx45*3##Lhr*eH%_Z_S_}4a2@lwLhm(|56UKXpkLtiy1jT4--`&*}z(Q3z zSbw|L%U-_%urQt#tkP$n+ty8J19&dI+KcONw*ux&n zQUNUFxWGPg*rSdK+mr%eA;}N+VXJY{upmQ)sKqkDt{uN;Gk}HCbgsQ4J=*ZY-Fj_%YCbBP?_9`>-=wuzMf#fbB3hK^c)%ju%b5Q61QV z<#8I90i*D?7DSm~EnX$e1h6ok6>Pf}btwl`s+GXv*uY-yc#w*+pX>|$go@l?PY)d@ z1F(?e0=uL4e)W~R2L}RJNb-ZV-!w&<-nHHmQHy1QEp^_$3BW>WI#`!U`{kYbCa3`{ zB!s{QzBrKUHZ`q{s0I^YBMav!%xw3S!ZP3f-gs6EcHL_pu#dhhQ~Fv&b{8Mjf&JV# zPE+*h!f)7Np(+#XyAxw70W6GX1)Fm0u4G>D&i4W{WCMGrUM7`vK@kA`go@l?a}Kp0 z0AL}<1$O1&BkE6G1~mk*kmLvJX5l5>nJ|90sKqkD9-Zsj3BW>WI@p~7J7hoY*E<4O zNC<(|Jk7N^^;(Xfbiomb1`}XoiXX~9Dz^l}GS$Be3$SqdN|LI-EEJd_8`w5?Hc(G5O~mhJKt-aT zwC`!%tdu_hu#n>d+qrG7I{Z-E#sC(Q{9s>h@R#29u7Nk5Ax~VeGr{gXlI{RtAxa0^ z$2eV9vv3!F`2`Y!U{^ZWl#GvF1UrIxqoV(ZM>LoKd*SvcdF}o6*26hnbn07?7VM|+ z>fGPfatMx9)_nUYQhZbgHZC?^6MOw5UJ^i6I#@ru{?E5I0LP+UdgMRhi?RC z$ObmS|1i~c>)UqFPpC-rlLod$)ZZEa3pp;ZiJ2<3L0FsD02Y$`U>`{wr3Q(|Hi%j* z6RcYH_y>T6(sZyceS_tR$xdFd!$Lv`Y{8{xIpgiumx*dH0XEgBwnAFpqAM(O`nMM6 zwO}8`@qn$EAFGrVJ(h}(>cE=UjMrp2Ec^&NEL5d~^|#y5et#x_h4HLluU^QM+)CZt zRA7c|U~fzap5wCssyl*5CZ#S@a3G(tvcKl)nEc_&jY;_QRjX;!a3b= zOj@i3do`H{te$UQ5N~T`SKmY3dpsELYeSS9tgFq@ApjO~TwuR^+@-#{^3y8-3rT*kC2sE0 zf~mh6i&`vmhjkoVbQQotX*$^b?cU1LzRTJHSV#zgUC}kbCfIMM3xI_q5Dg~4R%@rP z=$jCZ_ttk6MPAT?Rj=m(+rcqTxwflo40MP$ssp>VZk%R{(zXqNg(wqjdWhw701M+; z!Jd8vX_o}^{3r#0g&Y^yvzz`=&+#1;3}7M2 z57ydgs&v_kBK(jY^2B19VDCF-{0(3sN(bA~*H-rJe(C`L3ke~xS%FSf0b3olN!_ybFVE1nm0Bb$@=K%3h0Q+`EMkauTs&ue^c2vMiGXM+YS;5|( zcR^AdcH)=74B0LTY=^9)lBO3OfPO+nZm=V(4Tu7;kmCaDuy2#veay$X02Y$`U=<6- zOaC$VJ|k+eOt4-|RBi9=trXQ@0<2M9k(`>d zW-%=DYKM21v|u;v;{j{iH9=|od!3Q^s1B@Grx;DrUlsQNEL3HJoo{ste{lfgS;213 zEs%^~v+10`4B5aASiXX~mFtS%&47yBU{}k6W&v2pae;kxXM_4{VBK~A7Lxp64Fji2 zEiQCkEo!k$uz`6NX853L?{4pM|lYhi37rdL^TYOXpHh65T#-Q@V000YBnPB~&4SfPTER1Ib zyTATE$=j?xbp&R}2KMT?Na|SL>xs}$s7Umac1a+)@gASs068wO`%a{*AG8=B31A_~ z54K!?g48iAbD*fjGQqBkusQ%>p)?(=*}2=YsOzUk16W81fqiv9SVbN1z9y={1lR<_ zrSdLGXQN@6%^as))q?$Uk_YVBIm?u(EpDt6AJu^!a4|-6wCbr5fQ70|u0_Wo;jU8M1+W)q5Fr{JiBW=qFU<2K(MS`Zin=K#mJ+qg{#W&IPUUCo+)a z2ix(PtMu~F`QjGK++pK;w0a3(p)?(A6YC*z)uVCi0W2hhz#iLpUNvr{evqgJ6JQg^ zUy`rcc0K~mY544-5-r%0%RFGePK;H?n@{U6KB@zo{_kzAYbMkq01H)_V8?n|7Xnxq z&kD9%VX>q402WHq!Cts`QZe(@{Xzf>2_dlM&vFLV8FQ{SfQ2Iv4JN=Y zb`Dj1oK-a$mN|6K+v{4er^PkKA5N}im_M1t(=3@H`wE-+dnP8{6 zA1ep2FrF3cwSxnw9t-y4XK@fCF6;1vgV-*ssO{J5Dg~4Zfa6T(ROYfJ6NWdY0yAXWVI4muQ&X+aeh08nk?1FFhfS!y>kWW~ z92Z!>bxYN!x}8e^u#n^jJ8J#kQrWtDe~DTw6YR7r$~yoSO4Gsa?)Q)ERaD4M01F8r zu$|_c+UWUoeJ85H1lS&r>MCZn^IikX^lKAbt_8d70}t4R`7uhHlE(4kqdKsC-4irJ zo{ZiPV4*4#Y)tCd8UPl?vx42KiIN<8T&IV?4B5bX7(`PyW`7?9{e+6#VAIa0mIGMG zae+NQVU^nA@`AMh7Lxp6lZ+jup4smnh*~TYY(%H6cv}lf)4`6|sxND3(kvIiLP7}a zvr5C0!ZHhsSKriv{q}?C$p;Kko zT&p4gEF^@$K9u%Vbc*qySh*2!Y+(Xs{|F+ytMt2S*?pOn~h>w~s>gK7S}IvrcHe zJ6f=%%LTwb>|24~hvkg|*yX?e?hjxg$^?5R{D?2?urQt#tZ`pE$v>~8j|CRTw!<2K zwV^VvA8iC108}LUNdxPoIIRzt1d!tbdt>uBb$L|vZU7dN{9q^LjFkSo*abhR+R=4m?7jIMt*0XJ*Cd4T-62L-~2{zm$ei49$@vLAQXfh;i z3(rpiun;58A?~mmOol>i~uYo`N0NGc9OnMoaZNSI=HT32O7vW0$3ODCY}t)O zjc>Z`B>)RiCfF0ja(oyZjAsSw{&1J1;nDl}APtCdf|X1Urg~ckP5`hFCHhGNyP*6m z{=0#Y;{rQwz+Cl~+mr!-g(N@NC-H-&Q#y9TZ+k+XSS)jg-QRNkIRFb$I@oRn3VF!C zw_pG)B!s|Tsv2)ow&AfIG}x*O0gq@f0k(39Op#@N48IT%yQuF&E!ZD9JYWyn#41l! zJC+Avd80b8@vW9?-ktOu31A`01pC&v$`39HUM?qQ$qH6J`jW)bZv?QAgJJ>iwraINWAAp5~5ZLY!{ZxHwXz({ka0H^k1lX0)7K(eTS2loUK3wAR zNDKD4h6ij|LX6TNci?mJQ61Q8K3osLLXsbB^H6W8?T+aM zq87^pdvCr|Hh_iFbg;c1_Lh5JpFR-4LP7}a^Ty|LH;oTX6V+e>Y)SiF@-_p)%wd`C zp6e>LV9SaHz`89RR4zUWU`=lKegI&hDiiF%!D}}HSQyU=HhIkoNl(A!_%R;DICogR zY0Icmv*4@HPl$4Z?T{DQ55Pi>3+%>KKI*H+!BYV&B>BOP3Lh_x{9=hu4S_tdSSHv+ zO&3D|3sE}QhI>ZIR*(FB3BW=^2yD{^QMt}DN9v1eFah>T#%KAbSFQ1RLua-WKh}ah zbDall|9UaX8_HAoNf&Qa2eu+}g(ls03qEeM>tUiQ6YN&IGx+pE7|#ke)vW+PdaSrj4pfEOqs^_`j5cCtG++cH@TU-XPkmCYd+M+6Nd)7}=01HWeu#fC~q@GWk z;3H8WPb`)R*5O^U9e{->9qjefr)6=oH(da*kPrfU*{wxx?*2{qBSbg?(O?2>$er7= zf-#e0;hgStc=tpL_Q+ixuPdde^d-$ zA;}Nc$*Q(=WVrqyfz!ctm*8E>wQ&FzO4GsCu92dsXdj2yu#gY}Yww^`ea|1YT~vb! zutuqK6>o;x;@$sHS<7cyuv?z+fc5DZtF-F5tp#+5H>v}>r*o3#wCnQb02ZQ5u#QEo z2f`%*jAsS=C^1Vi?$au~j{z}Gu(jh{sAhRPGohal(k%hb@<_Ndd4BrGuSSGgcl|yGwQ0VId&|wuZ+)sxw#e zx`}Eq0oJXTf#UfYIX=+XBGc}<7HrZR91U2mZ%v0>fqp_oZm@bLOIyMv0pz&A9vB#| zR@GT^AHYJAAM6`5TWOU`BwnyXo_B|xeX_w(*kK_`2djTROTL-<^##B}LI|u^&KsM{ z;mcx0HJAW7UO4eYbzpy_uGAbK zlpF(KA<6{nd`*GS-wQX9R-2fJn{9x~>71G}wnrw!@PRJ9BW$v(XFBLriEJW#Gd!%iYrM=$Y z6~ID52yEZ8M^wQVU*Kooa0H^k1lZCi?GzsexvYX^?)0j7sRes8UI47;tQ`DiB5xGH z79ak-1HeL*33lexUIqXb#Erae*D<9IxKu^A&&71xbFeJ%{;At!I}k5w%z**ns(c8v$4-O$Ym+(}Zqm2>Ctb?7Hl zB>G7M+wyDqaR3WBF0eQ24OaI^xBCSPuThZ|8eB2Nz@xH*kc=bz_yQzQO4$2 z8bgP8qdKsXG0B>WCV8I#EJT@LYqiWQ0j#E4f(yd*f$J&iis z?`C!ACq%iyZqIAe8^A)23v9DvzUuu|c6gTnlKfzuj!u+bv@e}0a610`>turc6m}^c zz(Q#{*rp8>vcem`@h38n5CYpNyOCs7m(o3=8ccwl-z!`0@NqLfe&PGoh__m>+qUz7 z&2Jd3+#daG7<7m?sslUed9o&aUSqsV08u7bzy0qw16UZ(3ijTcLy}?LZjBU}A=?fc z_%fAJM~?jl{e+6#V3Y4A*aBF{ae?i3EkYf!yUGuCSV;1N?R9ac)M<93e?%>o3HIKF z#`xqHC`|`zf3!l@E86S`?68m!0vq#SqU!zA+76-`On{~8?UtKH8CJqFXYR>-rv;n5 zp9kz@%~IvHX+@#pqdKrh98)x=we#?i@lcfsw%3lr&j1$2vw}6OuTQn`?2ErRfEecv zyDjYi)mO6#AFc;cZm_G1#`grUkmCY7%ql|tE<1fbfQ2MKSm)8brJdJGhX|Ywt{rya z`qQDX!$N5~*pXi&O_9IaZCcw70 zyehXb^}`#=$S3L%dNP*j*h`HAaD#3;`@enP7X&@?8dC zVLU5Xy`Un=5rfvWuc9#)$F{>dX692?jT_*<(*+f|!FF#pEEd2*jtgvZdc1ns!)N#) z4M_5X4NaaZO_Iz(u#o2k>)p-D48TH^4%X;PGg+<56SH84g@h1T$9+w5O!s7_0$4Z# z(O?4XvXXW3-V;NTL0!{Fj-Rz)&t2gG`)G2ca?_aV_?s@?s1EFMyHri?zLdrQ7NShB z7srfx3}9hAE7<-88z@zS+juV>V#GPby98N7Rn+@twQE2>AxiXH5w*5v`&u){)lo@8$W*$)nEebsQ8oe(A8F#V3{A^?fj|*oAHnbY>$Z%%Jr-Aeu$6i zz;+Ew)qK<(!hZ=7sxrY+9s2DBurQt#Y}v6Rl1b-R)D)N@8`%5rGpH7aR^S7op&~cf zgWEF>0a(a!fvs|#sov8?V*y|x$q)9UyRURmmkhjV19{@*gb8-Ebw*nN3sE{)2fb~w z9YY%W!43-vA+U9_LRGH@9>kx>z!8WB6JU3rkCG4iSvC&N>5P)c-?U&;t9ZbkEeThq zmbbvqk$9szu*YAfYPQtsfjcZjnP3-K#Et~8FrF1`@9e&me)k5Z0*hk<>#5mI^=TW9 zuUJr#=qGK5%`NSM4>X1x7ua4SC#l>})(O?2>$@#Hz^`80b;heh1xA>t28~Kq3 z?E4Fgm5vLHmExm1uu1x98l`zTKB@?+GQqAHQc?_HVLU5X7lU-kLp>L~j{z~_9O5-> zRi6NAN#K_`@QMXdqMtOdmhDc|g&h`hTwt?;da4(X@W&4hAjuDQLqf1ru5Nrt;B;_Z z!`^efi+2g2G##u%)px16-9!a|g@h1Tv)nbgkqP;oL^YTI+qA_@`MIHuo53GZh4HLld+aczp0{X# z{|FhxIKeh+xRDC!l{gss2~lpax9^0w0a(a!fpwkcpdPz(&2ZRZA;}LmwDvTq@1@at z0%wv7tmE}LO<;$G(sZz^GIM1=M{jBgU?Cv{*5HwoYNo|r{HHtN2tIuaJ8$}>1$#HT7WdZ+*9C?vug3(97a!GuU3V}|v)seKC4hyhOt7WT!tu5ijAsSg z&-(abzz{ouf5Ya01HWe zunmfWrQ=n}3q&oJc@2BXy=Vh~h0=7ebqmMH_k{1mUmQR}2<-6c-E77Mu30Cl!30?S zT^f1#u;Jmb%!oT>zqMeCSMY#6+GVk_Wv%iK;-fmSN4u=j^ih}O16Zia1Y3Be^=#N- zVLU6?q%EVVs=7b(1!l+wHh0@nYM_%|9P|?^a)UMg5mXbvLXHcpb#N>7=x5vA04yZ= z!5;e*C{=oI`y^_yOt4g59XWu7(sZy6`DwDw`n~VL4hsn(u-)!g=5CW);rBP;2t{JpX+hvY`@o^uiN!F&+B@gdzY(OPD3Pr{`(m{WJ|4+B_p3W*Sc%d ztd6s9SVzlG~uM^9I8 zM=w_=@5U0z0!47!r2e9lzOD=Yzhs#DJ6vG`HR~JHGtl>U^K!MAHP^4P zB;>UG@q*DoQ0VZ;$A6~ypaIVmO+6HkYkz4aI{AN7R7I&j&Fy6hQzUCLrYOmk2c|5n z?C^I*exsjCYLUZD44N3!^Z(yXvT&L^*VkvEqlahXTmCbs>%mrT{L}lBa`AMV>p08T z$;IEz$Gfq`u{yMU>c`F<|JKWXoIVKZH8n6cFd~w^PTsR!8=pUTk~Yg+a>oYgd(bLDzud(fhYI*i0(ry-igI?2Gj)8jr7_>Gp`5Rm~*Yo!} zU1vJZck*>}@^*1;EIDxUxRL#yd14mo>FVU`?dCn((bvh}wec|fqn6*|?3?}bw{Vrk zuRlZKh6eQw4E_|>%rvyxWSiX=ZRhm(8`!d9#Y+gZHTcJ%*`L5%A5S-zK*!m>PBY#9 z_amXXK+=a4<>bqXa51f&@8lWa`X{Eh+(p**ZtPH4;zRp`#hRa^h!)&PQ}-`Wc&<9p zRdiB|)WIQIUAN=iPJooG$wZnXKi?-v1xU%^tVkE`H>SSlH2=y!y*~{_q=Tfb=@*-B zo`z16^|+A^*|_~HASGj5NIgpQ@}d&vSpZTp$d7c!nC(_&Pm8;YS*R}3TNRDl08+9r z6X~+Ejcf)DeEA5Fk^v#4N7n@^gB8#1#k7_{>Q>KJRwrhp3oLO-c+fKqQe}H?q>{ZW z6>aOEKO{P-MJkz*s4i)7dpIB^Yci0AWXr3Mx0?k>$>FR>>%TFi)a`xq`KQN*^w#!QB7XT?45JKAEy@%4K#9t|QLbg-(+7xRH8~@7)!Uk})o%i3_Uc1>cAo4oJx$KT>J8tIBQJXBvxHs4mi}^UWLp zDOs3_bo8a2(ql`yR0E`BKnSVb+|9}rlYL#FwZm`xpEjbk1X9O#8)g0Bu*EaY8QgS#e z(i?XtP)iO6+VfA34e8T=CeZ~-lLydAvK}|mD(foT04W*cLc02R`7)4Datp1%lsYUAG5U*}{ugn~fl1W{pA?-c? z1*GI~R;0ZvT2pUpo|W=Xj}2*I*bsWw<=V}llVm+^q*jyOHU*?)j0qvGumdml~vd?75NlYPeWYTP@!zI;lk}QN^eYjQsFSO4ei`4at%p zU0`(%kdnh$k(QT_p$6Y8@#mi&8`AQe(RBMsX6vAnWIb-A#$)!a0HkD$3+Z*+DtSTs z3S$5%8RSQ5I{uuMr%@ul6iCK3uXFxcs4mjPu^rq2DVbye+<#Dsr(Y)A(UHK1*yS6e_Q$$CU5 z8NWEWCVPbeQZmMcbdN#Ryt2kg(*Y?N+lyIqORoP*nN!_gZu@U;f%e{;E!jt&n~q!-?J z3eDk5YLRZ8xK7iGRb?)=kZL%O|S0-a*B z`6qOetjCR%8vAAxASGj5NW1QoI8Lg)d{pEL0b%URl>6fRrrE zMB2QkkF3hihkF1i84yAmV&fyEe)T#Ma zgEV?Y6>g=+s7OUW%*C;7r7H`U8_3rc|us2_dh$^i|3lg_qBXYA^xzoNZN`kJd(Uu*~)m@@Y5I4)8n9560alVBkH~ks3t(Y9D_HZ5*3^T$zb*>QkPWQVvpb#F zD(D{c6Do3pJ$td&XaEa2F0k^%Z>n}LPVWP-kmLt@=tL;>yu0B{QH#|Dn-$f+9Kb?p zCfJ^bZb-*D6x0W>kPrfUxy29VK9j!jq8dzqjZ;fx&!q!5!7^KKzwl18!@iH@0V^?x zQ8Y+i94J1j1uJdD|P#<%Dmd5B-FS++c5>aeoA0A;$$a`21&8NuA~X02Y$`U}wyqPJK3ewM5inb&mwy zt~@jauuz%_cF2IeHe2@H-VR_PAq4j0<{iqKN$EbK8ccva5$7vAvVXA!EHk3f)G`g& z%5)yEt1>ny_VwBFU3^pvw$8IP>U}Fm_5iR@RTu0zmvMRk7RIxJ9h@+qs$4xvE-*tj zu;o?8)6Y(9%!GbIMQ*SoZW_k`SjcgKeIEBt6%{!+6u?4K0PJg5I;e+FsHny2g1weu zG#$V~X(rgy(@tC8sPbqkfQ5t**oNLul)cZ5FBH{a0xVTvB3l<;oCC{j|G8_q2JC@s z9Cd{hfI%xR^%wD-c302Zn;!2UiGL^jLc3}9hAE7*%McGRwQukp|V zF;1`n1r2B`)$n}iCq%iyW*uuV3&28-3+&q!#VWc{aSs3sNq(@MvZcBIg-@F#a67ob z+ErQC1HeLQCfIG88p|w7tNsMAkPrfES(>CAb#_8CQ4J=*eyUbxQ(qMp1CnPWu?GXt&_LOng)e_NDVmb$$8r6aWiVb-~g*tKrL9FrF2xYOf{LBe`@V%RUvC6@Y~#KiHBDgXtcJ6P}1# ztnQKE{_e8F02WF!!FFChR!Ym)CIMJT2!Wk+R;5f?QR}&=1`}YX)J(Do_~MVR{OD~x z{7JLJX5HoiYnTjGFv@`II3%pREc z^YcDYi`4}?BDT$B01Ks=VErC`vUbUD`w_rGLI~`tAVcMfv&$C&ShxbwU;^yG+4?f2 z?YC{P%&KeGeAa+1dBg)&awAGnQS>}Qd{hh8!8J_1CUfmk01H)h!TzYzavXqlOd@8< z3UsCfF>v7Y880V27bVE0KU;2X+&`*dG{bYQ+WzEA?ePD-$92eNFmA6#8BX*Pm zSV;1NeU#8UXPWWzOK>|NPb^j!>=?IghX5=@nPAr?+R2A?8*viALP7}a+gB;sSJpmU zC91&$*hQCpWY4{a<8My-jVFE4fQ^5}19owvD23^rqnXel-l!I=!Gu-nJAMxq09c4J z!2W)x>-~y5QAnwZIJ7js&@Hd((c2dp1Hpp(4>w z#twUg3dYxAA;$$aEB~@8;dI6k01HWeu%-b?IWLYG&KI><-5u61!>T`kh0;v0qc7c& zp4E5j4PYT51ompRWaWm)ah*jqm;kGuJV(~<)U{o(%(GwB6&kRgDg?m(y42WEd=$W% zOo^)nV4Ev*s?{e+6#V9)PvJrj0V z$Z>)7YkpQW`{!#H01HWeu&*gIdV$ZsbzreC^-nSGB-akRsi5yq01Htj*mvPpHs=;r zMgmw!2!VY%x|%Y2QNeU*FkFFXFah@duKuz<;RDaZGPl=D`K1B7Gps82r?tGVM=4&E z&m1T|ss-D=)(UlO?w33O3so6lLlWh2QEevxSQyU=wwh4`s{0534+1k}13NeE7v=8c zZUp^=ibOvdJ8b1L3s(ROIWDmEmKLbYGyC-hu#n^j8$xXw81bgnUZs`CP zN;ARUv8ry<{<1lK_yrO|U~4;MWP@9Hdd)dM=OQr@(T>kg;qU-B< zz}6odrRcsWzMJ@{7HqG>%hg)~Wn};ssxrZ@mw(LqbO^x0cvi4&{3lS7g=ZEB%#aOi z?}vtTGm}@Xp`TEZ8?48n!T9V2$Z>)Fswhxp(Gep6EF}5CKAIFjWlcD^P}E{|!BW=W z{{yg4nh93_18tLA8RQQ;EF^@$8aj7ZD#se&|ysLB8<*&r`IShxhh!gyA&V=V_$n-|wL7MLL$ z*uWtZX`fTm`anOSA~)FGPj=&%Y$3-5_EY|G)%=DN@trP6@`DXIvx%yn6q_b$vASRz zgzql{uuz%_c6a=3>+<>C2Lf0~2!Y-F`#BeLrdsQZYA^xz$;DN&`u+Qif@NA5HLa=v zo4$hw?D<)175h8qB3Rz27VP`HP<4C5rV9ZqM44cte(>-Ze!dtga)X^e^Aa8jAjbu^p4&my#F?MJ0$51$gZ;W@AJuYiZQNlY zPrQbw3wBb9%VPiwQ6|{NHX$}`Gd5=eSV#zg-FWe4w$Z{jg8?jDfoL!Rc6+y3vXn3N zTEjhc9dk%ev%{`G!UNW~+A77fNBh)`X{A3TrhVkFm?o|n3p)?b0m63Kfvw}|HX9*x71lIJQ#>zzz z&mu)Nm;igf=1SS7VdwBjuz&5sY8tS)xjbO+M6FcpyIE%_bci>q1>5Q0Fm+nc%V_`> zqD-){^3CU3;v*7aJS*5bokJ*D`pVe?Gi2Lghf(8bm!oYOK|i4)H(0~`^2Y!ca$I2L z>H{kJpw|Qd3rT*kU#qvL-#0vtFWNw!`03OI+r+B^U)F*s6YQcMr=^)rJ=0)^g@h2; zOW_iw-p7=1Q4J=*e$Q0MGA>MA3->hmlcKr??3=SZU>%OEQ0y2q;IsIs7Hl26RqBgv zojn08RAqvVlfOJ*h3|C1cvi5f(t*?llevopX2=HilW#-X?1_07=qFU<0c*D>6u?4` z3oIS-ujBNght#HPSKZQA)M9nPJ{d447Is)D%>;Yu>rv@q-_30SEF^@$ zCY7yM<~>ZoBLQ52XfOfxaYdSJ+|wRDu*`Pb>($VJ-F%e??2ER`71c+!uPHvN1v@r- zwR*{AgH8YzsxrWa#K~u<4u`>!0LHU|y*q6Rb+lfm#sV{B18Xp80)1?N5x%Si6^VW_ zjs$I*-^u{6kmCY7>)>A1k`pGz02Y$`U|U2_pf^`)!5@ zhV^`q0$?E_1U9;Re`U3X8$Dr1fGZFUCcw^UvRZblYxqG}=4{`4f52WSD?pO z*h4>|BGFF<*e)i0i~%gu}Hn9sH*dfn*B&fChz8ipr zC==}Ho|!fcKg<~cU?Cv{)??`mrAys?qeV5C0Q>f7rmTaq!XEBvm$F?oH9PG0r#xVd zmxd@hnryo!KB@&99=TRM%Ch=y0K2~G?*FUG1e+jteKf%xz`}S|uxWc+QGK!|_lFrm zjJSvROV_i&HuS~C0h6Jh5akBzQu6{nml|?hV8iQfQcc_VXcd5kBtO{uDPi=%(tpN@ zTCDC4+wAI@mjD(@Gr5z+d(A zsw~#mfZg|o2W;`e5Jh*N_4q3dZ&V9*sogsDlad4802ZPQu#!aimj3?U02aoxgAE!< zO(~uB6z(C!IKj4@)`|Y+!}t;+M7hEGn(sugkmCY-$2LKg;c0yjz(SHAZ12vu>Feu# zPKjEqF4%|FDiAD`W`dn|!$cbOx%3-=g@h2;318b}ANo-{0>Hu*hz1j2n>M0kqx5Gq zg=IFoJGGVu?48d%U?*jUC}Ivi^cEl0f*tj4omxL<)(8L#RdvCZ+=y}purQt#?CHt& zl-UjU4gxb|I}#)WnA3IB?&Agk6^VW_js(*t%dO!^u=FL-PcE>vW+te5b@&hrU?Is5 z_Lch)I(^@>e_^qZCw@A0!Ct+5D3ke~xbv8(| zp9jwK7u8?_?Di@RWD8?W>%uZEy{Z{%z#d)01C}yaq`2{`{zvgqE!ZL3Bh*>8r3C;M zsxrWaB*_o2KR*e;!gyA&^>VzZcJF?U6qq3!*wXO|`ohNH_^Jz3J;-+2n$(;i=n{(yZJ%>y?6R-j_rmeob#qgt>}9!IEO zG!4E1V4*4ltYnkCN^0k$02aoxgN^Z{+E$x)U0{Z6V80biqCa>fZh?M6MWUaK9X5E2 z3jcB#=YbdJ01lV3n_scGvsUHvbRMGNiZOsn5aWfCt4U-orikrr`h>vQ) zn)pPjYqs6B7{EeR2H22I^2S%3S^-!X&kA<1=LG7UQ@b|;Gh_ohIBXa_`HpKh=qFU< z20P}*NPK!BLoK`{8?ltgWG4DcsYa7uVF$fK~6}0b6Ti zfTH)J+YiM@wP0n7Bh~Ui-?0D|s_KG`7`gvp9OZ(JOoi1LS$ZdIePP z2w)+~1UtE4u+6;N?ScR-B!s{|jGCf6w*5;_Q4J=*%2kJD-}+nNGFKZr)zyG4JIDjJ zegFB2C3X6!fdg+;3-(yrdUdi@k^_K+C!u#n>d+hEo_)zq5X-UC=j@`E*5Q%b)#%RC}#vAVx> zEpV{k31Fc#6RhFdWj6c&J^dZPLP7{^Xghmlui<#zARE0v^#|0_>>$#)ymGr`_Jvqd_6e%wU>3ke~xrdygQ-BOjf zBfu4i1`}Y99oR2(wAy+PmKnF=%O9{;@_4{Xwgo84mKVJcAJu|wwmnL1@XS#HV4*4l zY{(XQi;tHE0azH%3ie0aCDbatK6q$>7$?}7cD?9n2P*KxFAydA$pD+Sc@;jL9&%h@ z)psYTCi(ol1YjY_4>texKKfzW0eo;OigxkB1=S4t-U3ke~x z2afeqNeL-w%rL}A<6(N*(%@OViEo!K^V^pcJPZ-s&00x83Hq8I}&6^457_-JHCK^ zLPesV46yf`+5Q7NEabSrHZ|?4TH&RC6~IE0AMA|abh@C+^v$9cs|&XH-1}|-7D_Y0 z4s6=q#w`Be0RRgLA+Wm|UCGW`@kA-A!30>n1P9r#{&vk^nNc6&>TAFryukx@Z>GPZ z$A+Q!P<`I07OeH@4eCL)@5lixM0LT=&3TAN0vOKWlZRDgujR1DmS%o(d`G z&;a@g6}iCi6mMb@pX1P01H(aU_-Xb+Z+s72uA`K&kFX@pp{g>z%m32G2&lIJj34g z_(IilbijT>lpCx`ty2gVa$I0H2U4oppauElgutETI>S!C|85U} zh0;v0Udi#&)slS%02UHLUgutdfdX;S)(92I$g9)(156_n!{gH;h zTRwGf*+>I6`#lfXpl!a2-OelUxhlL-E!eMBV$?%h*c=3~5Y+{{)W}{2U|~Ef*p3yG zsj!@?Jpe4khcF)^Ms%4SB#Q+wP{9q%8 z9HXD+EAgRIkS7+a3wCnavHJiPqD-&@9R8E`r_%7rFOU!dJM8Yt>`m|H;)h>s7ZdP^ z1`}Y%9i(K`$F&u3PhWPe)>s4f)i)lnq3eAW9Sl0^i;rr-4w?|7K00}1D*y{s8DK*+ zJM4D=3*%YAcJVi-npGZbB``y_9k#&_bGp}vcOd{4DiZx$Z>&9@^DaH zNgg*Cz(SHA?6&H2=;x>AMT=UjF4()b18Mrw`HYtzH`%0u){(^2rT{ZNcP~e z4HlvrOn^N$w6(0GV$5?`rnA?bKVTDARO9}%mhta1?8dD_9mGeqU@P2X)XTR%F#@nq zRTpf2Xc+!!R~XL<)+MzeRkADplfVqwz;+1iM^8KBirqRR9(eLSX-WZ=Wr% zR=q8Ng)0yZCcvJ%I$d_S*HwJwC;82>CYl{KKb!}w!%bhsvxKfv=n!vI3)Z|iMqT^S zM=JmeQ3hDaHo5cb3HUHL7|#lJ?@bS?#-SVd@f?T||4QPKK)>q@y3d%JOQ4?+CHl$O zVZRRwL$HwJ0(<1=0M(nDPD24KB>BPaf0IKOrtJ0*xE)--blvLtc_@H|(oC>TP5h+8 zcU0o%Ve9-P*a(3g=+r;EWNJoxXfRxXXfOeGp_`tp*{Wpxu4S*mF~%COUt)Q{?v?v0 z>MirhfDZ9SwO}REjq1Y4TX-aZs4m!|&YN$*kpRZCf-PzhLJhzA08iNv;{+R4wV1lK zyT(fBCq#*UGQgf%D>(`~EabSrS|$xr^@=|{8Nen^AnpV|Sd*!9=nEr;gGQr;Pt0R{e7>tD-77{{W%XihcTJ-te8)z_GfoL!R_R4^4nbnywco1FP z#NR{%c6Txl*z=aYic8LizXMp_s1|G&&yDKrwA!~}hlMBuY{)iwxMkN(02aoxg57a7 zmYNq+jQ>hPjJSum!LI~_8^BT&?Ed%j^#&89q z!35asj9#+6#wj~N-G!VnO*LR|?&Sd+pEgfn;6J0K_^1}_(bpT*3tHqR16Zi43)XI{ z@-l#h@vLB%FEyZ6r|-5Dm?7I4HtAg&Rk_IcC2Rmtk?1D_?4=n+w*f5VxWGO%ZlL;k zu5>Kyu;!PDJHZdOw2H5KAxiSC? zIWDku%cZLP2lkl&7Lxp6yZbk=9SzE9Q6^aVm&wvz!-vlXu#gY} zJN&IlwjE`8T~vb!u(mJi%66~0jbB}xGF-2@2JGQ%9v8Gxq=-l!Jr=;pEN z>^qky0$7MLz)H5ucQ>4Y?{vX|t_tOP8!802Z!5G?)OpQqn=TFJk;pxTg!%6I*D&J~_n$cI>Em z3RS^id~23Bss)=fD^^{_c4Q)eg(ws3HhJXBwnebR!gyA&^-oWwZe$O|cSRsZ+(QK0 zBcPbdP(9rX{e&pdPsR@G{4Bl%z(S4-Y?*&sRgveVJOB$xez1+IwXvQUR_n9Co#c9z zfcp1X0Dy(kOt9{4r`TLrv=6~TLI|vCiktG$3`b}2hf6z~;$PKn@aF1I67IIu*bIYw&n`3s(0kDwd2ixmPJL?~P!xKa;R(FRD zZL#AGfQ8abu$S7rk-k?9kirfN2_dkXgRGQeYh>eZwQvQZ!30=mt0J4(u|fEe(Gv%1 zwbFo9-R1!s_1sU9>F??U9pa5@!OqQ!RZpsOz6I>C5M_Y<{VGAbZ4T=JER1Ibd&(w@ zUimx*A2$Ut&K-7B;ApzZ_8j~YB1DOPGIrQqrO~4REabSr$|?q`8t?w_6Tm`}A8hx+ za{5|rgN_2XgKLMq|MkEr01Ks=U_GKUq!y31j{~rf5CWSkugG37-`op!1h@jxU;?at zqPc8%y3KA_=ALoS{(yb=hzD%aNI!+ij31lCN3~#+#>T0QH*Z@9V4BNk%-u>~Zmq^IutA>q>D1j}Gk#d709c4J!Co5hSQ=5#buEB}gb>)*t8Qj*_q#Jg zRD%hymi~2RUoRD>z&%avmf2df!)|@W1J)zgSD_wPxk!9e3$`dJPJPM0w+VoSstmBd zf9aY()B_(G593+E#ys9h1*IRZAuvNWuqF+s&@tC#$DyB4ksIuKPp_{47IIu*t=yed zl+o-Vu){)5B&2gkmm(kF(nS)IDjYM7qE z7~-dk;0i>839tpbGi8UZul9s{I$OHNR0H;6IS<%3=Y18f_1a$)AJu}jO^Z|SYV@Hq zfQ72MVC7pDbcG!j#&e+uhz(SM(He|c}c3b6H01M+;!TKfZ(a#EZj)r>(F=ErvsMCH4vHgFM^sBoA z@ntQD68&U=ZTH=F8tkx;;{yAoVv#C8zj+9Ng(N@N+^=_O>AIV*MJ-kr>_=O_FaQgs znPAU+>L4vMxpo}DLP7{^KzfAosI4hJG9Io#G?)PE@11S)qo-pDEOV+~_cj`^sbST* zKdohZdY5eA>EL7D6`}{%hIRFdeS;0=WUqdQ;|*XT$q%-pg|YQPUk5zHLZ0~P z)CC(pk_` zYQPq*=K*^o-$(Jr!?!tb;Eig*THcFOzv*hc6u?510amg@etr93a{vqDS;5||45O#U zIpE7$5F_p(?y#c=B-4+YOwEFRLX;bSp#ow{HjPAo_Quuz%__WNBEX~fy-`vEK@guupbo;6_pS{rv!4JN=|?RUk- z%%$NKSmqe7!arcwB=UfbqP-PmO+z1vk7~gV7!j}j)cW{*01H)h!M@M(+yG!uSkmCaT*vmqdINA?i)`BEI*aM$) z=+L`Y@jXk(6N}XaJ80-R{G%KYWrEe8lPg{4b>J<4g@h2;>?uQ(=L}2IL^YTItKWBr zO!@o}{y8$q_KbF#9X4|Z4_LFdUW(|Fk^%tB8`Xl9NaEGT-_8aDSco#fhU}0Z{U?C} zurQt#Y_kTT)S=@u@M}&GBkm#Yu>A_1Y4bJh@xw0=P0N`877{{W`(65;eSPo9 zTmTDKAR0`7jT(Ag=3(ovhGnKLTHRg)_C+cW*!(tLil&YhtHejOVE6QkSLf9nil2vt zs=8oJ>xAG}WMDiiSiO)}RFotsU0{Z6XV|5uT#>ia&7D_Y0Cg(4fE=!M416W81fwh@f zBYRLvKK>C2xB}5&0_^?S&aztm9shx4ZrD1rg9dEe5gxFH&K`=3?RrOvk7~i5@QYWE z-m!ca?66Q(7i@XjA$*kp#6dg?}-P8zTu&+>rXxY}LO z;9CH`@W&g~g56m)L4DhPECo9(L>XWuDe^t(|8xYfFrF3ce;p&JCKH2J3oMQeY}SPF z^x4oi_{Wij<(|`kSR14O+cY=CMwv__FLR1%Qzxh>)0W6GX1)FqxB^B|nXQsdm z*}&Q^9!6(%-2Mal2^EQcGIrRFwgs0I^YOScEf+8dt6uRRU6 zdGH79wL%`S=V!So@*5N`2M)YZEm$KuL9Hwe{|aCsstb01%Wu~JER1Ibn=>t%DtFu6_0x2nG3E!G?)N8 z^uP?+(JI#X_=Vb&j+tq8*k#2$V5gp#qp+(`;(HFfQ7zcT8xzzUdc4X9un=W{4M~w( z*(N^+urQt#tQS3>QdL!UgC8k~5%&-jF92s|(h@Z1Ft+3sEN6Q2l9AyFMN83EYqn0^4#| zRjbTVsrXJ8T!CmX0rrOH5Lsypg)!XI&!0AT(SSYlh6k+r(`O7xQfcD>~? z7uaDT#|2i=ZLvzWU}1gOVIj#6c0R3VeSd(tmB8)zbN-+XC{*41D%>?_j++O<3 zE)^eW3<)8ymE#60U$vcIDXPH)*dj-FS&!ZkcqC{Vw4|#B?8DDIVC_t1D+--nRexe+rb6a@Nwh}*kPeG6KsKMkhG!kyT@=O zfP@g(hr1$_S;KJiqQL~%YKt$}B%JH@7?yeS`*d>+*vOC?+#i1FUM{9 z;-gxyuRkQH$LdYNHx8hxF4)PYoAGbW!gyA&%DKy_YJEqK5tt#{FI`#7=g^8lZ}Gt- zP?6{-V~2Hh^HTs=$Z>%k^kAMUZP;ggl>n0bVDDJfwQj7o!xwEJPyBT1?y$=m=(ho| z5M_c@6cYvU?Cv{Hmq53_PO?zc!q^55Dg~4u6?x2=7>iI{;OGG+Pj+uY|a`U zuope&C^j!2ITJYWMzvrK`X#FGNp94D9TuXxU=K~Y-vf477|#keSK&qVGLxkW%#aQ2 ziNpQrKBtZGVQ^59=qCfLUAGkcD>9Jd0_*T?ma5UJ5zAnQg(N>%N&Al0vwzg^6t!4g zu(1VH695aPnP8Vr|7bn!+15P(77{{WUB4G+FX~xR0!IS40?}Xs?2Y5GHc3Nn;vXuw z-ln#N2JGu-9Cg-;*Dy--cCtWHy-6-31A`004v!k?;Kuv1;E01R$Ds0A;gGH2hXsFeEeyPsq^K~PlyuzWPmMh-{U&$u#n>d8`H#96*{q(6M%&z zKiDOUqiO%=wGN3|tS;E~=Q8yGER<$~%{`DP4a$B}9l%0D2yD?0^MTf#=Ij>LU;=FJ Mw;r|6Zq@9>z<^*VF5-~H$PxL)UdUGMXBb!O(wnNfnj|NV{{m8jD^V5q5+&OJ%n zMss`}-Moy42e^3oo10BE*6ri(;^pVEh_sQlPh1zO0qq zY~D#HSSPdARvFxcWLe`MY_0wOmncDhjZlHnjV{dU+K`M?gJ& z-PXE#MAFyMYpzR6gGon3Zz~s$@A)q__>Til(?C~Wx7pv=f9K2B+h>V`hqs?!%Qu_r z6k3-ozhUw(=sC09c&OJ=*GRX`zu;mYkN?)`;_MLM=b;*5bi&0pI7o>J`445 zarE_a^P216>*(*&viq79L%J_)VAJtmVXb9VU!ZVv-KM&_e+#Q-nxA`0{BY&*U8es6 ziNV1yA<$X3qi);30UvJV{IbA271-TsfK>Ht>BMftB6^st83Zo2V5ZA5DW96c7g z{Edwr`BKuYea1;x;vJiL{Z&Y>8n7UJv|1jbbE}$nQjPRruOOv&_4fckO4g(x6EZvM?2?om5v6{<^_;KuQLYy z<+m|;afeT938b&wyUI$2w|ost)K&}`phEhh3k%X0f$|n3iu>_Ss*wt2hbTKod~Od& z$(mH8MY2wP8#@3}ayTv0QG(wV9iLqguuqQ;>75>)}$g;$hI#vS_eqU;j~E4G#M?NBr80~K0P|54lnwOdOSR_5IRZLV@7Iopw0?F zO2(LwmL%6I{P|;W6F^D^*^!oP6pE~y9O}qtp_)k34%&AGq-0?#QvJfwlIA`My#Og0 z;6l0}qHg|>jx+Q5w3a|Rq9$8fa=LjuEOAqd$A6I~3}!}ZcRNfTHC)6$sYYsN7p&|x zd(<63O4g(x4Lm9PZu)ozASH*>A{`s`!@||>?i}`o(IK5zGDcMIedaRgBw3FcX|IYl z>45Y@m;ZH=3F)_Nt-?*;t=0lkGRTfp@Z7^<(l+f>*ctUk})QvS);THm$pgs2Bc(=9cjs}ufl*g=j41As)=;}^GTfmDOs3` zv@9oCQrF$40+5mcE~FPr+vS_wJ2Ht+YYC)9+uuslmi9`7B`QPL4OSt&KAIV6X?C>y z_4haPc_-CK1%e>uosu=D04Z6Mf;2E!rtNrUCLkq;(;_Xo-%xn>&y&aO)1yQBbi@eJ zQSWw9&`Gi$Gg6bs_iw;XO2(Lwj-L2OVeh@%0FaVFcBGq6))V&{(6bqzg=!+5{inGV zASDY^kp^A2x148d@BomK0WPGaWiRq>46GW-r?mvqWv_fBM|R4l!xCFn&K{yd`f4IG zQh{ZHymjV*0^Z60A)Otd9J2M)X+TQWq#zZXkQJ29+zUv_;j~Co&6@~Iv*ftJkSXG? zAilb9+GU(*f6A!G&`C1MjI`q6t0#bzj4>gdCHSK#tet%jkdi@mq!ugti+cM>ITNXf!fq@vHCEt~c%##i@bfD7pxErp_61iW~8oNE*}S^WQ+;vDT5k?zjSQ`ASHwBNV`q_ zAsQUp*^tjdHFwgD=Z1IyQnD}=X-x20%d0)dY=E7V3~(V${COnr?(kJt__UTlx@S)v z>EP1j?y$sfdCkpLNRwQckzPsIAvZo#xS4lSjdc4qf8~_5n->96vL*#-V79EW&)^Y& zlpIcr^kJ4*xc^xgZuDe|aVI@d6(KqoSF;T|NhX<*Ztc+34v>;DCZunSek&F~dhH2F z$sjw@e#$Cgk3IhQs)CFY3)Mv0{^y}_fRs#9ks293wR~CgXeuBj16)XbyL8Jvcs8dA zpVkscpU!G4ZRcm&4X7RJ{_Zc*94}_1FN0#``?kF3%R8w?>VLyusXM%I79b^SQjuoK z&e&Pj08(-|EmC3b5aB_6u`&Df=yuY@mC>S%rtj>alVm++q#k?Dy#}OYj0tJHPL0Cr zbxYo#$p)d8@?yF<-X_XBJu2(VKdNRb5V$LA z_MB|h;a}CBZ}yMJs+vwG@A3Qri-TFxLcMZigs}CA*!dhYq?2khC_*&PD>kdgzZw4V zX=Q~oWTraigvlfz12bi^I_1`D#cXNq)PDaeZuxxO0V}d&4V-KxUOU4il-FW4wc2kR zH^0-r(u$<2W62qJ>=4SsAUGyhcVS>wR@s57^d6j!x^J*{ww%&nPlJ|4c z7s4{@-Jc;;fn6KM0#-0PRxUEU-<5w<4feRFm-6hupDjE5TdxW%RMiCAG`eO3fQ9k2 zU{lW?6At(2Rf}VWbYL$>FBIv`X|fdh2^E>a7LRuN0AL}<1lH*GbH!<&<@W$AB-z0h z8(t7qT8&QRwOCEC5Bt>V0AQgs6>Ny>Fv+OLYbpRNB)Gsvmwp>!=N1;ttHA_VeLpkl z!kll_u*~HFW+D~X(#?yj5 zw{E7emXCZX#|-JfURy60$zJ9?hJHdtX0R!%GIj%4$T5Mv-0qQLiN~W=02Y$$V7s*+ zD2_BU*u`tHnqaLHtu^#^@fOSq?-59_^RSMX^OxZ`hOV6rH_%V0$PBhu!@FSs7II8r+jM=b@G+=!0Kh_$9jt3&GqG+=c{H!Z zYJxQoq|^nlP?`$1aR&p*jIo!)04yZ9z;>#(x0qjbdN;2I6JTeH)=M^x>+}JZS+*g= zQnkarO=AHY7my?`$_|_gQF#JOR1LOo-+9W=fzR^+EJQWI-snBB7{J1KTChP+y9w>--2`A5}YXUXO()BSUj04!A11Y4{14L1M_<7vS< zc(oPw2@Fr+m?7N`JJ{DxWGLPE0{RIRnZdrTE&dEUEaaHL>U_Jcu(fZy1HeL(9qe1D zo1)t9+~)FHtR`5k56(`o!$N5)*ulyvl2em(@I@CSxWL|69Wrc^&X-VL4JN?a4_zyL zc6WIzSf)|EX;Kx~)It`p{V#2kKbsKr{}EM#b?xS^T>Nw7V*m?PHNl#t2Ym*xFrF5y zi$NEmr_OjO$KvR~Hm8TttonZf>SKKclNg&Y%D;nq^c$6a+>16WA1gY{bV zO(aaJ3gNX_O|ZjiBF_R?C`|>s$xc@~wbP`Tu){)v3#{*<5xFzGr=;*|Fab7ZMTK&&00^T-rnZ>0W4IdfE8rQCVeWw9TvvZ zf*oJdNLc3XlFl(hIvLb0BfQ8ajus1JVv-}>Cln!7a!3DO!Pj0@}Dxfj11`}X=Z`7B* zzq#WuEOX@TI&u}*J2yGN-so|>HvcGqm71C909dH130B$LO#(YCjHd;A=<_<^y{2hx zIA%x(_O_LaXqmg{9P|?^GK1X^{H+0ig&Y&ud);m-T;ACq1h9}~2ixUh4{=z!yE(7L zYJzR~ZI3U2h0;{8-DZVY);nS>0CN>7lIAty%zJp(+Jz;4#_P4XfG$SQt+WwyT|$uzRP3 z-5fKd1M9MWqG;=+TsP<^RAdHQ=hYkhS|sF{z$WgxqNwFKtpvbAk{#@wuVci1r?!0L zwOCEC_Cw=y04$WIf(^OqEbUisacckz2`;c5E9VUD&}dOAuLcuf4U`R}S9i}bgk=^Q zpB=8+VZ)xWfE{;jyL@7=9?kei)nISN&sR>UwJ;07LRAV_!73Q;eIxI~2e|k{ztB$tH}Sq3*>k8f*1f(z^j{W19|lM=S_YA^vdp?8jC;>I&m zV3|G2c8ySh-Sv(ItX<`H`HU^^@LmGes2Z%@Z4af^W3zAo3sDN#zzmuA=jd(#7RJ+p zeH^qwIQ;8-KaR!Gf%P3QLDaNrz5@CQ6`8?4UUL5tfQ1|r*b|{w6n9^Kjt8)iWCy$L zW)E>_*^o+Ji`4|1TbTL-z(Q#%*j=wDN!qQs`5JauNN|BQuJtK*?1L%zA_0y-G?)Nu zP#~1hpr z*q%GPN_Tio$cAN(xneg;1-4{$E#|wml3v8ir$61{%s;9Idr!w(8N9dtLjVg^DPRQ| zvKB46_Jkc4#?yjT#K?pJkY`(${3ppmRqeF@m z{ubwM16WA1gY8x@MLadvdK|~;`1|KX6YQ<|E3@OfQ1AX*fB1f z^R^$HhxZb|5r_s8U<<-+q$g@_YQr)OTueu+z=V@X~E9Y8!ue;d>q~n0x?FgpPp|Lwcl2L48TH^=qF`|4f5VU z5Wqr?3GABEGm7zpW;y^^NOFK(DHgl!4PL=4PYV11a`}{ zBE_@yQKtbcB-z1UKIbNW=VO0_*J3qy*q~W`qhW`I(p0dk3XLV9jcg?7_qrmaYv%?Ex$#xWH<+J(zc3 z@#kK=8ccw#N@ybe(EiUASf;$J%v!a>D)w-Ios-`1E&nKhtz2-n0Kh_3D%faK0e$TuVEp_1h#*`CB-Kl=b-== zlI&n@!^%VoyWrqafFdt`ri`4`hQ2(t9fQ8aju!7HhC65gaq5&)F^?Usg0Y z`#S)@LXsV9H;ZZFRV_1j@LH@U*fWjBp8~K@nhJJJ*j9;t&k?==77|=w18!vG{m#qm z&#S=%*dAIX67MgK@LqyM$(?a3uo0&@z)l^KFabKm8U?W4=h~D2Scp=<3ese;(Q%yt zER3fGyVGN&P*JDV9gZ2&fwj{26`eX4c?5q|+ibj4*i5EGgzVWQV@WJ923}t!B-Uq z&2lFISV*#ioiB9|m(7@rUv`2#u~<#8y?5Vi2w)*f1^d4Av*l0&@BIK45?o-LJLKej zNh&wv)nEdwllM7E)xZatpw4s8rSU4Tr*E-o1g;wpo|6Vxs>hl7kek3fDW-n)nFr> z9F?Dpuj&F=h*H5Gls&(<>Jxy4@w8xW^E<(6QV>vDPUJN_W1~4A;$!E(YA|<6FZc402Y$$V9g!xi0ai}Q^;$vnmcT) zo(aCK1*NHABkpNgYPEYI1+b9d0(;XG0l%|5+y|2PD`HsZ`01F8&u#L}k$=7Z$un(^W6JYmePL(c{t`fj9t)FbS zRe?S5ods-IyY2G)Lj{ifqiV2KMb64?sWZj_Sg5KAwpQ`FYXBC;(}Fb}RU$N-qrj*4 zK#XyR9UT%civIMbH}n&t%wTnuwqsz2g&Y&unWJtg7IiSp2C$H12fKaeQ1PPI<@g5= z^2A~_!PfXbJ_KMPN(JlWyj4=RrV(Be9QjDF;Q~9q_qJSr=UR!-U^oKNU;=E9qa&ol zjqBj;g=Q5?>{MWjf@(A0t+l;+o7~FFY!ZNFjjF*40-cp{aeY4nScqzZ)hi!U0bpS~ zE!d@2x9l?B5DyiJeo`(8%CzJ404(H~z)o9Xp01Kt5VAprwE!k|n#0Yj+NN|CTJ>4oV-#d9NfQ2Iv z4JN>bwEZCwx~H4KGOwK+K3N5}d;<&E(4}$mfmK4O+7)~pYH}!RA9fwuz+=VzeO%z6ot=KVU4Q6#%Ih`8oHYA z1h5dLfc@`9SC&p(5rBp9v|!s9b`@H8i+;$lIJzBHcz&|Tc!D*8g^J8z1u0{009eQ| zf$iawuXvg>wHfTNkYop2qSZybG`Tj{>G-=?O|S`F+YAA)P?`!hwP$nb(+fXG09Z(H zft~NXJg??yu{(f;BM=QHz{ZY`lg_VMX|kVhds2H1#C=tjNHBRwg&v8 zYOtZ}-IO-5A>RNjRMiA4kVIqySQt+WcC+_J;WVdp_=*x@#9v9gB>0pVB@%0O=m-6T zC^OjQ?JU;94huOZu)QB0SD4zr?gn5X$qqJbkG0ry!pMdkr-NySy*kz@7j{@EtpQeV zy`-kEi=~669+;{Edp4Z~ti`Zsxw7M` zG0-8_s2Xg?ZXU|eL!M~>7NVM9mn>`248X#8TCmF+EfuB;UN7L7A>9spBx9v$jE7tY z`Uw@8!49aqjq)4FWIvg}W<69Y>b0r#0kBY!9c)7@p*XjJIex4MdE#HE<_?=L^nV9n zAxZ^%MSGBBYIE<802UHlU>{XQo1YmuaSg8q6JTA!%%nZLd|M3XbijtdX)3UfPOyNr zvx$T;_4$2Nrc76X{c)ND z?E57XhCzo|qX71$ZuSBI3sFt5NFKs1;D+u*l@)bG>VU$D$qUAxRsfsMJ$0yg+= zwA?D?fhqr}8ti*tcV(LW`Y!+$s#3rP9+c_aO2HerVLUC^$&KdK)|i}4{0kSG3} zXo9UdWO*6DLX-+tw*Q6Yj^eZUB}7PYfeouP$(Mgj*$X=Y9D!&s0oJ4b8HvOEUHJH^ zD*4C1VAF21fStHFMqdBBT>)@ljjF-!@|maXJ2T4~z(Q0LZ1R4=Sh$9T@w8wUP2VJ3 z^+1T<8i5#b4)K!UkmWqlx1&}v=qE&pep0~NM?Sz$x**2{)<`>Daj9ytVMYn156aHY#$ivM}X_8-RtXnqXayS+oJL zFrF5ysG);!!RB#eIc7+=!*v!{GoH#?ykWI{(z-QpDWm9E+m^J8*g%(Vr798$dsyBGFF@*jFzM{{UFX zF@Zh3BVCbasCxszLXsV1Yn^w6>QnOH(nHuzp6LBzK=(o(#*}Tk7JV0{iPd3)rVGBIV`BQt(~^)~Fh+!)bTr zk{rbh01Ht~uxFiua{w%irv>Z(#YPy>d8&|OadcqAHU^0d?6;UhKcONsSo0Q7&Hz}* zF@d#Sl&&bKXW10MLXsWqdSMfB(7nqxycVkowzp^0B>)ShsbH7CKPmBxZM7M|>Q)hK zxWKNeb2Hzw`L!R=U^oKNU;?bQ_iE{iuz~il%(?G}%vOPo{lNmZd7Vgk?1*dl7A|X4 z4OZCIQ`!1=fG>cBs3usG#=oopER3fG+vMwcVPe{mAsmaN1DiZFN;J?i1n+)>ibOvt zJM8wjx48foa!g>e%l9gl8gKstU?Is4woAb{@!$(RZ}VELCRm$2LsI}Ol%|4hrQb_Z za&eU-fQ1AXSaHvxdH07^RRCBx0?}XsY)t0_>64^RcmsFr`1+12u<5~dnD5r=>JllR z@wm|v=n!jE4Yun`4`pwUsHp%JqMBegw|9~OSQt+WR`_b7(7dv>7sm|gz{dUw5xp3C zObY#kibOvtV6EGij|H%hV*-0AD^2l9`AY&|A;}IlpogjWQbBwKuf=MDoq4^Z2Y`jr zRIpu!ca~-}-(dq_A;ATJI=5IVP}M-tAIYt_vCoU?Is4_Fd*Qv1IE-e8L3eiMK>F!Ty-A z|095fC>3nud8wAQpA_NqVIjcf@H*c?&`l(@}-|6`d&`*dmgAFilgwNK3923|^?#T-KoP+5A7Lx2> zS9Y2r_RYxQIvs!ib!vk3O)xzQV4*Y>Y^R7U%djq28^R6?2`;d$(r@S0j@+lmtHA`= zC3hc6@|L}S3Y$=AMT(OO?C&HNuuZpZmTT{{$A8kSQ8ie3k%uz;_vtj$4de@ z0?}Xs?A^eplD!S;ZG>fZO9*mSf!(@~1?;yAo8-${ow>z7ss@`L;i0@bxN$0gg{qoh z{Vv5ISQt+WHg{O8aNg7NcoROv7{OW}-YOcs;$?l<03b^AlX4B~CRsiYE(svV1h&Vc zI7QJGkIeuUlI&nV?Vc@8K0Ty}<8&~AO-zv)zzz$gsbJ@sUa;JmQ|lUlg#;Ja*5Z-F zPG?Yl%omP8G?)PE->-x8Tg7u3Ec3!72NxCCjH4`I1&=n#um9ZNjDJ)O*6gf@^5n6( zCjl%})daiDYQz=TVPQNi*yK=OVW4C$e$oXoMzH#+Yek_MLtFtYM2UVOQR1Nl% zg}d_F$KQBK08ve_Mz#0g-C8i77OYF|a^d@fqkT9Q_xBv)HSDmtVWJe1tG@s&R3!RI z0lT5Z&LKI6s$SV*#iy|813_?_0xEMAM%yoT-cHG2<$h0;{8hvv7G zd|TXb5P*dQ7udlOyYt((zxtL}g9)&Qj^s10`Ojv!ZHr`?mF~%KMp5ZL|DLRhd znuRDc*akMECIVQ(N3Gb0pF=~QSga=4myZXw1+WmM zf{h8@Yk48)&T{|@2`;b?Ti?&Em45p?fQ2Iv4JN=EH9ID;U3vh2_Goy?kH268udsl9 zAG}F^Te~;@ChML6qnxWrx+jVip5nA;$!E%F`6ZLOa1p*kK{b4%Rk%w%G9F;cmPZ zs|j}bw-IXqER?2#E!!GwnX0>L1%QPF7uZwo8_czX2jLCJa0H^k1lR>To=9xpeRhIn zuB~-*o@$5Peuo9DQNzvh!A+jyy#%aLHCREQhtkD4y$67Ws3zFEFV^e94h!RH!PdPW zD70Ht8^00^F-EZE)@wzdpU8&81^`i_pA@jtBB!MQ7II8rb878TWRyH`1h9}~2mAE$ ze6eJhi5th6WV(jk;%{38V4<`ISeIPOvMybl16W9KfgPPNIX|gfiBEokBM=QH!LDm2 z9on=M-zE4w{fL_iZ017_uwN~@;9Iz?Q2@L9$9z)&3sFt5DT%r>04$8B1zYkmPI${? z4!-Du7$ewsrHLZl6=MejScnq+q<}Sj;8cHon%SfgsNi@$j&vwl6B2w)+q33f&OkV*gx z<7vTq-X9>G(0P?F$KvQ-bTz&;T{NM+VhMnSibOvtV9R^#d;>cyjnU?;dH{-?eoffQ1AX*jg{N&0CzEh>tjj zBM=QHzz#A!Dj78UH@=yAuzak$3haw&7O*jGHp>O=Le4{nSfgsNJ*z#G1`WTs0$7M@ zf=zO-N(8Vlo)&D^&QMSC%H0*84+{w{ zuus}-%ypO%jt|m+BM=QHz$PD(NGn#P;iHO<`?dE_fere}0#@*Tv)tJvDgZjf8dZaB zGT%eF-aqs#fQ2Xp?0@$Xbb7O43xI|3v|t~f3KxF7ocfVthIBh@t=8_MS>ICdUIM5{ z^pgTMrq>z#HE+l@dj>4vV*4(o zkL5ruuXC`&LV^pd-nZ4cm)P#?l;|e~?7+qTwP1&Z923|vlcN+NH>LQ&0VLVM*1s`QytLv7eo_v3VzHWF zE9cF{-J085 z_ECY&4rc*taW_JK;`b^1!Yyl54ffeTc=HH>5IDJU;qmVF0i*2F3KA-Z{-YL4JN>@yJsY| zSt^#nr*c`fQ2MG*geC? zi8FMMC-7RVCfNAl_nrdSx~mBURIp|zW=c-Au*P5Wh6ESb!=3E&Gn2kqLWAK5M1u*i zcYfMP`?jjWAB1PXe%z zV*)!`=YV3?j{W$!O-QnXjj3)e{uy+y1IOuLdeK#0ly?HaLTM`4YegZJubcP9-#CB- z7uY2S8VD=&X5y1y;0Q#639vbT+DTt8NY004J_?TZQ-NKxp9O5ps&KjOo0H-EqiV1h zU;8Li--&JmSg5KAcE-DN+5i^D(}Inxy-PSc{uMsz17eI|8-3X%Qs|DyO9F@z{iJ~H zwZe4>fQ1|r*o%MS6{S9_@j)7pWCxq}VWik^e1|6-r-KP>)TXsN04$WIf?YfDlElRB z5Pom~2`;eRrghJ2QG0J~*kR!aM1u*iKZlQyhWGxCU(C|?i}6>1P0C;an`ssy&vf#{ zPr6v6YOpJ%3zQ2BYuW->h*H1??vxoPYM%$NFrF4{?fyx^&s|;d25yKkg6(+bn5eF~ zb0qW=qC`I_V6}TYH3qPdV*)#^Rj8u+oYr)>B!DD4*yc_%#q0G(;XCS(Cl;%DNszoO zv^{`@C>3m<={GGqWDI``*RYV_0;}DnwS`X41zEfrOn`Oz@JC{|=6(hIyL4zDy-)=< zCyxcJ^hdZnX23@U|EL=5(P$s#d|9)O02Zohf{k|9UkqSjJT2I$K0(42t1s5)m?7OY zto1}Uk<*g#bD^J5kr}M4V@m;mg&Y&ukjmAH#!o`c0W2ih!T$I&ODv9f?#^qmnqUo^ z9t;MsP?`$1epoxn9@90Q0W2iAz+Sy|FK?J_t3kXPOn}wB|4DLTV;6j@vUqDufC_AJ z5ewKW@^E=S+nTq~A=aoGtm_D0WtY@x0ssq93RuBT*_=w*MgR-rX~9LOjGz&){8ccvK+q*?lsUM6_ ze%WOhyGRAL>Iw_kEh*vhnzkSOphK)tHQ2K4zRKg%9(Dn+5Y+^Gan&(=7#xhJ1zW4) zlJNS60V6qPNVmgw%?%UTReSpYSg1(!lX6M0u4(vj01G)LuoqiJC_0#h909P9WC#0Y zsg3ykqILg2s}RfCP)=cg=twXz+6g{UUjYFn*I zu*1T5TCnp*4-=M;nKhqdhIC*pd%BCNvgQ~;KcONsSW(0VD*y{QCa|aE>l9LXZ&LsZ zNp`STTDXd%^atQCkU*XltnjNv0qn34rGoYT7G{|+_&dH23kfc;jZR+8TXsA(kXM5V zux887OI~S*wt{ooZq()_DzM3qSit(~hs#5hIsYF~HCV&3e#!%)=|2H1RHc9oOqJ@0W2ih!DhU$6yLVmi;rrAJh52K9oC`W%3lB$qExWWzK@VBybXU;=EH@wKIWBgW&Ek91(rQWeif`@-d8zq-VN^}WMcqH3^fD}0sv zx;8!sU?Hjr_K@u~{MjQIPYbr{*jV9&gH{hYW=OZg-n$tgy6X4oA@ma}GJ}nJa3CGP zLXHV+)UEZ3b!XjL0$510gY}R06AN=|59YO4O|WTmj9vp+C`|>Mto6<^^vCUS02UHl zU~S(%%5&);4CmEg0_?KlRLL#Ho=jL~Wq0dkDzLXcuz;=kwNbvdAx3OExWgXJ=`PCfv26+cgeWuE zH~LN!04(H~z`iJ0tFVhRD+aKTWCv^b*j;S=sW^?}bTGZ>YP4eLG5`yusbB}D|Fm3n zyM8?Y3kfc;=5x2_wROzRYvad z)~Fin$OnGP9YbC5k^rKbVE;_JauLA7cv`UE?kp6JPHu(2BnB}?u+wtqigpaLz61S) zC^OjV(W3JJwpTBrpG;sY?u06KZEkiRz(SH8tnpisxcb_zZ*V#wPb^k*hppwd&l12w zlnS=h-2_YXj0H^rEF`$VPL55Xm5GAC?(=^~GPX>qF`> z->sG1I9%Sse55u1s2c32cz@-4%X=SShlQ$|V25>lIvl{lcv`UY;^qny4t0FbF+;jb zg4tQYB7;L$tf8M!k?1GoU4j6!H2jSN$T5MnJ{_vCo^kaDfQ2MG*wqKU#Jl@m#qWed zo)zrP3+>|pEJUebv&I-o>Uh-0ZyZ2^3+(vioAa$kzM93W!35Z(g~^iJuPqzFIrSQq zxk9zWrbe)UHTkhoF6lA$1plZS?9K)Ym0QxPB>)zxQo#QANmsU!kr2Sbcv`S|Dcgjh zX&o+e%#aRjo$XGdkIOoSLO-D*GuY>EM!kX^7II8r7c^g^Fh6}D0>DC&9qgjVQ^Yrx zX$A9ItmY2u*?Kkp5+anQf~{-PRxA&q_VsGt@~D;9UOxFA}s)g$m~$jQq$naNE5^vpNkz1N>}dNPI6 z^Iuo?l)a9-8y>D-)Q*r%!Lun zJ4quZ*Av?2#wHKrM)8riIgaL!59YdZ2Wa2?CHcwJYK`p~D`XmlEN+q9g_GGkSkdgQVY8@GF4M#*;+9A?GOgTYV#dLs%U;7AM;ME3RzLg` zik-QGxZIv%!=#zPo#O0@NnegP2KJ_;v_arK?g;LXo`71VR4iI0U80dKR=oKqVR(U^ zLr_RWRmR(FPP;;;Opy1)BE>@_?Fot#KE~d(q55#gyog8H2BcjjHuOr%OH(D{)$Zx+ zqb8>FPi5+36P9}nH@12`Dx8k3WTz!W%tWudupCTD3H3-tXGlcm=miWD_FNUE?%h-> zsGZjqHO4q$x7zh1oRFSsn&UYF$iSp@R<(oeb=%gR9O-Xt-0}R96dSE$J(bfX*e*Vh z%xYOntyN_nd&k;{Yh53Y0kDu@0=uU5@Z|ceQA+?U zyus|iW?PyDlT4PbvNwx$2VeruO53CJi$>sF&Cux~xzsE^L5ivq9^ zC4o&oK|K4tvKhd_^ORsiKX>LA_h~I+SdI$p8NZ8yQ9mzffqO!u**y&(=l}oDz--5u zj{q#>=)jhg*y{M-4|ok=A!!}#*>gjM;a&ZCtd_L|tBCx=2f#u#8En<8lzvdakgj8UgYB~fTdeo@lp3q1Swl;ca zGk}F09oVH3TODt|WGH}zq;;_M1V^|ac+YlL%UXivQg5Nnn$Ui0S@8(*P_yPYHIz!7P4P`xomOCZq!U(59DgQorjz!abpp9_+E) zR~rE=5_vhonNw#n!t|! zZ;HNm!9oNJtt7CVB4VDdAp^j|^ORttkAKJ4pFc2zVL~dfnR1@+#kGdHa8GEY2Yb4& zxDmiYjt*=|El2m@*5Ww;7LwM%4yoBDm}H+6&1zXoupfj?I|yK*+5&82m}r@oXCQ!u z1S8m$PW+u6sV`U^*bMBJRr|#wijMb#HEsW0aoPa()i?I^U)baa>5@x_8rHIpn!s{? zPtnWMQ|G}K7FtPQlaCV3PEGy*7M`aBtFAiAkEy&jj$uM7uo1U;!q&UQW4I?Y(u37( zS&<81Ax8(+uC%NA!H?%}16W8}2kSfQfG0D@`hjfdzQ5XJFsY75P*d! z8SMCBdqjyfzR&0X+L#>x2ZlG89oP))&e{sGlfwi22>p`W|9b=2`n+EB zU)Z|MX_EIkUVRJ~vKlpkosgfRzo3oY2Vfye278Ebt$r~dz{2yCU_Vv%7R;a8k;O0} z71+e{qlJ@?`VWVDLZjI|Nxu@De{1o(02Xp|U@vQ*R__=4{}aGM(mL2XK3fH2-oLD5 zwX7xBBkS(A09dFdgDnx)i&_?V!~j@GFoAVfPUnkw*;T9#YzDT!I!}D0>0cqRW~zLu3G`?_jH3~#`tSX*+)%a+iX+xpNV7t17M+*1eSA{s0IO0azwgb1cw zcWGvrkP7UsTpwX_h4TuyCp6N7tqc;$0W9R`z}n1culBegj0Lcev<@~Ws6mjQ=d*>? zvX)@oBCE>)EL4-h+67(}>6_pvNs9RpyYl>|2V5YZl$1zu(bnTL;+aH(Se=7yI>j5lOlff2v`iL%`>1qM6kYEBEaI=_S;NOA28^RmR4r~TCA|g+`{Il!{ F{{x>w6mI|k diff --git a/000_image_stack_ram_based_reward/logs/PPO_16/events.out.tfevents.1680183136.DESKTOP-9E17TO7.30948.3 b/000_image_stack_ram_based_reward/logs/PPO_16/events.out.tfevents.1680183136.DESKTOP-9E17TO7.30948.3 deleted file mode 100644 index f3578541e2d19f9872e8c9fab267f014cc6b59dc..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 53172 zcma*wd0b52{|E4qkSt{vWv!G*gg!J|Gb4nMeND)kB$b`06w;m+NrYDWPRnF0*-0d_ zhwRxY%g=9k%=f(R-0kz{=W$;5ea`znJMP@MGc!Q&_rG6J1Gdzy)zskjw7R7Ztr|@A zcAM>K-Otb6)2D9_7i;}4KJK0i=X+0`@8&(-dZF*Ud2ZfItQUFD_Hp;NcK`oTt}|wP zxV!%SKcc;@zIOh1+&vp3KiBm+7N$O~VUT`jWBpe8O}yuOc+B_p>E`a`>f!F`I?vtB zvzfrZi{kU=riQ$e-tLS3B?a45;y#^i+y1LLe2}6g)NG`0ps(jMd!Bo@8D0yU36$*= z#d}=eLZP!a=9m8e(hb))Wtn2-I)#z1Z#3`Z|E8$itZJK96%JD*Yf`2tcp?8aQh%!X zzZESU`b1Ed9NtpDxxRtV|DU98ZeCvA^B23$^=LNm#w+2JW+`^;)BBs6<}usLb%wXw zG@se?J)89^pC}&rU{*$_fAvm2+V2SUjPzUR8xl!xH_w^w&BoZS5LbKW#^*7)(-(&W)C9X5Q-KNj} z|33-!0bDnPpGewfag9%F{oFi!-T%ghY^o=p@_j=!EHUxU8P7gDl-?o^MI7BNkw{1-aY2$LO@Cmr$t&{mL)pl?S7AadVd>=NDCBkVu!W& zM?)vcddx`24QXEtNXZxz(q98~3;Jf2JOiX;kOS$KTDkLfj-A72q1s3dF5W5!q-0?# z()dJ6hc8P_*8);9z=d?chp|GZsx8a;w3a}6t;Ta%jg>E|V2MwyT<)ro##k^T6{M_G ztR52J%sZ(;DoBY|EpIK02c%?83R3^m@|aVFZviPeoEE8lY9~>GZ+~I!V@JM*4Qa;zB@5#+Z<{NvK(1lkA=dNXZ~O(uwDa^WL>;JeJQwwUHKhx?cvQ zWML}O`m2vPbexpm1CWvdE~KVc8rvH*40q?#S_0|#amQqdKOXmkB`!JGzf6rZp$9Y4 z8Ri=mo?U)M@lI-xULL$rwfw653?LTlV_1Pmd01 z-s7+0hcl$pp_61iW~3%b`)>nMGRB1TT49X>zoXkH0#Y)_j?~}ou5d-x4j(=X)kZpf zzN04~B@0uLPFLM?7?!;~1(1>fE~GVo2MeV(4Oa7MErIlL-!HPBAt8-ni9y}V?yHd| z3z?CQ+PO~QIAbjS1+yhJNVDdIsy2Q9wHuIhoS}Z8AE`Qn_kdi@mq*IEI=B+g9E8??I zZKN9&T}=QfS(u8ne~78{{jkXPfRqeyAssr=NVw0bM2}Bv38ee_&X?&l-K~Np=07NT zphlYN$c!|qJW^4s|L!ZilNzLE1J|owj(&Lwkdig2NF(I?^j1j#DLI@L>8E`oMW^$u zlG&$6hqO;lqWHjApQq4CvK}+iJxkxr0HkD$3F(ktf`Xhzu2z7Q46-BjT2h)jU21_l zDH&J4I{&*+ZKM^J*HQo}nWQ3ZDDEyjt!rlnNXY;f(hXH6_Ls9SmGNmUf%J}BhU~=l zNzLJ0CKsQ3s79JTj2WpQeWSv%=!_2Uqz0*=U8qWbp3^5lO4g(zjh2thDb50<^roI8BsbYT2?@u?GC+CV4CBs0?ay`v2QDH&rz>M&eT;OtQv4oJx$ zJJOVjtHL$MMhs>@4@^kgt)AHjkdlR|NS}*) zX`YX)dFVHDSYn?IdmpKh?jFyKbkwM5#U#`3EqN#Zhtxk*HDUD5j)0V`NkzIz{$oPj z`hb)iPK)&R!Rey1HwgZqG#3~(WBx}dyo#p$aD z__UTlT5GXVR&-#)E?DC5_^8Kfqz9%mBc0KEvts;;*dpFZ4N_a%P?f?n@e3d&Yf_N< z$ICBC15E%aIh+=$#qa=;&W)lD?9-z|S~>l=IBfEwchE_)9y8K~7f$E^QZmMbborQ{ z%7t;&#(b50kHPV7LHJFv&^@~(Uj3cM> zkN%ITAY66R%R0Q>zp9pRGKOJQs?%h7&EwsIVR0}^TBx5yJw)|PMg2HtNGEkm^(ArF z4c)^n{>|{WS92$vAv4uE%ZK27XP7CI)l+wVQMt`H72;c8s%6B^*kL7cr};+ z>pk_Z!?8s{vtXIJ3oM_h!JZ9e0eiVigyNb<126tj4cJ7ZNY(8@)z6`*^cv`UU_k9zt6{hv#m?0h5X}YQ6LAOrbgMLCqX0W^ayqgbu9ORh5nhmN{ z9&HRvT=9+l|El7D`jWZm4ri_S__ACV+(m7uY_2JMD#= zvwrYuFag%2>kzrgQ@eVw%-^96pR2)M+{6M_Al;<6^w94*|ELD6pkkw{p<*HKuuzo( z);~pVlNvk`z`}T1u+GY4k*)R50~|A?1AE4}R6Op({bJ}RRAdGlJYxgiwuKxMShsqW z%JDjFD*!Ac*}?j^FwQyVpM8qgVzt56o>#jIfQ8aju=|sKOD`V|m=9nf!3B10%b)go zr|xC*YA^xz$L)C8x1%36z%rXSzWEFGS_%u;_rqcpL65$U<{#C79dt2FHRAdw1?;d; zl?ry7T=C%aFaQhVX~EvVa86Y8z_uO74C%lM+q@OG^0iz7{e+6lV4ZSbHG&-$a*Sa8 zUn`H#)N2M{A;}K*R%~4Uq4rkz&k5v-yT{sKuUjbp509eQ| zfnD$PN?E^yp(TKYBse3E8&z`vER3fG`_R3&$TzBae~uZ_feoGVL7Z!Ha0m1gDl&t;k<$4I zfQ1|r*vSd6m9_oGe+RITWCwd}M1+F(PzJ--ZKAxZ^1zOS7_ zp=Zc=01F8&unNIzVb+#jpP<2T1fszN*j|t7%8Li-_l0Gy>Xi0U4fa7E3s|#(8x^6( zucz>jYQQEx4^u_>w%H6|p(+*Z4*477uUP;V#?yk`<>(?B(Qx5njv3N{73rT7znObg z4*i6RL_aAvw7v`qUIJht#{_m!t=Gy=%^x@cSV*#i9TrzNZ=csi++iWldP%TqOOFNs z7NS(J2R+(5Byuuhd}63t7OX zZVpwnY?>~F(RN$~Mo`T!OZTwp(SpDHY`)!qTX!V!oD6JYyU?2!F8`59ir-g>v-wHoY; zA{MY~2X9m)bz7GX9b%1Yz~;`5P?gQ9$^fts)dqX%e(zrZ7RJ+p9n{-IR6FBla~}yUfPE zQGa1G} z=QL)R_^lf3$7d{HkBK7`o4fq*;UCq2J(e7y+LhF^8o)wT3RwSL@{kK_D*!Bvrv;mB zpCnp*wYn+C4C%nG3;7|=E-n>AKR-?(`oau$f4&L6y$v}gu=jdhQ&x^K7zbb>$qrVy z)?VxqbfhON7V@lM-#ye_3t%Bi1#4*ODD{m_tq))!!3DP6vLJikn{oI~7aW0TFah?= zS|eExgTs$tnMWKtyi=Z(YMm&>qc7!C`A0Qilj9>*_jiWX1h7z*0#=YF-}$DG zGk}Hhv|#s`<%pJ*uE!k~V#GPb2U}Zt{}Q_ud(8*15GDFaxg_Z6mo0`J7II8rN9x^D zM(wSA8Nfo49c)U)y}V^dZ!FUGUr~>sZ@jgS;YeOdUBLvq^GZde^diD=u5atsN-h< zV4*4ntbdw(+4N5W01M-3!A1^wE84vO9loN37$ewP&She|VY*W2Cq$XSc3H7h0$?G> z1h(y(^U5fT8FK(EB-z21%0fE-&>l%>=M8o)+xP(0EZnS8E538PZ)6jIh2bUixMl-qwPO%wW@&I(7rF zkYfV7;$psXbLvnLfQ2MGSi_Hrxvq7mzUH-9?H%^};De_DER?2#ZE++}nxFA17r;V- z3v92-r}mG(A5Q_Wa0H^k1X!1xaWdOa4@+U0Q%{|FuijyU!&$(dIuNax(eYdY|ELD+ zMw>|0Lh<6402ZoJ!1|}lr?gxc17Kl1E!drPQbny=)c?#eLprblzstmpOiX4$KcOPg zPs%01-k-6{04(H~z;-h~qx}Bg6nt6>lI&pHeR34-oo7*p*J8E7TJ(490brpt6|B#Y ziw=Qa4ORkJNN|BQX}wx#d~1ae8ho~hfJZc#0Bhq_D6?{If)}En>t%dUgAGk!0ekja zgyMbphmp`B)~E*Tw9rUZ!9=s=02ZPYu!0P^yJ@ZofQ9k2U{^G<5KX!wJj5|WI=lumH~KcB6=o zYOs;1EMNr-!WG@$`P%Z2YQPF6MyZC>n%oS)LRD?B1t;&!0I)Eg7VO~a2+@qN5PY%+ zV#GPb7hSvJ3dFlR9LBe1A<7KaZJ$>KkH+ja#~01M-3 z!DgHZ5Jj{Ih~t z*}*=PX6FhIOsnLzSnVD5>Zo&gNdTp(U>#N$N{@yt#oJnt-~t;y$l# zWXgB?e8rFW!gyM+8#={^e4pFA;8+|TSicQl#7D#G4uO6`MWUY+utlGm-UqOdV*lZp@ISHzSil-wh*Es-lZRLNvCb?}4cNqlXqDrf zYqkIuq7<T1q(Qm>7Lx2>$JP+$-?Zs}j@M$f!IrjaiVwd)X)0KoRUf3+><$hC zu#n&ayL-IcUf^Fjk5_{Uu*>~N$WB@KhQl&jAJYG-2D|ej3s`|(q{4d4vOxY(4Os88 zXq8-NX$pXasuZw-EV=WXAAJBUjHdEN{6QG|^ks0hc z=N0%dK*%wH-PL24a*{#BbpQ)VcCdOS_IaKb`)~4EtTx!@KXRRLhb0kE!8$ftE^YF% zfenC#$#Q``UtMBvHS6&zUJWL|j{ZDF_S4kW9G1B{=J{W+nKxO$+VqQ5R2}Q{lz&tM z_IsBYRrb6W#Q+wnYJ;6)b>s$sh4HjtYZz@6eR@7qpJRq}VDDV`A)aS{F$Vex6`8>n z9PEd82_VM=Rz4|R*>Kd|x&RiE>|kReL-I2_3|`4=vD#q$y3hRxV4*Y>>}JDH(nhB3 z9s*cMaDh!aYbDefVRM03g9)&DzplwzhD{p;%ey`6Z#2J zX0T~hWv}3p0CG%VJ<@h4kBCGn01HWWu*a^O<%v6G;vIF!6N}Xb`{?mJUjPeHD%e0D zUs>wWmOlV2B)GuJ`(Noh=6HuJUJWL|&W{X{oz6DEX9N|p!tZLZhhDINwRH_w6xQjj z0~}bR8nBnkVpJ)e0uKXNh-!n~GTQ$FfQ9k2U#Ye+gf z)xl42K$ID5SUq_w01G)Lu;;S2DZ2UY=S#^w4G=PN!7uXByf`#5SGjahe9D!&s0d`r|KG~gepeVmLB9E)qwr+A_b`LPeY z7OM@mRq@Et02WG9!5YpFmHPaCUIAbs!3B0w_9~%aX>=cG@UvM2Jfgt_*sjJ$Wz~20 zb%td|U)fr%2AlVj1?-U04T|=oV&CwOYQR>liB*+9KHvgip{h1m+ZeeW?65GN7HpWv zNGwiz{*GgYbYL^S3nVk^^cW8Pgo;EzDPZ><^7sf~A;$!^*U~iQxgq_^04yZg!TLA+ zox3yE9&g$}p7`fP8*EF}@zwwqqExUy+bnUIZ6G)TU?IT;c6814!jaePOL;Yz06TC| zP5Fs{i__qo8h4BSp$4l8uF3rH%ZWcb>^tW}cuBw-)qoW|j8&~~6BYtsA*u~FC-_P& z01M-3!QS|`UUV?d$%tcdbYN{Zy%tByZ}otFLPchfQ8ajus2E`J1j0!_64wz-~#(OT1Pm;d8#?D1`}X) z%@4~;AFenJ%S@ji_)`tGFp>rAo%9gJ^#-l+(Gu3E2JD!KO)ByJpGN^KM76;-oRFyx zU|~EhSV6@Lk-#*0C&%LGz~*+Z62I+P6JK;eMP{(W&zY73SjaJfwRxSOj9C5455Pi_ z9c<|LoV>$lpUmX7SZ%QN9N+Z?uuz%`Hm|g?bopr$GXM(-F0i&btNUKLu=E;$ZQxJ9 zBN|MAO&l>r)^EWuyf=01_o82Fu$MQpfXxzzCL@54exqMwvYf?A`0lmS@CF@Zhv zD^l6pX>Klng(N%JhbwgRR;CQz1YjZ0dPy+p11H(;43qGtV8gDu+00`^v?b&4;;<<0mz1JG71+H$fQ2MGSo6fj`I+DMPU5v#?H$%KZa;pJ29&0PRa|tJ`W{RW!ww4x zF0k3f3BtrDTRH()I0DgN0<37vW?9zV;2yBdquB!l)BpcR-AeYdfEC>dQ8cZ57Rx`X z0sCcEoa*Jp+ZO;VRHcCZbC{=HXXG(%`dx64A+-@ z>+hil{e&pdPYPI@v(CxC?{J6N9&8}o`z99qqBI{yB3YJ-*5 zKaQX2g3?s5<<7beMHU^h04yZ9z^3kPA*?s3>oRDtNiG48XfOeGXi!&Kt;~_Zu*@M3 z%xb8?mK|pS`~F(6qJ`fRQ~ps6*nl;0s@kqeN&pL0DPRTJ^8B#f_)Zs$rv>Y5y;{`s zN^5-41u;gj_D`OP?S~dxK|di%^pgTMpi|GSu){)*32dvR%}U+bmtFx_NV0={=<1mF zGv-8pj?=*e_Q!C?g>Xp#rKw<_+Ehx`UXN%5U?IT;Hfh}c6V|uAouI)7-VyMK1`}YL zy-Jj24>rc{niy(cOGgd%k%|RuUqy)GY|<@!fSWa{0b3Cfr>bcgZ3Y-fN zVfXeXW=RY7m(w$m-U^!_IEN5p1lz9qjX3#h4Snb*M2UV)XwF*bTGAHDe{{{Q(G7H#kZ-Ny$F2-B=M>SxtC&#Jkjyn+tV4b8&?*mv!aDnYVa81tk zin3$?3r8RtOn_~9I!AW-WGj5TJtXjIP4y1@s)PmX*9IYq{gE#1phK)t4cMV|<5a%p zq7MKTq7<^F76Pt8J%5$qGI`{L1e?j}J$AxiXM|(jkB7_}2Ih+>j?0tG&bKPm0b3un?t!^$CrW zIIJ-Y1hA0c0=wcxjhyrD9v68vm;hTEa8eedcV!Q#+vUGsR}HrE5ewL(hl3Rjb7maj zAJu^MoExVKarjyWV4SSs8*+W(e+_iQ;9>` z;O)>)h%$rK-5!SDO8_}0u%o9XDW}aX3WOaNlI&nV7(3>d-#n+_I2}wo?EKRwp8!}W zO$EEmbA;6E_pmtt77|=wAE|!Y-~2XYA+H7#VCU|#lx-L_3_q*gdq_epHQ3LuSinBL z8KM|#vppX=#2VFrH9Z!mlIOKv4`3mx4YvAM2Lub_X~F8c)fY$W>EpX15Mub3aB0VLVM7Hu7tUo*h~pVopru~_XL_CVWM z{4zL*Qo-&wERvLZ7DWJ9NN|De-1WY2YtpXnyc$e^b*VK@X7i+@H>gXQxVW|&Y}IEL zup6hWQ(WBL4Brc6jcULy92%!;mHiSwH49M+Six?2J?}vL%6J%03-)GkFLBe2$M6*; z#E5fNi}jcUMNz7(g*kU9PbJ1j&gVEBhEHojo>;8*4!fw?TzqR5qExUQZtRlS)UKQiU?IT;w)52td)MAiym&R30DFJ2 zsqAc;jTM~JNf$@xslf)W*JXbACH;1=LRz$bKL4l&>`MK3)l>^Z{FpaXrGWjj!#)yc z;SUeOcv`U4$KHs#mh8n#0*Ddk5O>(dgY_hLug0{4enONPto!{MP5>5iOknGNPEuN* zdXHcs$qsf(z`@+KtCvL_r-NyS?G~Le6n0oBO$FQQwW-7<{oHu~3kfc;E(?rvCbSk! zh6WehCEyVaCcqkGo|joJYJCBg8SE#ns|LF+h6SwOy|s#r9*fTNk7~efa*tOTm26rM zJ1kVy2CH{{xGU_iFrF4{Ycor%uuz%`_KRnkL?Yz=8^_}Qo394e0xH;_ z`q|Q^6?<#}EF`$VT5Rno5;yc|2n~iK5Dg~4&dRtXOFrJLEu2&76oYzdu+ix(U{f~) zDN4NdhVzeVz^2wqQ0*MQ?lyphs@hG;hrkYfUybtOr8?z5FUfQ2MG*l*Tn#5yh-Y0LXHXS_q1)w-)HO-04yZg!784G=e_V>hYyNEo>;6l*o2y6 zy8>8^Npf2e#!PQ%R2&89LBUs7Uma0ybqpk{ote$T5L+iwIYi7=HW!U?Is4R`0(s zkzp;j0$z*N20Om1+!(+@X)4&yr4mWQRqv_*EF`$VP8@0_dQ{#RfA$EDKs1;DyRdka ztfeH+36|Ns&8~)OuxZy=zz+TypqM-C#sU6O4cLfT@v4Uf!wLZ`RHcCR-z~ot_ZaWP z!gyM+*=eK2OIANmG7K8(7kzGk}F06WFZ2k;=4bMffW+ zkYop2nff-jsCKLkuf=MEEsuIt31Fc#6>MnnEa|1vYwH0lB)GuV)9EgHlNUKQMe4fQ1|r*u$5? zlm|-o-Gm($lI&n-b*au%76|+CTC6tMw4!PFYu-?r3O2}ckF>{`xvKyyB)GsHI{sLw zQ|OELVc`fwg9)%RIuDf1y7TfZEOS|PfT0@f{&E(u@j8KuMJtAE;2+h1wQKq3l3?rT zSO5!EwZZC*GTsSbVLUBZ<9;G>rz_oGa?Fr!hqcZ$k(AhO!mrzeibOvtJ8Y(VziR*% za!g<^)r?oR9Fd7XEC)$;u&*CK$X{skZa=TZYJ;_O3aJ4*ER?2#HCq`fouuP~?{qg6f?!~rC@z&`(Edt!UjSzUQGm;f6sJs}IVe02@}E)N9`Zmb4-@*4}-gz*82 zR~=Py{!tCspMmkJE2~_M04!A12Afu+3I6;%jHd;geV~TKZQgHuJO^ULImAl>{gU>Q zCN9#6&`*dmgMDQitOsBr#{_n_LzHs#OTT>p7Lx2>jdi!@RgPPQJ1pdh#cG3H98vZS zz(SM?_U^A-X^SS0@RtxF!38#KPz{k$Vt5{}1`}YHZ&@a@>D09rsQcj5w}~38a!oDf zX9-^K2vC$|wp_+PssY>n@}Fl3O6>LlSg5KEHn7XPS+K*xcv`THAHEYEYGa9yqCt!} zhY0q$xPfG;)cOVV6QayutNlM+0I-l_0-NX;sC;wyvk8EOBs*9^Q=Qzi>AfsCPRHNt zA8oMB#c@&q3#F-GMZO*mk*fwK!8I%-xWJb5Juh69{$C-l1`}X=pL{7xxZzX;%e+!* z*;EboOehOj!!R*V3!FrF6dTc78mYZXm= zIA%z94IAj&QBpho6h2-E6`8?$hX+^ySjaJft#@vnvf#gLeB%I;>|oPeyZl90ogiTfM?3r8RtOn{XQX(4ZYFZ4Dn zv+tY6&D3BoY+?ax+doh-cT3-L{!tCs8TaE=GkQ(&1F%q48?0Wi{Zjx7<7vUVx9=$K zS)#njF+)1A1IILxEN?MV3H^kML_aClu$c>&3IQzSn7|(G5Tnd8dps6)SV*#ioiZvY zulMxL_%UzD6aSoOgLRA;8xLS1N(H-bdYA)IyY$K@*H<}Lpgo?~y4emJm16as0fqmqktc=z@{}8}Jk{zr| zj(&cPbk!wZi`52e`*2?jfQ8ajuwRnQq*L}SPX(}$-~xN_(kFY14Yqh2297{9m;n1S zpsOsQ@*aMx`pfMPnyYu%;!GB>X6pkL=Lem|2QXQq8n9RXJgqhByz2-63sG&bqY52D z0W6HC1)I`$qGS!LCgKEJTTZQg+ycPOGf|EaaHL7OhHF ziic?xb+F-4>48{kzp)?h&`&MshqyBI4>oy_51=jplfBQyP z_uvnq!4ZfC6JW)yTF91}M&PeI+sefN7RJ+pO&va6JoR@*9-KpnF@inPqp?JB_Ff$T3sIt<6tK1}s#O3M za!g?7+}ohMQnwAhH4900un$d6=gvEAhF?_#d1A5JV7={CG-p^wJYxX@*@oT?bA^)fb zY|CBoDyttZ_;s65RU2%6_my7&ER3fG`{ch#;zPa-tvO~$cS#`m(pqA8`2@a*g^EN! zDPU!FlT!dJSUZKR;`;lOa83;u?Ke_`eNxB*c1S{? zBFS{V7yqaR?Cy+smHy62F|flzRc)|!_8L|JSQt+Ww)WReVx72Ib2w&52R7wy(=G@>vbU$B5bURvnAU2r zZ^~G}z8D{A*(rsV`abq-z)GCsbqxyV}QgE`Ws`6WERmPAaWlSC#-+NV0TOc7YsM+?{02XpgU@JCW~+x2e1uOn^08FjA(! zX(ldn_h=szHQ29}EMToI0u`o@mJ~pTSfd)S!`>Tnu?R zccQ@}IH%@)#ap9#5u$r_WFa*;#w;|^@n~!lo_nQB)AKJg&Y&umA&>TT|P*S0W2ih z!5TIy6K~o=`4BVYiN$K~us0h~-Z+3L73?9K1cz<)8d?EZNN|C5-cgzpeBbLGuLcuf zpLN{i@MvO@4AdF^>fKfic6Cr~=7(RF{`r`bf}K({T3mnrIDA*`|>E3LN?F#V`1K*Lb!$OV;>|~oA$~i{AO93n-*}=vOtMWsQJK#6{LY`QxHdw`~ yP&WVzQ7YJvy(de)uL{!xu#n&aE1x$;6dyYnzY7YEKs1;D>s_;fY+zdUvi}3F_nbHY diff --git a/000_image_stack_ram_based_reward/logs/PPO_17/events.out.tfevents.1680183432.DESKTOP-9E17TO7.30948.4 b/000_image_stack_ram_based_reward/logs/PPO_17/events.out.tfevents.1680183432.DESKTOP-9E17TO7.30948.4 deleted file mode 100644 index ac832342f6b0c50a0035e7bef806de8aaefca7fd..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 10538 zcma*sdt8k99tZGASsLe%GATs4rs#&Grl*>jw#bp&VHX)wjp{T_nWm_;h6-J_yAoZj zmwO^%Wkxg&vGJnFEz73dBA2x6YRO@m*Lc3qJh%Sr_4~}{_x<+nY37wLqwlLX*SEy* zhNJ7)V8gp!BmNyI5rm2Dykmu8sjJgMJLVLrP#hg835*m-g6*PXA|eEmIJ>oyFsV>t zC;WPfzdB4L~>sRll`#%MYh`0>m@=TPPl=0Is!gwTF!Q5_QGNstbOsdEkoZPRtc$&D@Lr6^|!s zCW`iNXBeW7n=wt9L!@7SNcMuLC`sfxez=JBe$acj+ugU;kzcPb6(kCa;;)tnf}~-Q zVpiViQHWtoV)-OZpW@-M??InAb2!rom6Qm?AwpJ6lof(79O@=(VlzMU;WbAx&6&o1 zu`fm>kx_AcQDk&9>+nYdrPYg;P!L(o<`f3=V+E2hfjCIW zVptA3-IVRoOlMG$P#_V9i9`4jfmFykk(=T&Wn=UmD^0OpLg#x>Y{DGMWcC%SZz{;Q z_skmA`?I4aP?D6?0RrQgR?HE7fv8APSWp~4L?Q?d`}!-Peu3`lCyHSY?=$GEHdY{t z5%$FzpSO5jPUzYMMl`p{w^k!<_ai|%uz+VAVq8Hx`3>o+K-IwIo(=#hx)Y1^EVq2~ z>;`}oeH<65_XljuHTq-{$&>;O`9j0kD{a|5M~ zUb7`YiVl(^^$eQKE|EAbqBE#2((x+>bpxd6Vl2{aO*=SV7Z52xiVjdAEtWr4@CORp z=&Tln)HPa;V+(!n= z^Xb{Q0MfhN-+lz-NEuA7+qUqN-C$63T>a--^E}jfl16l{Xaz{oNi5R&;j=tr_XY;E zlUk&cVx_9u#S8lZr07lzQrU6tDBnfT0aEmFT%?mMhO<5P?NE|m4-cv7=>H(w`48D( zljuIwCe_d2Z-4IZDY^OpDLO`k^vYQSKij?knfGt#466Giz0iNZ z9YBgM#v(0c-}6iueElzg6dj;KDz~p!I2X*lO=qIdd&Ft&?9KoDW-dou+dCISYmZx5R}y zuF;9@Yn{^oZs;0|9S%?G#W|Z0j^7nGYt0QmN14ts1W{tD|DAT}B_IQGL{{5!4V1nY z^Kuc{x^7y>6)cCs>W;dM?z*W7ajv|C}_5 z@#af9VS>u*=elOavml>hS_?*j9bI4U#b5WL4veYndg-VJ`?Qh-?Bf|(JfmW_vGk)_ zu+I5$s+e64EKAM2YOtUc1D0`u+hM&U2Y?0ValyI{Hf665dH$K=hInA}au*^uB+5Xr zPtZsVR$71B8-N8lBCunU4U{YGlg9zDAV~pMQeAWC?WcLPhSde@d-Js(01K+IV9W3H zco_R+9tU7Sf(q=9_jW7n%hMOpS}+RinexG$ccnqw!I+f;CQMg@-P%9`Hbb1vOIcZP zpMF#emLc1q;_xh20kEJ|7p(crrZ4~&oW}**V(HB`&vfsixFH_cRND>6-)W-|uusrP z4EA>Mt4IJAk~<$pK(NH5P2#xtkt` z=Vtf-upmJN_I^HF(HlJ7pVop=V3D7WbG)A>&H!U}uPks@gFV+WCx79`2RdK%xUX;`u6U$lnR1-mq)WHum@8f?Qy60i(LCJ#xR@`8R; z3syWbQB@l^$OnK0tr)P3W86JYpSuCD;5;r^msnr+>W$IYC~k-cHZOM*l3gr22KEUW ziNOwPeQFB8f*cXp;BI~8kbc)c0Va;v6xP#WPx?rE>w^RVIpc)G{!7tu( zk(d7w02U;uz*f8F$Q`_k9?)7a3T)hyG)_jb9v5tJmK~eFYW;1B8{&bL4oF4Z&Ezg% zpP-Q#?2!dQdjMFFBLchPq`uN&_O1N@EJ%`r-D=wIZoIkc0Igwl!8*peb^@@V8Vk1f zfrFRaf7fyV79^;^Dn2AC3@iPQ&{{AG?6p5kImM%^rhzd>a_imIU^9-AfVF5&40+Qq}%ylnKCsRt#81CHK*vrLO>3a2^*d+i*EMEoDJC#SQVm{Kl-zVmaxy^sOGf@&;S z?~_ZtxYw3d1F#@L1-3IiP2S_&B_9aI4_V+mNytjQR5W5RMw`)rTZt zkteAUxm%F5x*08!@KNbFM z1Hgi6EZCaxr02Z`jz%q_E<$^KyUKs782AiF) zPyC@P&o-4;Fm}ya`cW;|)0>i1tX&751F)b~7wn&JGPeS-;5;ta`TrEM_s?-0MR7ws zungx@$U;w!1K1~MBnEqVqT6c#7UYP)_U_bE_MTZY41fhmaG|tx3;wC|H~sVA^-pY diff --git a/000_image_stack_ram_based_reward/logs/PPO_18/events.out.tfevents.1680183612.DESKTOP-9E17TO7.32692.0 b/000_image_stack_ram_based_reward/logs/PPO_18/events.out.tfevents.1680183612.DESKTOP-9E17TO7.32692.0 deleted file mode 100644 index 8e7b54dfef3ca47d98d1e09692783e8dfabf22c4..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 49623 zcma*wd0b5U{|E4i&_WR@bSb%HOQDozrkQFi*_Ws+EmWeCWX+PjLS-vUQDmn@_NGiF zM6P5ht|ev3ntfk>_d7iLeO_n3f8NLEb>5%P`#k$NGjrz50MYONey$&otQ~FNa@b_; zTk_UTe8YSKLo5}u{X)X~_8e)c(=FUDWajiR-|0SKlPzb?3J&%On`b#EEHKs5+E=NM+w@+yJ&UU@c&Jt>2bp@COWNknukpf3YtDEyoXk40?EskJ%xa|j+svD-+|ESL4lLzc?E>|Ob+}XPxS%%7lbNTx>f!V(%RWRL9_gR z$8@8#q-2Z@X{R8~{Hg<8jsQ|J$c9>@{ei*NXf!fq$B3!Ixdon3IQn@;6pm{)%Bc#&THNaX)S?tW0!3C zf?vMpV2Nd$%15e^zUab%)Z0RlW>qg;aFRgUvGBW2i`RgZtVux{dED7fa_k%+C5JO2 zjX1nk>@ohzeD3KnAw9aMnRKAf>sHW7vK~9qmtDr*0HkD$4e9c5&HS=vy%d0y400n4 zcfFYRImh2Y$U^Bzo!&hi21v=mRHO^rY?O`)Sh*39k^w%XR^`shqtj%rLRw28om}%! zCfX`Wh9%B#et(o2>3JJ&q$Z17=?G2&(&cx)6#`PSCIzV|+j+Uq(6)e-9L|XJz4aCG zt(E^8a8Hj3>GvfarO&&EuZ2#M_1KYCm7BN$QZmMdRMA8;KUJcU4oJx$H&WT0za*g< zSN(-7l#cZD*=CagDOs3`w76iHZ2O7Y?|_sH@FDH4=c(+O;*lhzwFJ_t_9^oGV(}PQ zqWy$Nqt!@v%Gi;*9qXWoRHU91oFtH*E0}8+TM0t5u#WoYtpi(1gz52siLnp~3JJL2^yygK?GRB6qs=R)_Sf?Tqkdi@eq#Jv- zmTGxuoZ&tXzZXhJI?;EPHXtPnQ<27uHjy>1(sc%;WPlH8PT{{f|MnWXO-O4Aq>&{Z zBYLaE z)?3}(xu?g3)VKO?X|3dEHguA#$BwjrJFT67l#H<iHNo(h4_rq@ssi6oH41my9BU7x`q_J=Rl14nXcn+N;lk7-+61N`&q-2Z@>87-L`TcjjO$4N5kQ=G& z;sSAAJws<93#B77hpYbQU{O(PksXev7a8l8Y-@hg2j|79?jn4h5uSl8)5ZWo#rMC5JO2 z9h7G%8L~g?8Js&Z#fr4~r5I^?6MakQB$;GKnyB!Y1xU#l8&Zqy8u{{?ulVYo400p& zUb-}Q`;lJvge;Vf^it(UFF;BbrXt-aGmxF=_D@4VN(T6lI(rA@I3BkR6Vh4&sW|Gp zJl`G4@)>2qRddwFdtz){rgH1uu)X83^f2wwV zxqmoTr8-S_zW4dg5?CC}k`d}HU1P~M%V(>2X2|q!e#naX(#Ugt@-6<%@Kh<)Pg}9ocJo=`(K@gq(b59>;Np{}f7Yu83sos#|9i17 zuRnMJfQ9jlU{^h^7H>TCpaahgnZV{I2TGIjs_mekP?6}T`qQib|Dbe8(7b~H7IJK0 zTQ2*h(y`j*4qze44K{RMPsxKXdbssKo)hd~^N3vl7NS(J$3#`KwimO109Z)yf!$@} z;xMlM3kN|BCcxegnC{fu=ffvBr;}UejaP&Hx`_vD#KQ~^;ZXovnOm7B)P$=e(e-TZE=_>XtDGi_GP$>9e{<>RItmPmdT!!Pbvqnkl+J*)csJ-=7}mT zK@BFrws$R)kNNlg0$8SJeEI}6*c&N4V2{?ElL?Ok*kJ`51_M~AN&zd%bj~h1`xU^# zct)^kRR$7C?f8c`JsU?Is3 z)?3^l&-ngK8$pYugLRr`?FC?=G!<-I!fM%?p<8wXSV-`Jt;`yr?33Z(E~vo-*xQ3F z zGlD%aYP~q>@itqY88U&5(0(NO*P^-<`Uw@;!B+152k$O~92?lRH#G8%4f<*T*gMCF zGriQzA?x_Q<6v0k{_4fvYOs%0JYbjI)>a6Q0$8J~7ncE8s7e7V%5q*Y#d<1$ zh4GAFqo>{zH|TO>2hR+dz$$F|NWb=M&=UFy6^VXQUUZdKzmJ3+7IJK0FU5%RpIIE6 z2w)+}4L0&upk!Bk>z9HSOW$Ene?HO#z(Q#%*c#JIveXVbIRF+Cd|-7llXHIU)m$y8 z!35Y|dfl9|Hdw!dW%@Lm>7xdle~AO^1eYd?cWYna4$B#>0~>yIL_w3Y1qT2uMCo9o z&W0ocSQyU;w*J!H;w<-C9iGK8fi2qCO1j?Hw*dMH71_c5@JN#YSje$~{mWG&KPjrf z8Nfo48?0EX#hLoSJHH89EFJ8labpYtER?2#jdhshIOcBa7629!d|@Z zg9)&{!F}cPez?}cGRLTbeAQr+ZgPNio1v!|c=SQ6@Ms;_g9ic%Y_c}31F%q)4))~P z(Fp(+#xsI7ala;h?P7|5jSwULmBc%%-<+_Q#vIx`5BdpFcCb$`p6CZ)A;$)`{qCQt zMqO>^0$50LgEbwjk!u|KwiD0k`2E*O2Yc|?^jrW7rKw<7JuP+||9vmM=z;_v*rYq1 zl#8AOR|#q`0k+#T9j6Hii_&13PW=NWslk4#*HOgn7TE>=<-pD(G?OC}@^dO9U0CMsShvY)uw~DAz`9rLnIt?4V3%KhI~l-2RXSKB?|m5n7REDzEwSGw z_AUO^fMzp{mAaZF%mZ*3v9T5u2F)`E&eKPfM|R#yDj1YjY@2G+sgm+Im6*bx90 zlH6eJZbj#v8j|54Xt8v#|E8X{1+Y+>3U<)oILFO)L3j-d2|loAHlI@7_BeP6z`_xT z1`}XKPb+0@i@KJ;GPg|W@2>_MwWJ>Vy#)UQySd>hBjHg1J9lW?HUJi?(!sv3UFZQj zER1IatCbulw*Ko;3!WJ=fmQTvEnRVV$$97}R3!RI0ekU@V?6*1IX18-E{XC3#_m`P zU?Is3*89eT+*-R8HG&pP2Wvd|^j!c8rKw=IxiojI+ST6}c34R8fwf<>N2yVKzd}%h z39zqc_K^3VYLClIFp~zT!B(&402{KQx#D>7x*yOX&S)K2k*Hrm%+%iQ02ZQju*>h9 zKL}u9JR{hC+sni*mwR64nIRL{_r6`E_sWOi1^^Y=!Io(6&H%8GV*}eaNtFM?!&DEz zLXsP-NYuz7qT1q+pvBU`K2Ivm0kBY-3U<@mTaLC7A4dXMNbrH(DJ@n?`UgJ(uy6#T z!35Yf4|~b=+z#J|Wtz0GpP~kvm%ssbt4DLikDXTdE&*q>4y=nyXu&;M;W+>cQ94+U zR#)&VyD**+Y#&*0q;q-irY&l%|4>bvWN82Xs5Q&PpHTaR@7`rF8~WUHn7d!Y2Y4n#SUT8s9cugmEJUebyG#4ZN`~GF0ZL$N^S#%0Lm?N6QU5#2KvvD~b#)cxdrW1HeL* z4z_X5$mVcK0OJ|KHi<6~pA!|ScxK21_P~YS(vrA}-q25|Nc5Ak!|u0gcLBgcjty*% zSd{;^Ys6y!3rTLUl?OiL7G}M;Cup&Bu%}WV;tmU?sbCk^Pmtx!6rTaGkl+JrWf-SS zY?dyp!35Y2VK#C{@ig2fS5Ip_O%3+SaUQV!E_*kE4sk{SY+1yvt^gLIbg)Kd?N z7|#fHtn)Q-r_=g)4k5<+!9m)@QBvR2sTKehqU>M~PkmefU?Il_)?$@LexE~k&j46R za)VWE`YMqhjli3KAx|up4z{+Q@)hi`5T$~h_2ju@|Jn~@0W2i=z)sN5P+s!sxkFHc z39zMSJ>}zU$}~aUn82n%YOn|LxxiK$DEiIxUMxIX2R1O!uV7Jp_doy(Rq0^8XJ1Y>@K1bpDyz3;+uWKCs_6omN(kOkX6Z!35a2 zhpptBew?<3W$ND23|50(QNjhb)IebpaidUpv<|F&?1X|@KN9)^Sg1+|t14Pm0$^c0 zBUqgc1`>0f$CG(x$OJZKjH`6d&zn}zPpHTa)_jZQc>oJJHn0zBzN@CZ(r*o5A;}F^ z)pL>9Ypx~!TM2p29oDwdy@3E0qExVby;?Y~$lG=az(Rr#?EIBhI1vLbUEtf>*Xqm3EQ3wS#^_lpXB+Z8b{)Eace0hE#l2 zl}|424qze44fg$*)pz(S42FFxh&1; z=G#XCVBrWvg9)%tB3{b}KbeFdx7)NUnXU$#@PY%Z^%`x(fR&+{&>_xf9avxEJ^7FG z)`tLCh*H3cjySIgDZ^`67|#fH^xR+KahU}lcxK21w)W|CX{$NcIzd07BGFIEy96Ca zw3!89A;$)GL%=sx{}m!7fQ2LvSWBPW;*jJff)+~$JLjUg0f2?lRInq8#>$Mn=Pv=U zkl+Jrw!lH@Ctp@BsKEr-;qCODbj^J}ksoFA37!qNSa~MrA@jA<7Q+b;kZx02Xp= zU|TN#q3Rqu&k(>uk{hh|)~dXmCmM!4r-SX1;PSBLQvfWKrh+}Z{gdN+)!;7x77~15 z%a1!N`%jutCaA##Sp6eQ`WF3eDaEm=~Z{a%6|eRUNNW_G9#9pa4Ef!(!w zQU0TOPrLyvMCo9krl0%;U|~EX*!Oc@h&>O!RPxM_X@|{v6DF+=OvAgipdvfi@XG55 z7IJK0Kb?82`dR(YUH}V8Zm^LmeQ9(=D_=p2rSGuqV&}yJSSU>enM_86WSGJ$2D% zeVVNNWZtJnP=g7u>CMdK_wPq&z%plVE}W?byEKsltSCiCaqw(NpzvrN*p^39^1B50 zY!6_eDjjT8`*!%yS{Tm^Hn64SWQ*o+cxK21wrh)-($IN1cz-ceWCz8!#5Oa=mlD_>F^@*vwgKuqO|3fbD!oOR-#Hg4Q{s zbzmb}!$Ce6OEFEmhpma|F3#F-GwSMZ! z3hJMG24Eq<2llk9xib0SwdaBwOn}vyXz%o?%nBcl;&UW@wi@h)6Fguyja-Xw%X3Bn ztWoZccK{Zm6tMq&&3i^hFT9rk#xsI#+;FU9dn;2DIEN5p1$(FMVX1k7 zz1!bo2J{o6>|mc7IpY(`A;$*RPXD>8G{E&7fQ2MCSlI;Q+}`7(hVq<_-`78MurJ>f zPX(}0nhJJO?^wq+zqIuMEF}2Ax^3U8w9q}>UQmMxu>IGzl@RLqDM+JJ@xhGX?@!$gzP9F!`ctoq6aIfQ2MC*w9Z_d8WzI&Vm+82YY0m$5{Xi zrKw;irZ1PZ8CN?1z(Rr#?2fj<$~MV0Uj;Ro0NZR>FZpEo5B#3q{O#fM)nI=;-~hYN zy1t^xv;}9OL!8k%uvvFTsfKm-p8{YZN(WoE?9E}=VPQNY*ka=elCdv;J>!`n6WB{% zwnz{D9E;yVhKlT9FDI0B0Scp==?yR>@)*?n9KRAE{AK1`At(5zZE_wi9;Rr;739#qp?{TVXQGhqUB+d1Y zP=mewf(LB;Rr3+RfintV%bX=I0W3u6VAI77!T~IdX9W8$t(WA~>icdyGh_lgtoe57 zg%Jr8p`TEZ=qKe}f|v87w*pwmv4Pd=@JS^(wM-MhLXsP-s&lhEi@h81T}H@rg0;(B zJ|4hAlnS=&%}K{eH|?hsoBuug66<}8a}d__=$39!dEYdCFuX^kIOwW}DlKn?cT zCl0XDDoussqA%vafiqeM_TJs(GsU;;aEFB`1?+z}zYKerjUUazct)_{IZY%BBVF;K z_7Ee^A-?Fk`)!MKw`yQA^b?}&U>zEr!rKcW#|HMxoTsWUQ>8ut7LwdxEqYm;k=u>O z2k}6jSS)>q?YCy6H-LpG6|7U=osOHYOzr?+A;AZB{G%z#FO#oL5!7G;tX*|$`NlpC zXM?(lqvZ?LVB?o+vfoSaKd_gxW%$M)XB5CXq-ZpT9TuW=u##2wm9WFYct)_wLOn_I zU&|NpERJc1jcC3~+97E<-d_wA*}-maYkdNCSje$~?QytTH7fRtJ%EKIH(1g7i(>zb zN5cgzmJas%qgB}e7D`jWUR&=V|KjMP0tm@?hd{hyPX9Qc` zW4I)y|M5FKi(>-YwfjD4%j#wLwRxyW^pkQ)@Nu6Qe{2YHY+&VUf2ij7nX3i`M0$3P5J{z_Gc38-Ck9i;pmw-JA) z2aZ5Am;kFgvy=R=&RG1U%gxgwQVlkBCkNPD8|x`%=e10OKWWZr9oTI_J!J-xzn{Vm z3sE{)b5~gifQ9jlU{5;hNIIsqtm2s=(++zqYK3%6QxE)64yZ`>-s)ws(#O#mz;xxo&9+fyR0w0a_Fv2?HrrO(#`SSU>ed&cIjW1p!;$p97-d|;2h z*rv=hw@il}0gga4m;k%b)uV>T88U%Yn5~t1^{?@RenLf}pA@iN z3mb+2Sje$~9cTYQ^`_|LO8^T=Zm^rzEtibS{B&8+V(DP-Wm;e>!y?KxFi0d z7J!8WAJ|!)|58>e`dbQWFafrWOGBsCjpOiJBpTODm#V>*pWp#|tlw*6=n!WVzz$9_ z#v8aHN&)-dCtdUOlwJT9#xsH~@qa6xd)9sz&kUKscIg=`9TIKv3i=5Z*}>*6z1|kU zLXHh=+Vy)X=gXV-16W9MgH3sCE!8Ud+f~qF>0pmt^1A_Gp)?ijuxqulJwp<*0W2i= zz$VH>N_+23;{-LB0Q)XBL_RJ>3!gPHr;ph(HP|BsJYXM8ncW>a#2E#!a~H=}!ww5k zI@oiseDG`DFrE>t=J7s~^z0t^E&;@d%R0P{CB~xooAmCoFS|z3Fl_*tM5Az`7sOR6I$x+%7yyfK|!#+AU}a zV4*4*g&Z5$ zLE?|97jNF(1F(?f277#k&zTWR{R??c2OHQIn)(F*7D`jW{+--L+P-n(#p z!35aJVOL|Id&2R33a|kh3u=5?Vq_<{2!%HlPvV)!7^t~&9g&Z5$%ItS4 z_o|n84GT$bu&Y@;S&F#s0EGlK2=tc~QopZ9Z~88W@-Y8km&>YkN^w`)R0qMwv^3Dy@|Ujnd@ zV*~pk|Fvp)V3P{iVIj#4w!`e{(#8Aef40he6pH5n z77~152QJ>AoUnf2bpQ)TAR0`7O>NakuJJkr?-6t``tTdU3g~51a|b?6lvoV2EPC- zR3!RI0h?Qvg%5*+92?m1l259ixr4d_SV(e%jbFMn?`$h0d_F$pIl=1va*P465T$}O zvGS5WcQU|l96*8(Y^l9m8Cm3s-|~bb5Dg~425WSe=bk#g1>9oV9whh)Ru3vh>ps&ufr1BML&urQtxZ0rb;8iG%vn51b?d<@|<9&zmYiu zScp==`qr;?44mG^33gaW@PX}g?Nd&Cr!CI}HJAW9WYu zyLEAdYNr}r_}%!5`16>eXc%Te&Mb{P=g7u2CdJ@ zSN5U&;N$r1dsnN$KHA9v_UnLpiidB5MnQ)-qjg{lz6_8*9PMcXU?EBeYuJ374S)a1?C0_Z&2W?rS2CF*E0k&|ThC=gVK@xD_jMjlQUin7$AfZSEU?EBe+cK$kCxC_V zj9}A5BP7elyu)7-gBWoRafeO#u~%B+*$5v@0#SCbSMS;y0$9kgfjuC3rCPt_Cq982 zlH6cT(}w1HCpaA8IUT?MI_W#?>@60r0sFo_1R zFrE=?%&;Sp_gSkDEW}vB{*_)TO?@=75%d$HL_aCluv3d$;M-b|V*{HT{Xi9$tA7G^ zSV(e%U2r!pui1u?_*g&46N{yT4GwG855Pi{3O2hWU$*Du3T*%j2|lo=Zp>DWj&XJu z)L;Uv?T{jQsBBdVfPFk;eykeo#{v$p(c3f>xf<;ggh%VZTGc$4=>~n&0kBY&4)(O2 z=Y9YS;~BxuSvp(NB-P%LXNF9d1cO!|mEQdrc?$Xo71_aVzi8PMc38-~V+g*{ z4M!jvOn@DE!df2IzCQsgcde1002Zp! z!DgKsg>P%Yct)^iH`kLSyHCRJX4Fd#}A5mSWEhlME7Ps$D()~HP*01G)b zuyg*YQH8jS#vK-t++daKc1hoaw!mBQAx|upzQYD-?so#P5T$}0RyDzKsP=*a01F8| zuygw!RpvRE^oJb*jzBb+0NeWYTiJ}DB7Em3IA%q>8tkD89@~1njUdo)K)TNdqOZom-9JnIY2-yE8pQ>d`11Kk9~xL_aBDSIM^70$9kg zfgQN4T6Jd0n=sg6A;}Fk#cW_+E0b1uw>soG!Di&I4+pRirGi}_^S9&h%1Ao^3kg23 zh2xx*5Aw}E16Vi$(O?4X^6b9yJo)J;IHwL_YuBm4uBzq$Tl-2wVY6!LSmDt+u+dRk zva~0#B>G7K z+cY@rB!Gn+8`$A*D^&0N3h>8~A;}H)^`nb<;%BLNwMQp7s?T2ntIH$+1u3xVPTlJC$?9ZCp_~1j% zD1eQN&S?Q)Axa0^;LG{(02anGf?eZzKw^0C@g<(cF@e1>p+I`oWgmWR9x4+3q<}rT zGe94}LXHh=>5v*#V2}Ofu){)<8>~f4R9=H)UsnrSEd7#Ty~Y|t01Kt5V7+@TkyVJ( zRsdK?@PSPY*wS}U)QTk75#R_!g9)&02TYg0@lwXYGR67ZHmJeoe&zuCVP!qVnnY0_ z;n6y&Oc_|u(`LvclH;f$-$npfNbrH}=8&rFTbB41z`_xT1`}X!8h@7QuiaY-%iLj- zwMh;3-C7>7&knT0*K3?n06Sc+n*(4WN(Z|@rrHi*VLT()y=Hb2_tSk2@hpxB?61FK zrF}LQM?pWKBGFF@Scezdr2rOkY+yT$xTgyES^62kLXsP7%Kj3GkxlnGf)+~$+ivP) wyuA=gQ^6*OOmd8DY&00aLV^$Msiy;!xAe;K*;;S}qQNBC>9%rDw-TrS1Bc1DNBwx;|NXPFU%tt(lFxb3 zCUs&vvq*(3Hle%p7kNT*-=BtbH|>@zPnephh)k3zqPtH`nLJshnASa25t}SmbeDfy z6%i8~FOT^CKLtg%%DOgw?w?Cmyfrx;HhtZ<&$YN|+ttC;&eT$o7$2XQlI$r@iinpd zL`;^;60CS3HqtHbM-4eA74p=^B#*C&8hT`R`^K7~1N?2EW-C*3)8@&sljWW}cxXyF3%(avRgOrsm1t4w9!VDM^u-77-V3wY6I_ez&@xE;4WLdnzhEHYp-TA&W|m zO-!&F`D+v5qne-rFn_3W(3R%Jgxz*%;Qla}Bnq(z!Lhym$x3+a>=t9hK0{~=W#)(raL zc`+a*)+8b29g{rmH~1PLB`&8#svh^*$9+F9gL!-32Z~6a?7lBpX~}bdNfPVPBfa&Y zXd@sc#^{hvtut1?wChmAf#l~tANuP2+N(?e1<+-FD^jN$3Dwjs}kp_(E+YFEr3zL!N zni-31BZIvFDKWr?G_be3YD7cKI4+|lAe~t9P*mye)zQ823_jof=m3+~GtCOLNUtaj z=#}oUYbCYs&|1Mgs$)8A*h0;*XosW@jaA*A6^39{veN^S!injb&>ZZN5~_cy9e=jN zqH`=eq>}1mepBE(eVlcd#vOi5YTF-oNKZ9rj$Lmc13RU&nmfZ-ExL7SfmdV2oVPU* zSdj&*GQ}rjza*Sfv-(;O9I(oFZY-VFO7J(9CUcEQJL3EP?2G07zQZK`WCq zV_ti|>Co7(7A!=`VE0Q_1a&?DU|~Ha*f;ZA@Xc?fWU%az3hanU=LIHJwyj{EP>~*N z+p_)504(I_z}AHut8WO(t^-&|GJ{o4+|1wM(!UF*X7$0I+0gtefQ8azu(RuL_`Y-+ z-50<@f(@*fl~C2~%8lWi22223cj&Qb$FUa^pv{uLH9NInSC%k;|wC{E4lgH>KToC;u}G#Tubh0dbk zA8Nk>SV*vejlC*RJwAFVozs8`U_IOqi&_l25dv+#au~2%3$~$(0c=dLt@L@@kW}tb z9atXkpr$l$h&O1kQ?l40P}>3 z^k7XMeK`kUAx8)HQ5R!%{NM970$4~ggWdC|`ry&jU_Pg2^}!yzI%Wreh0SwP33sFn}GVww127J=c9e{-d8`yi6T~v4MPslk9m;g5ZR<<~5#`I>;X2*wJO0-~i&M~CF=(--$S~^Q) zKZ|=*2ljgD1I;Fv_c;I-s*=I(l^iunXn->;tfvGU`plibefTZ>^#L*MO>Qc%rElH{ zQcgDahj~Jj9_*;;&#C|{@4HaAe>Q-H1RK~(nK7!rZH8ZZHDZVwOflgEdzK%2RJXO(KfE?Ub1 zHYL2B9rq}JJ=5$H55PiIeXx>=Cm#Y>SWgLd(%KZh(8S$0ST_U*o2LgliSRWMJe zNDuaT!j!)NEad3Gw!Utp_L61z16WA1fQ`7KvMux)#;I9-u>V*UDgi8%CWD=I=DcXk z{70JrEF{>#R`#-11zowjkkfz(U`KRVCf;IYmIiGu*jrVm1^cjs0W2@fTKdT5>1ys# z9a!G@Lz-n5MHT=Ss_KI+JG5gsfQ9vxVE=Isf+o86PxGc8V z7r;V-4ea{!ajKR(UPf{nFafN}Jxi2iUR4KeR@C>Z(1JZt%>Z`mWov2Y(MD?SQ5{$h z54EOeR>cnh7OIlK^7cxygY7>9SXfU9cEKep{+^H}9xOYg0((gET#)(UK?TecD$;}1 z5vUJ&LS)PmjokOAz{wRX}K=Kb)Zi!rJL zt8l2$ID6(D0fY!n#pUf06PpC)_ zc21E%0AL|U2e$nHBlWqCHaP$mlFVRlFZU8G%{4#GsabunOC0MB04$UygB{iXs<3`} zqzb@7f(>l^Nug@Cf3ww`2223kp^2gRY<|QFXfr7B%V90p^mHToi!NT0tu)-E&W3wb z2X>sKSR?V--3h=#RT5a<9!bFi(p>^rPYHJSR!4rl)9aorJEQ_zHpoJ_KWq8VFi)sR z5B7>p!7Ts_IXbZBEsWGkv))$#EF_u1_U>zV=-H0}S)7{H2U{H!>k43@G#Tu}`b<%G z-{ltpEF{>#I_{29g$>Hd<1}Cb*rJthMds=cOQ6j^`wY`)!QNiW0QTq+2kFh@m)dZT z>cGyI9nw5<$t?u1P*or7;T_6AIK#qvO0XZ(y72q=3I2^`hg4v_|F99ZoILa*%o8fo zgB`W@zAb=-935D}6GL@f_3s7%7Lv?hZ%--U2LKD}DZzT?`11F7jmu$ajtcB9nXxczqeoMiCsd>d zTY2()Du9I?9oY62hU(FIS?>WXB$>fB9IzL3wAwb1Q?vSDd*vHX0I*P+4EFS~zM^dn zsxtr<5^P|_vqY*l*VpI6fV1le@CXAYfVFfC5-WM>rgi zCp4=MHf@_v6@Y~(8Eo{I$-ZWe*Ng!yB-p?{STsge)A`JFP6H-@l?K|1C2!>Tq|0MW zK&2M!r-uw+dxSYifBLNrekEXx>cB43?A6qUzg`4jA*v5HzMa1_fQ9vxV2h^o<2Rk~ zR|FhGh!Kt zlev}o1h;4w`&4VVD-{w{NI+4A#3 zXw(18?lW4jSJRE@FS@>g^-nz_;~oXDe*{HT0$8X@0{iWv>xZ|+02bC$f|b7v=ZC49 z$Fl5@>MMcgo36q>Gji==o=}kT8y|X zm=zgv5t@ZO;ipp{>SaPA)f7NR7u%H5K_ z{C5)oEUc#lTi-5-?=~!;9m@`>z_xtqDokJX^D>wxR3yxk^p)Uo*qB2A7IJi8Ukx-= zKR?M^4`3n543;-uQ}O7|*gc$@)dzbs{aqq}h0 zI!LkF0`GrFq)UmJ*opc_g<;rg|VS3 z01H+1!CvpMateTj^^{=WY)$9;_fz&}*&!9!1?NW!H`{rd!aSiOJ=l#^#u@+%IXbYO z)duRsRz5=kEF_u1Dn}KnPIx`=<us5&#RO$zY2Ea>e5VJ=y|TNU(ujS>9V^ zt#-@gG++YQq3#34o4xm4f;PwW2)wKXTl0tkY;v%pwAqyFwcMjRuyMPN`#lbG!UqRX zRUhoZl-YP&3)WMDoxE`#zt3n7SC$=8fpvCP2o;aTg)mR3NDtO5fA%Q=3pqNlo053y zn&(x402Y$WU<-U-38t^`e3)oEQ$aulqQ3%E(!HrP*YwGU?IT<_Dp0`m7C4d zdQJl-fPFh)rdT>~FskeM-0G?p?4KD;=r6iluiHzXKPY_x6Jm_&z?MJE^_ypXI33Qg z5Y-1;UI|25uDY1)io{H#rX_iw>Ghp#`U~{Z<{hkbzsxd z=K6KLuwoK`g(w;9E{XiIO$LC4^^{LeEf^!$Eh3b&%Pr z0W6dzgEd$w7nOL2;9nd-f(@)y`%$V+RhtUnj8Hq40FN+W0@&kD1!A|t?RXLz5whf# z7VN1S2C%Yn8|lZ1eem^Y#;6YLXz!7Ji_fW_0$7OZgH&fhP+q@ z#}Hz)U= z=hUqJ8P>;oqBVep(qypre+v+$+tludGb|+7z-}&dR;i7XXL1@a0c@|2?ZmZ%rsL!G zk*DkKXu)oM%mDV@FgxkMJqa6NLX1%z*wb+#evhuMXboT?stz(S4=Y>wOCM~1JwbPvw3kYolMDO@59 zjF0o?)T}<(b3OTM04$UygWXoSOqBP*D*(Vkf(>ldnG}_8!-3rZ_QW*;Ji>qpU|0V9 zUNq8q06wmAd(x*~3wG|@rt}wGygVD}K>vY0Fd@dM4s4HN7r%iwwloK@5Y-3!+lho! z01N9W!4BCskN?TxoQ7qGRA56cOcmY^J9Y%-2^9(RB%NVz21okT0vJ@l1- z7=VQ&GuVQ0mjz$GI9}t_tUg$`Hf1&d7D|)BR_E;z4w+`X62L-&4eX>l(^YHTul>bo zzyz?uURy+K7POrNZN@xYb6*SguY3luO@FtRPBxik!1it<6N-j~R>C|XN)L8f2g?Hh7IJi8%d);4 zDOgY^g|LrGs16W9~ft_yC bO6BIa1|J;2ClCfq0PE;8O+2{U?>GJrG~b|+ diff --git a/000_image_stack_ram_based_reward/logs/PPO_2/events.out.tfevents.1680177234.DESKTOP-9E17TO7.2364.0 b/000_image_stack_ram_based_reward/logs/PPO_2/events.out.tfevents.1680177234.DESKTOP-9E17TO7.2364.0 deleted file mode 100644 index 9b2266427cb11e9e7840936077556faa73a332f6..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 2971 zcma*neM}p57zgln6168}1uQQ`VThJeNqK1qgi)HVWuwK7t(#LayUVQ{^zeFjxwec_ z<3>--vjhyv2L=y1v3?vO%>YD$OiZF&@={EF5Qa1ZZxvt&$^WE6vaVZ-~FlZBt*<1uo z$u<-!b?qDWcjWVZBiDvkLVcM?IwA#*H&ozFZ^+$>4)+3^}(a-iWqhEP+ureC`{xoZVsh zZm*CTbuZ)-3pynX}YfsIBhFNx^XV{dLYF- zu(O4QR?Pc%NlpmqkxkK&?y#c9Y^BsEIJtnd{?deh+xOnv5K^!+9BH?qWpmv$gcN){ zBGO~4C-tj+;;h)?aR-HwdWUFTWy8ULpi6>%z$HV;`$!LzeQ^##3dW)#Rqk0a`ews6 zJA@Pr#z8v#^759evnz!xx)^Ec)B_p_DOeni^xQKE=Hi}-zaXSwARbbyS6}^Q;GKYw z(*j6GR3Dparge5`#i9K5c_E||p6EzLq6VW@yzZpnDcBi~^i{)Y zytWuZ3O*hYsl7?2ySrD7#U3vb(%l}F?pEs8rO+k8zUW9Fx;nNCLJG#BAq~El>Lb$q z7a^ozFgDWBP135H11HZ5S#&Ydi@mKK5K^!>9O(-)?WRAId^aGZU?3jS%V#v&jRj+j zkkbN48!IUDzF(wcPxJr5U(5QuP7?T|JwJrBd!IPE(vn1*vAxH}!XT4o zh9`_p)e!7G43U8*jb`=K^H2Gz`hLfX`NlV9zCq!}*jR5~>Cz63=iL#s>|(8!=j3Of z;H%q`wg17@;ar0y?p14&P4-eg@nq)4DL4_&>$7j`tNJSn?+H3E05*78VZMHQdD;JA Cez;oz diff --git a/000_image_stack_ram_based_reward/logs/PPO_20/events.out.tfevents.1680184256.DESKTOP-9E17TO7.32692.2 b/000_image_stack_ram_based_reward/logs/PPO_20/events.out.tfevents.1680184256.DESKTOP-9E17TO7.32692.2 deleted file mode 100644 index 5a2dda33b1171e2141f8ae5b53fd76581a88daa3..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 43434 zcma*wd0dR^`v>qz3njFOQkD|3hO9L`Gt(GbDN90VIfO_h*|#KFvnE2eNZC20Oqdy4 zCuGUKZ^ z)<03fq2cWmQ$xa|T{{kJXVNA*Bz$s2)ISlyQKQ>Uo-%P_aMX-;)1pG7L!#P+{BKp@ zn9#70z(4;dqP=5Oa77xd^ssZBoyqPW1l<<{TUu z85J=-a6*{XY^xHtW-dwpac}QWYE)QgWZ;;n;8D?`5#d(bw-2E#W>Fz6{?=1IJ=_!O z*_hNfF(Z;u!Qo>=tl}m(Qu79lUEK0-tZQW;ZqwGp#>C=J?DzGGiin&M7#1;kven8j z2I{f~2L8@}gA+$K><{(qO&Xh6{|!!$4Ex<@$mqbS!BL^X;iE#VL~GKO)e397328Je zBseNOG<1vYc9(g+9bN)0rh7H~qD7k2j05QtV}*V-(IUY~0_jW5baDJxKuXr6A&tqGf7#Gt zGax0GGa?Q6WGSvpE<~hcO8c+x&p;7ra&c>_&4rK7FiA2=Oj4Wtf20vZW9NOh>va{<5U9S>4rulnn48 z^=#siBbmJEKOv(fknReLlwF)&{vBGJw4eH_MVi}z8>xB0`9i@-K)N(pWdKOYnslV+ zd9aN*1Og4V=3~x?gFD#JhT@{x>i-!G!OSDLTxU(Z2Txg)^Jf-ng!O1G5d-ud>?l$dc3P{PC zbfhYI-R4)~04ceg5$VhW*W89R+e2}0j|r)NLAm>xm%~QEB*}X0NE5ccSOZAO7#q?_ zn+(*k!KwLxlnins4GQ#eADZy(rI1E-ky_WjmIg@4!gQopI=qu+zP-E-kdgsDq=oTw zl+pIBKMENwfwVZ?U-mKO<3MO}W72|eTBQ5>vLh8a>M6XUYa|FxRv{IM$}|y|N=^e( zvL+3w=%n0SzwKv0N-k$a>TB@C?U&8h$K2avLOL@tf>PKn$%ILg_1KYmC(FkHQZmMd zH1GFG8Zq-0?_(pn=6C91jG1_4qsz=!mL zexfpURYs|h(Gp0H`&XCkEohSsEgp2*`(2ClksmwKjiJVhxa1B=f|CSNy)(6r*ggfM zWK9~d3u4CZsd;YE!G6tM`LRlJ(e;E^KC63P{Nq z8`3YoPg1k97Xtt(8RSOl*nSLkz2M<`A&u%H{d%wVGeAlf) zzZP}}q-0GRQc;$C;jX}{eo zO-@_}q-2Z@Y2kVU^`2fajQ}Yb zI|EWOz=w2Mu3kOYtoS(mj{*3^8}>iaz>=hG_}76JS+hz8Dm4bF3CXsG$!x{ASHv`NQ2z3xfd=dwG+~)F48NbO=N(SEKEmw|3Av( zYU@XX0Vx^aL;9=EYo(E2qLq-*5=gJvsbzh~gypsV`}}OY?HNzwlC6&ATBK=<^|+Nb zz5T^PcodjMw^C`E{H@yZeMWz*s_V2`T2=ux2fJj1TBl`w@rv>+wqq_D&)PSdn*4#q{x|4#J~VU_~(*8dF)Dr%nF$s|5>HX<%bA z<##*PX#rqiJtNpY%2#fI|4EE_cE|*_tc?#fZ~a*W3l-VH_WCCtp9O;)8(3AGfqL~d zi|POtlH6dUetn@%T??rY)T}O8tK||S01Kt*VErfGmVD^&p&Yb)oXLS=0{z z3y(kym;ifhsX3kg23eO1Sm z%WrL)3}E3AhyfE|m6NPxxg&${mO%V{W~CNv&VC-SPUpUd!-P1a0CuQjgX#blqPk$G zrJZUHU|~HYSXVg8HV0Ty4NFBzt$$;LN2|bYOx~n9 zHTSDMfQ70wurbHvwZ0#H1Ylu3BiMJx8jBBIJT{MKhfH7(yL6^LyDoKsc|t{Eo;0v; z_ja-eu#jT|J8*=7dfB*P4FN19xxwZ|m`hs9vmyjFs|&W(yktKB3#I8`Uz{8!mAC7K z_pp%Q18ctUmU7{)kePx8On|MwzK^W#$B{3f%`oS^dRnmC&hvnc%(#ue(r`ur?Ajme z&jMJ8>Vl0ZxS|JOVLc<*(``D7rxw&$!P6WQ*r2t8sVm_X&0(HUksWN}?%V|c7IJK0 z?eq=QlS3y{02Y$mV554PNZuSsHxSgUF4&^aUzY(`C`|`D&nZHZzdo=xoUoAK1N)(8 zmeTa-vUouQCcuhD)Ryhvm@*35Y@L6qnilN!>l|RC?dvIAn!Y_FJX!^|XZ-|CWcwa6 z01H)VV1M7k?(BKa6~MxJMzFW@KDd>io6omHCa`y#HK5jP=~)2tgo^B7v!W+W1F(=| z1AE%lKwWcg%pw2_Np7&4hkvFVmZkezXC=!g@xqg@>NHc~9QAoo9zkVC{;{sV+4Ks$rf`ksWNudGqmIYmj3DTc?kK zdZz!eEC35hZm{F-_)d1g#;hidAVLWiGiNIVZiVR z#DEE~o2a!?{}0K&a7}mlI91nz-56Jm{gtkFI~ypbnveS;JX!_T?Qn$VX`A~602Zp! z!2W)g;NMgFX8dF6jcE|*FwMlC#XGbF$%o8dS^Q1jXuxq#I7=VQw z8`%3Zf4>QCS1U0LB!q#?|rvg|gO$R%>UaWLcr?XoDEF}2A z2K?upGa=Sh*nkPJPlpD``aJP2f;MNqA6P>R_R=aIuq$?)@DLsauw^G}jRvq#l?GOH zOy0Hbzg_?q)-!@N?w0G;cFV>vo*goQHB^($XsLM}Z;t30R&J*_A{&i~rEJW#G-YlJ}*B`3@ER?2$-CX)!^18xk zFMx#vAK1Jlopa7eu3ix|U;=DNxSOo_?d=0 zULF7z5`190c30$7OYr?BXut&6dbXEjA7?b{2yGr}QdCn5_SrEWu!pX>w-X)(u({X1 z&IYhhl@9h_xo^K`K>!xkGlIP^y}sDmxYszI9WsI4x}qy}zxRMNm?ulthV1Gelyz#|4sfNdLKF1zV7)DPNR|FcUiE!ad27g&Egg|DeqYvIu93y?@Is{)-!_581~w2lhO!(Erb|xTc`cGUiF0mC$=@B0ldut)S+uzG?$tA;AY$?`FfCqp=r03mPy1_T<4m(z7EM;GK_MWn677*z@@u zU_I|QP%OB3Wdux!Gg<}q+0z6~k;T3*02ZQju!rQuUw@SYSXj>p_GIUWZgGd(ZsFM> z(+T@r6HL|W()=UL6DqQUwV9Ef4`3n32DZ~#ef2VV);<6WNp7&O=InI$Juhu2s99aG z&En3v0az$a2fJ?{CHrjc_Z`4Of)A`?Gec$emy8aA226mRk!9)exOcq|(B=!@)H+(Q zrS~|%M)}rLEU-D;TzIq!?A|@&H2UE+Zv$AUstfi(pYU7&3+oxdF34#vPAz+UnrDYh zV4YRXsa`J^wS;*>MRu^E2j3R~Sje$~UA0wT-QH`*EdUEiZm==-MiTLIvl2ng>Vmx? z4K)C;P?`>QeR2=!UF%2%fQ1AfSTC18Ig8tM*d%Dc1lSx;Pnm(-`a85aEBBO{7VMrP z4zOYA^%TSE*;B%!RbZVCF3{WxYOx8xLRDR`m6}fY_Ci?C2-fmlUGXdzqqjUeWCELP z(TB1-@*Zyqpdvfi$Ib(l02Xp=U^jf$R~uZ2Eu8fGhPQ-6*EuvC8Hs?c3+oxdZf#{LUZr;R z=Gh?=*r{Q@)RLyY*)UJ2$PQM%WwjT8g&Z5$b%FZo%0tcG16W9MgN>}YgxY^=F@B~C z@|<8B-k$vnz(SM`*6DdGX+f4t5P*dQA6T;pvz*a(nO=ehOn}XesVnOfw(TWc(=(l# z)YXDjE$0Ahy1+`&{Gj!2;n6CvTZ*P=9xk{y6~IDO8rYaa@()%kk^wBNX9PPfu&cOj zNt|HKANM){^Ms1*V4sco^%}rJjt#6`H+^+h(*qI!3rTLU#a{Z7ISWPw z32IjNgthp(p&@{U(sZy*o{6L``9C)TSV-`J&G%}QBcGD7PSAh}ur;P1lFt6LZY8wY zNfu?L1^ame4_JTw^Gk$B0qpkn2KN9gRHcJGD1Y%Kp#;FfdPcA@i`$CRT4&%5I>d-W z2cOomOCC!}TvyzKc|w#O><8}&+W{=(*ud78>Z^xciW&!CA;}H)gK;{w+p`9qACM=S z)dicclH;=k5T%3dA0I0zZ1@wOC4dAU*m)YCoYl$A>;(;&0GpU!TP9f=v=!8SJb1F6 z7VOSl9AHmm)l=vd+{_dntpdBe-E2*jK zAJ66Z^W#JptZLzfyKurnX*yVG-?q}EQC(}n2@456up;V((&g5mL4pQMfb~k$lRf;= z5nrxS?yF&~1$*l-2UzdGx{ApWb3ej_IHOfyb3ImQ&c&{*3t%Bi2YWz1L{(A*CoHUI z1bZa6f%s+TydOL}WV$72GRlui8K)cx^Ms1*U>`{);V)f~V*@+CrM|lRiSsJ}EF`(X z7H^$Fxix)0Ur@8UVDkfd&jGMdnhy5srD3ve9X$I3SV-`Jecj@gvVV?)LePK-u<`L7 zWIicx@N;_I>kqckf?a%y1MFZQ3&nTaPiJ95oY5+p*3`#cykM`h70(Wtz&`Nwr&7ae+=Y2UMRu?iPF=-t!a|M>Z0@sa>h#lk_--vo za)TXbJcGLY=!=V>W_7{Fm5sq)x}Y>2?Ct+9NQQcSivqBa-~($MR4=Fez5f(J117+F zpELEiyDJdi{F1a~Qv)s76L}n9H})}C6cmf`Q?s1WDzIltVl^tibuMtiLX-wpv|oO^ z)m&2m3+oxd_WL|Ryt2p?KNA5l)?0!)*$I^DXXO@{Cq&u7ngu(~2e6Q11M3s4r(X8m zcLSWTkmLsIS? zC+`q6U;?bC?<-krSNrww?{Y)Od|NHpcei-Ju6Y|;OL!E(&L4I?7r;VQ8rYb9@&jwu z{{*nGo)K(tmWTLNMYnRE9WtG;7tI2xMMrA=1M`H6>|kGS@Gu3ikYfWIFi)h;y{>lZbpcKjk2v9o=HdpylCf!*RbhkD*WX)4SUDzbx(Q5vQJSje$~y?aJa9X;Lf z6@Y~#H(1rh8WKa#T^9s3s|)r=jVWaS7E05>&VBhyvNm`?B!GnkAJ|hhy5(%LQJxhv zU;=EdlhtIVr#s+t>pNYk##*pfKXQO|wzp7JSPsUw2XRKLz((1v)BG%Z6aXhIM0LU1 zcWl@Rz`}Y)u$u~f#XT|=`1v1*5kDpIS%NNwGbvT{N6t-hCXvLY`<=7wk0Kgkt~}qI9s+Yq?9;dOE%Yu#n&b+drUv z&YaWT@s*i3eF=EPfC;b$)dtJDweWZXZCVF~G|_^ME$0Dyas2qZ!lM8-zsI|E02Zp! zz{aG@SGFws24G=5BiN+S=Hh_aML)$n$-pCFhElQV4*Y}Y+vK~(iQEUJ_A@t@PW0n zROIv*8RiNaFacKO^;lMTSYrZhZXP(zUJLf)$?MjaY$8xHe?C_C7; z&7Q4<6Bcr8VAnMesfT=6G6=vzk{hf;(n@Ofzg_S*Ovn?>>Vh5HaS^^-3!-$elN<&} z>y4gW8^A(>4{Sgq|Ll?ZUuFv$Fah@SKR;wnP7CqtHoK)9Y^nvjVLK1lhc09816a-| zfSsC_`WQ}Fh|<8uWXPof8}OxBSkDNy?eGZkeN$U~o*gosu)FRpqdqMAw;#+CDzbxp zqXIPzT613Wuq0(-M)BPH&zBn0LO z71_b2O18cOu#jT|`{`DtDk!I76@Y~#H`v)LTqXae?(!7WtnLZh`^S-*02WHq!LCo( zB%NBc&k#;nNbrFz$S+9@jp4VVDi>wv#(yOG-`Xwx-^YOV!ap3MO^v!{ik)8ulz zL*$HBf%T}dRWtu}=n4P}Q5x9azjP&;$?%Uhz{(Eace0o?lh2`ceJfV*m?DZm>&7=u4s}PsF1K@|-8^PEkQQfQ2X> z?9|lul6gf%M*%D(_`p7EeolG1leLea0TWlwlJoZ~63+t_D6&kmWuwmQF%>NTO$SePeN zWC#0R*6|R4g&Z5$BE-jVD47iEEm!vFkZ>0sh<}nZ0 z=jk=8fpyL(fL;6Gt1X=wH?V7S=O@-Scg%_}^Wp@fT-^5!VpG z-e0(sl3&?A3+4$?cCcRuTH#m5Lyiq>%kSl?ZXYcy04yZA!JfR;QsR-@Jc;K@{<;6r z1?%Bscm}{iX*$@qj{T*fBLb8F77~15ThENliE5(QD`>z3*hk7{viO>ao(iq zeR+1sbPs!7w1v8PB-;q)2^HDF)^X{#4^CLfv4MSmw?sAR@ou~&fFw8A8N(eU_qy#9 z3u;yu?5o*h`U6-fO$VE_^R}e=K2!YEEF}2AzFMYGwo7?=N6>%?uK1V*m?L8dy=9{6BHf5;$RDJtNpn zbLWb?nmz3W*AQZ?C#OwnhjVDU?Il_Hg>{KRku4+7s3e(Np7$e zZ<(LYE~DlWHz-Nz(Q#{*yvmPrS}_+ZVV?ZB>2GA9^{k0i6CSMs+jYZE zO|5z>P61e`stZ;z{#O}*h4qYJ7oMFb7L|M9^RN(OJz=HR8>owm%kT~H5M>AJc(}S7 zfQ1|z*fZD4RX3b=;D-<)$qlys8a+wNP1#bO%fWUJTRQPsYXA$S>0p(6w|W?4?#TqO zkl+Iwe|W#r_fy6p0DCxqfJY3N0IOV8B6HY28sGNYqkDV@E!a~TJYbg(v787K;*0`V z*^m2U04zjlV1GYLuxtF9SO5#_8Nn{Tm@IzeQx?awL#7kf(j0sMu z+DOf|?7aYBA;AZB?eay+Ut#Ygf(A^2Rc@9kx0vC3d?tQK>Zk=%IS6WCS*_fvhky>o$qhE`zPrTnZE}X7W_7_v_DlZjq#U!3Wmo#8;(J?0}ns226m>nQJUN-(elL8FD?_MGJO^h6AihV*u8s>Xtv*XI|yJQstb1MK}mf83+oxd4%%ztUh2`X4O~Nr5r+;wt@Y-}CF*&E z{w0_vMA^Z%KD6W}fQ1|z*r~05s#e^JI16AQ$qm-pxGps$_(n59&FX@kTE{3Cz(Q#{ z*uw*=NyTs6Z2>GK_`v#&*wKCA!$b!`117-6**SYWe*7g7+AMl}r;`@!jeHKUm#Nwc zznO)7gh#8uj!E00@mV*5&B8ra{jbk#0s5C&jjJtJ6uhm+z>pR3j5*&)*joAfS+ zn%H4Gez_i0WCy#iQxSe@7IJK051;+2+R=yh5gABwgUu}-EGd)paud|7F4$X@4NL$m zl%|6{Wp`1M`t+U&fQ1Af*nnTf%6$bV@s$~P1Y*Dh*nlXRY|+9I_^qNHpV#Q31si{# z2kafo3(H|boKXP#w0Q7701HuFuuEFF9s#hho)PSR>vZuHc|up79WsGka_kUgW*m=S zw+R)AdD8A->;3Y70Vgcv*uYMoU#7aV%yl@Nu#n^i8x*#JI(@ed{uL_76F*LL!46H4 zT?ViarGph+GnW-VIOhalA;AaMy2}!!#qyE(+BZA`F<=7h+XkIH&P+LL3)i&s!4_S$ zV6%#Nz-}JX(O!5I!0wVLB>)zx>VkD%?|Bly!g@xqCl&j|U9;6!cy`DHR?<*O)w%hz z5`JPqMPi;bu$uhN_|h!o*uYi{`k`{DxbZK5g(NpvqicSWWB1?SE9H>q1Z#KkP7r{F zC>?BabgJY-e0d^(g#;hivnvlNJ=VQJuMRt6h(* z;2J`V6|CIvICV8OIRU^zl$a+C?5i)4YXB_d*uZ+neNj~m&pixaA;}GP=Faw#ZJ}TA z1N)FCn$-n6tgQJ001Ht%*oyz!$r`o_tOj5q!3VayP7S5crt*z~226mRV45jCR2rQJ z*VH*Z-c<`We>o4>6Lovzvjj<598m!4xhiQDfQ2Xx?C!~=KH!HCA<7O`v$?@701G)bun)bys#5#8)d8@OVi!aooWeSAxa0kyn(Ik*ogEA02UH_VEv};SDtWrCSpLE!dc34zTW5>M6!6?7P8)IHOfyuY5_O+jUh6r|>Zz{DraTdOr2%^M1X(#NVo?{aMEace0dIXlJti0gbOD2gsRsi~s-t diff --git a/000_image_stack_ram_based_reward/logs/PPO_21/events.out.tfevents.1680184590.DESKTOP-9E17TO7.32692.3 b/000_image_stack_ram_based_reward/logs/PPO_21/events.out.tfevents.1680184590.DESKTOP-9E17TO7.32692.3 deleted file mode 100644 index 55c5befc1aac6cabb2a60c51003cc03fcda7f360..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 18129 zcma*ud0fo-9|!PB6Pm2VMwcTZXXVIZGSf7TkRwNKMlvNjr%UbrlB=*q(Ym&Fb5vq$ zv63}4naO=`He$28C^ze<5b9?~kJ<0*JKt;n+{foNuh08E&!#cPSl;LVnl_KkGF7V5 zqzcoU5}Pj;DgA;%on$eJ(5O*EraB1*Mkzug!<37{{FIBGBBMh>{FHG{vC5z*h0;m! z?Gh^wF0*C-K5mEFuKn!}yrOpPJAoryk=RMPBJaFZq7LZYr)8qZ z$@h4s#N$?i&I0qOf1f00zwmHn*mC)@V9T8oBZLj-DngjA_c`Ss9271OQ2O~t1%-uL zy4DLs2aK~D99#NScMgq#K5Ic2K?g!o=@%NPungSzVf2cjlg{;PiG9^9$7|XOtOXrE z$37WRhK0w;gTo>tEnVA~Xx>!TU2$#+hRpBk1AX>_?gFcp;PUX`Pjf03%VYeML4KkB z3QOKk;!)eHn_ajJ8m#bBh6aTO%9Vam3d`CZkt5cA>3P7urP%1}rwvftNnjxmd@k1A zR5G<*bm5$>&)}9o*6P)dAka%-FR=L>2oDPm@{f}TD*YA*{re-Kdw}$^1FDr}U$x`1 z+8Dp!XvODP`zSk!?<5B+7%|zy-&=?D=h^f~ee0cNOIP#KI4226uWI8Tt!x0K#7+{@ z#G}$-t;;+BDe*WZQd>c?(B_Cw6!Y~yFBFm5^f42aPL4eVn5vvS@ipmB2Q&gwVvrf>!98`QX>v1r7?c>-y%M%iGeBD2$L4E5N=%ZG)?J<}zA&X$ z21tnkHl#W8E~_M`6CT29i4Qog;lXOTkV(F0%-P2n(J!(@p z=cFF#rHfm&r(?U80#afp2`R5oI;)~E0FV-oQzBh)`%mGqSrto|uSbRS**7D#v z*d(!!ut^>7|6WPUokl(Yq|<-+ZN|RBAj4QVw@3a zmuo&R0Vy#_M(UW*=rMCq@+m+{46q>;rBtd;OAjr9)e;|ouv!ArK^JaHq-M4&2eiC` zC)t*Jo4$TjI7Nr_U4{|8(ok=ES=Nz)9PUv)Qywo@EA;%qzDG-Izi0VA*h+GmxKEm% z6{v#Y;Fgq7{ZsRVjVV@hS#C%rbz6hC=+_&K*?n7X*c{$@Jl>G7PZHH3dyhw_y!`@5|CWO?tLeFSi)|5v$2u-^ZR1 zcd>JB9MY0-u%7W06Kq~*-&>?Icb(I~X~6`r8H1Kea^f;w;W>4jv3a@i$)qdZr=guB2^XkAtD+w%bpEUSQbUy$K=PAK@$}@$H4wGG2Zb$|8 z)G(3Aaox&f*e5j7gLOXnfDd3HM+f#v31749mf2kZ3rS|MX+{3(uG!8XI1OtE*0joO zD}aS+GT6o%4|mah*%<%}2{y3J2Og_-tPAz!v|s|*yz8?i$5Vd!AB-8Y$Zw_&Z246N zumSCR$f`HY^5P!VgB?1wPJ29Lh!DU+t0CB;>kGF5SU67!HsM*G@WY`InJhP?0$Uy6 zD@xADvx9v?BR$w&15)+@Sjf?VRh9BJO~;ES09Z&egLPluPo3U<$74>z8iEae^vDRn zLNyue>VfUt?@sw@A%KMh8(14rzN$^Y<%OIUOaNQ`WsJn;O~-r~GyUe~IXbZWo-=^; z&9auw_utTudsGjW$2+2(R&`nqV4;-+HZez<;3V%4VBtI^So6_M!gCj{w`I8@71))+ zI8n;PF}1KyXru>wx}fz~01G)fur5dWnj>{%69FtFnZahyl$Jg?=dzB|u!dkKn4Lcf zV4<1}HhS7oaT}vwwgOm4uz`(S{(v&)0!XO=(5{ z9(F^iwd`JiMJw)6Jy^$>Ozpei{jLBOTFGGdNUwN`UjtY;PYE{1q*%Bnx$|+B8&ZK) zjPe&bWh!D|pU_ATR`G3qF@S{}9a!xrunA!g*8o^ZGJ_4D8>@D`e`5xxVGY4{Hh!}W zz(O?{tU5Jb98vH^Gk}Ez8(6`f?W)x|f7WwaFahkb2j5A)Zt86gWB$@~W}y!3t9%Bq z|2(&n)t&wE3HPWTY;5cvZI#l09Ds#Z5?J0Isl~iv{A>=+Q-aNRJtR!36zpTUAr;uV zRtrR7n;Isy+)rrd;m@U2%3*&U*c)dU z!16q-WqYHhwSf&WM)hEM3%6^RwX@{|Scn>eO}I4eCcMJJc}lQFE~Ub5+m=aLZb$`o z)ddfctx??u*e5j7gZ(z(NfLmC935Es3cjYg*5f9Cg(NfB6S*DKtxL*{ISp$F_Ts%s zP5>6F$zTWaX1b@@Pgo0JA;AWAVZ#HJrrVS)u;9c@0zATk31BNdf0U&BwND6Rx{Ti* zpaWY{%K*09q@J>P=kOuiqk6E{Dh_JbkE|I1V4>9z?1mK%S^x{@DZySyJ}bPIX==-I zLn^R6oEC|M;yVSfPiQ3Ulk~CHx;eEb02Xp|V3WQ0nx2sptN|<}nZXXblcGKqQa_Q? zu!dmUwY_@|z(O?{Y*p1?;>Y&i_yAZ)uz@``>5Gz)hxc1>S}+0Zw4Gffb91w6U`(mq zs30BKU8{}h-^12)u$PT1etDaFR1dahM1i(deW&377FtPQ6ZcAe=A5qquyCFd?C!jO zgwrh^XjpDY1$M70RCH-V>{Qq%G}428=-Qzfz(S4=?5N3n&5QAu?*LdxGJ_58RaPpT zJ7@x@VGY41d98W{V4<1}HgeT-QQiKZmlI4a}V2}1cEb0<<${Y3xjr3q^a{oL4U?E2bwu3ca(~#O&4`3n543>A~ zxNy+zyZt#0YY6tD{AF(d3)N(>SAP|_=jYxJ2C$G|1Do+OR5-oA-8oJRCV<^`{U^`w zE<|;QF{5^*hw8vSQ8R$OG{Q+HFnMvFdsGiLAYh}$I$qiyz(Ok-Y_2qQr&&0Fh4YkP z7r*N5cKJqIe7^%R!e3S57YFPVm7<`?WqGhqh|+`YE}#1YfQ1|#Sj}5w&CgAZSpXK2 z%wS*pu0LU?txaQjIzIn&8iMtGmu?GSp_&Z#gQK7OZ@d>q02UH#V3SPe2oL{rw-^>& znNNU6STF(Xx+|~Ti+;be7sjlf?H!>5d$pPY?4$90Wh)jJ<1bvss2(hjcUCj2f+qs7 z5G8?4%#~)zg6jb+oTmhvzR%Xpp;HBqWjLx=*gw9_6y?^4#IR3jBj4S{P zIXbW#KD{M)J=xV9z(SH4?85X?wQ;{LPMn4{1iSpit%Cp-s>xty)X#7i#?(y#u#jK_ zTb5U=+OvOvAEyNqz`EY=EQwrj5kE}*ez|d!4s1~)16W_PzOuq2?U%xa7^8ZyzP{$# z7+Fm_01HtPSYDnqFni)I01M|S!4@UVa0`yqykxl{71-j@M?|L{-D?H=ghqO>b9c`x z1+b8#1KXh^Uo-z~@Kpc{NoKG;KDJXQlty`T8rBeO*uEtmi{dh->@!Ns@U!kCtsXJT|MfQ42=uyz&s2LUXcrv%%7%wV_iZkbbAZb$_-r|6JqyLa!6uuo{D2m5xl z7{BZeIXbXCju>n1x&+AqEF_u1_Vw;m)-%+05~pDe!B)i>-2<>tO$OWcv9-9#>a8z; zg#;Vezh~c7{r>&rzd0?K0Cw~(3yID0z$GxISpR0CIF-pIkB4bTf_I4`3n53^vidz9j9;(?U+e8iFl<|2h}ILNyue{*h0`fm0jp z0W2igz}~uk`}oGR?kSuWOaNP6^@n8B*9CPj=E0CQi8`?7UNV6FC#IL|UCn~E+@pH1 zC92ih_}AZ90$6AzgUylp%v<*yUSZ)pCD@uuKevZBEC;aMkP56_!Yz^I&2JiEpU_AT z*5t>vn*l83=)jInGuHG?-#!GuLXsJ*&-%IQtWlM3I1OtEHvDq;Y5)t>WU$YR-ipVK z8}S_igplL`HM*dfCm zWZ(SaV9ht1!2&>NSBZH>3jF(V<#o z_x_p_>=POZ`y_ozaMv~UDS(9>9a!51#v1eZ?;QawB$>hX`1G$0dh`F%avIhUY(VFV zo&XlA$zaP*^>)uF?f)9ULV^u!viE%9@i%<@wiY}BVZj8j%a4o`^rU6(uPYJg6L$sUA?YH+? zZb$`osqrn5IJ#~bfQ3fFK1pCr%_GVIEad3GN(IK6-(rS62C$H120JW1ux$UZqc=DW zYY4V}x&0Ra7OKf$AAZOXpGlIxLV4;-+_S3huB&L$t02a!?slX<=G>C5JcP@o}LL)ucNcj%@Czz0<0~>$XNYj-ceI39;k{N6we`D$F$5o3t z4QmLt&*-3E0W4IL!A>iPabMMETdLW0Y9xS#^ORsMqIS7i zw~zad<%U#Xm;Tlun%4K#F4!kD(u1vS+Js-=h8!K(-#;2@&f7f0kF_Al47TdYNAH@1&;m(O3>4!}Z!4eXf-N@3H?NiR7qm;g4*agJn)$qD>y z>PlzZG#yxNQfvD6usf4&WT#&a$6vUNQ9am87c;erBvBlIg(w;9E@_;)>R2~m2m(aqXWCM#7L8@wl;=WSV%I1 zJ(jygtteg}1YjXg7}gN1XY;^A02ZQTuwJ{A;yD91n*mrzuz@vtb7-U_j`U>>cm%?N z31F2=VkONH&iJMLiVst_=)mUfWdQpyy|b*rC2bLGh%u@MTO6`N`-{5wQ2+~35?J0Y zX~@l=qyQGqQ-b|tXSSPiXh-~d4#Wu0A%2%2DCwi9dPMe502ZQzeUje8DqO7E09eS; zft{9Nq>1=G;%5L0NoKJ7PVQE>AO6&X<>~nR>% zU5Q20siD4pfjy+*vcNDG$1yz&x`oLC=LUsN4e|}0-ec~(IdgnN7xtJR>K7&p?IHVb zmG=z40Gapi|L6IrSI%~Ie>ZjQ`ie&8z9BpQ`@7Ar8QEDHSQxYn4GIVdnipm-3-%6> z1$xhs`39N@1QqVn+HL5_I~gjQUzd!G%kQ)&@r89=&Cx^M&7h`{fuVtZnBN?k{fywb zzY3YV>-yK|LZQ@?4R@-yxT`(e79Y5a=U3(NPX2$3f}Qy?$@YD)MRHBb79&gCS`OOx zZ>PGB=8k+OXhdFaX3)yOFzmkv$=)|OI5cR1w|{_1rt2Z$-fd_7*|+yQH7&p|*n38( z@3b(#pg@zCU;7cI4H7=u*3~=n(43SE^$naUGx=;0L73TITim5C*0jH^UQLiD;-oVDd;&&i8D8O&pLhqTOzSI5wdrGMP zK#6FEd`_AfO)dtvBKvilH}RRnb6|9>4k}Eq-DLCk$QSoxi5Si zt^>&t^O%zwq$x*+ zBi4`H`vfLQu1A`rI{AO3-H&he0;J>^6H@a-ddgu&Zw~-ca*!RVgR8Zu?dRGXd>Yk8 zy1BH<8jz9;Q;}X8GhO^WBSH*F$pJ2;qjH7i>w0BvD{(@5xJE6s|^%m_` zBb5(eM;bMwO9AgBAiZ_T*b9)7Yf_L3a@}UXIpG3G$;)Yx-rCev_|o2JA^Y~|kgoh% zBdQu#aULc~uE&hDL++$SfRr3#LMr-GPub|Tbu=I)2icKEn!Dt=oF)F?)2KGmv!`~n z1El1_RHSa}8o17{ZhjDuk^@{wW9;+JxR@2`@)<1&X>HF!aYnqL3R>*gw_B1L>6-D( zNCiy{rIWkOwCA1FAQePfu0FxxwV@CRCiQ*a{CC8YM4tLg5uDc}j2BhR5J5oWmM4oTZw?3anwUOQ( z`>7cqB^Rb5oqv7|VXsrt5|EMuTu6zRacA1ct@w-2Xh}%lW$8-l$24jUEf(*7maIm4 z&yN}Dj8i7ksv9Arl- z=;kb(ePC7!pGLKjHt^2x2uR6=sYp#z4vB3`R`mv?-3UbzS&GQN*{6k9jq#t@Tsidq>*Um0n;Zs>ae( zuBz!yuE~LebsXyw9n8JnVS>x+{42BN=gv0@ij-1PpHTY)Svtf*Y!ax*o2NZ{b3Y32b*+J!L!VlllM_lI&nR$G;Xi4PLc}SFe+xExbgh~9*c>op?TwqtW9WMXy@@fIE0h7QE__vwFILEg$w0Yt7)T3&!nKxO$ z+Rtt(z1UbK;~&+4%_&V*&6xBs5x_!K3Rppg+kjW6h67kwPYbr-;|igD@{aZ#JEQ~K zYQ6!{ckR79Fi)t+40ekAZeKiM$@63advTMF@~?c8762A1vV$Eo?7FDj;LK89&1!?K z$ZzEbV4*Y>tb0z7>(K*+qW~-( z0c`cvq&@%^s%nFkopjO%um`V_c1a7?Bf3B+sF|7#JA@eNy-56wRngy=Nb0|`AIuY? z%wX3!4Nw4B$T5NSU9F>BG+3MqU?Is4R?yb@^xr|YOL#S_4fd%+!XN+(rKw;CRL&sU zwE55*z(Rrx?AY(Y@~it-dGfjG z{G%GMw&8nJv%bt;31FeBHrT53Z(IN@tfvKgKQ2yq>DVqjVIjr{_Rd~?Vr%mU_ApO~ zvVfg5xdVWO923|@Pjr-?*DVk%B-z1UAL=iuJHR3>YTd^Gtq%1!oQfu#jT{`+ACwa_zZ5Ih?SNWCvUPqEIA^n22v{L7w#N)COzqy)YfX zLX-;j55alYo5_ip02UHlV2d*BExUBN9Kb@332ee_9p&l-nYTP$YlfD z*Fx%X^ldCmh&8GKD=4|4I$=?G7{EeQ8|=YOT|xjXtfvLLXYUfBzV-Zgjvdm0y?m!T zk#Q)_3FZkEN%N%KC|H(dF%iH*jtT6$p*qTn9ucJg7Lx2>9Zs$h6&}7^pI5WmU`sd8 zUJYQOG!^XC+b@W9bJE@bSV(YzofzRQmmcn&$!owQutOy4Bq`?#A3~c`q9d}@U>{y( z0c#j!CLJIQ!3nWOHDJp>zE>r0IdKKRLR1@Uc$n{501NAB!EW3bBfNH`j}u38bYPtm z8WR)rycWPbp&~QbdlT=T0kDu`0y`>Hpj>=&iYtJHBs*Be{sY3U!M8GbHLDF)Z}+g< z02WG9!Dbb?x)PW4h5}efaDjdI-cmkycA^`v0h7Q^eKA_%cgdqUwE3~0)oC@@qa`e0 zQ{Greg(1=H_(wHhEiXJ(iR|L=qgkj*0V_y%>;CFC-WLh$X~9m2o-A|-OHJh1AsyIJ zKlO+q#j7e|o=}k)Y}SJ85&#Q1Ca^uV%Hu`tQtL z3t*u%73|`&rmlgGrY`_2B)Gtu9UUfrzlMl~0goI;f=3!K3G4z(z5X2sHOCiSNlPy0 zsKHj2vw-bvXeO;%;*1kwjcUNI`t(NiNVi!KoUjn3fQ>xicD82j1vp`0JuTRgJ+}#8 z*gu{Hk0HcJuS4){t%2{XiRV)eM8P~EN}4C-lHmPn**E|TIVP}e1`CvLypIL|SV*#i zojzg(v3yz4dtS|IgB`fOaeV*_rKw;$h^$YjmHQ0ZmbeZ4Q`VZ{6?SVI8Lab2$d%$pl9)N`?1+3tN+di9#e*jom zPYZUMI96yMomj@PL%I|8qJ0Bm-TK$~E&)_z2CKL~{XT$&923|pqXo+Crh|q8SV*#i z4L;&1YL#s>kXN(XV3);=4+XGLnhMq{D8_Z*M>l@}3kfc;AD1M^=R|Z-0$BJ9qydw_ z8ojocs9ZOngf@rzw9Qk4-M*Ov?BpfeU-6Fu*k!t@czYpK)dstEm1+@yh4r*x`F;F@YTuSEHC1*`O7Gg(N#zhd&%e z-uIoHc{QsI_P~aeNdOi~Q^5}KPj)Tc5wi`zLV^qI=j4rY;o#m5yar4Hd*JIGaijKL zqo7TX5k+U!U`r3MfZZXpm9|W{gSQ8!~KRdO->J=K|`>;@&3bv$IC*p_M(GCC>5?o-for;lnUq9t43^;QN z2_9*{B(VEJSBaY%+2=!>&DyS2s=;Puvw)pyW-ER6@90bXqZ+WHYfn_^=Z@kB2T+v) zR&d89#`#TaTIX1ok77|=w zl|gIek{ekI0WACl(tt@|@06#A{kQe%1M2*%TIZ|5#{9zqHYc*Z)Ws#LKmVu(tbNWo zRg1XeX>h_qRc)}T??&$cu&|yMZ2Z_5q0Kfkyvl|c=`q9?T}DRr313IoAebjaN%N$D zoo3%e0G9-iV*+cUs!^Q$y0$TZg(N%JbJH3V@j+hSIUWwC6SmyE<1+vYrKw=sA8~di z!fx3BSV(YzokYaQH*X!=5C(juiRJ&{kp@fx8&+IT(prB3J}=i_JaA48_V#@iu(@5@ zNk>iYKL94g8r6Vx$~~{TFjW={U?Hjv)}W`y8vqOIX~Evgh!dLU?!!BFA;t*y?aUg{ zg+B`iz&s&JnkNP9vvUjE16as0fo)M)qlhRQ^9jI0k{xWx!!x;$Z;lG*csQ8AF1#gq z31Fc#6|6@i5AncuUm^f3B)GuF&VPDl$q^TKUIQk9y6lk+api_Yw?7lJ< zu%0umrJh2w-u$B)u%4d9snwG``(dFp73{pQey&aQ7i|k$s4JJ-k zIN*0jAWwRBYJ*)FTN4W>EJUeb^&Aa|k6**^J6(|A0vmlSSKeFrA(YpENnn?Z@fFA4 z9D|=gn^YKIRfA1C&jMDZvX)*NyB@D$S)&@Ts?aAYBfUHe01HuVu%oKh%>uBno)+wg z{Yv5b@O1pf0mMj;A)c^CmUhJK^>LSAo)BdQo3=xWzk~!iCa~KqsujiQon8T0NV0py?o9115nT zI&!Ck@LA^rZBE~I=$aaA&A%*Q<+|2VACnk7VOgUZuuJF@jQk-C$*cIm(Hz|gyYlNIqDA)co-j|S$P9Mjk}&-FJIFDC)xY&qF?!9+ zT>uu6>|lM2qeVX+JK+1UkY@$Ew?*I{01HtnSg-I5*Mj98ECDPexWJCS93szraB4cQ z0h7Rr_a#dnK9TvtV=C_1`-U3ql~NY4ckHaB5z=nc_(wHh{f~W6ZN1Z5AHYIYZLn6` zx|9G|SWgSK&+c5|iOU0&96O`~yCZ5cF=>LR6y^yPnZbIeH~bEl1dw9_JNa0Z!f0wf z{*VSF*}+y7}c^T$0Pas*{Kb7(#D_o!2y(}f;EoqMRaHzvJg&KNN|Cj z-(;EGp>lXWuK|<5TG+0T+;eP}0&Uvw9(hX*_U)Sb%x`P`2eyyrmJt3?0DEfx&_4hy zRMiGMHNr9-z`}Z3u*CYS!jkw+cR6-QcfuA<97LQd4P68Cgo?~y?Z>>#1+b7~0_)YI zQW3MfRX+d=Np`S4R))E)k6AY1)vPvHNoi9doUl-u3U+7lUbpX(eqsO%2`;cBWPizz zKIr-vuK|<6t|*tRUX}d`+HC6h{I(iwP9h7~lsGHtm{%XR^N(u4sv3S)EvWp0cWXga zZLqucCPo8TSWgQ!#VSwObJPA*jvdm0J*_V#{`|YMIm{C(GJ}1o^E?*7LXHV+^}s5H zsr!Hx02Y$$V80%Z<>g(wy5$3dw?oA#aYgoOkb*o&9f z%R9Df_L|p#NnrQ-Y!pk&OYv*otzNdes|H)FU;$fR-%8piAqc^;Mm1mq@7Jj6O?FTK zScqza6(qae0I;y07OY~Tf#_<-+#GmHL5%bm;x+7_1tW>+XWs6Fc|w#K?7A1@kHZNI zIVP|+-F_;pazEPxSV*#i{g|l`O=y~qH_t(y)T}mG{lc5W04zkQU>AN*a(!Xja4uXD zK!OWwk9GUx!`|P(`#0e)kOoWwtGH<+xpe7J5Im+AFx=VuctO>*;8@>4e7AlhF zskZ+A{~pYr)xMhnEaaHLR&J?Mh-8aa0a!?~gKeJQiP%(p1plpsJS*69qUw$S7NS(J zy=E?VZSyGYCV+(m7uZENXUjv(@{hrQBhpClNCPH;wZE}d(){uPd|PYOz;O@MV81?N z0XsUcwKUl3Z7^_PjcUNY_@hj9@J!=W01HuVunEn=W&l`NPYd?vgdE}F^8NS?ONfyk zLp)(uopmFwoUwfZ^MojAo)oa7`xO2Fu#jT{>o&St@$zwh0>DC&9c-u6L?WeMI(`HM zc~Z05C+wl|XQu&Jh*H5Wt?DB2bvt|mz(Rrx?6H=c9ev ztCt_~_UPLpm?u1=U;*MLc2Pu1>|h`xTSg*KOaCOuYz-L$F! z^V?cc?v~Oh_p1B+qZ+X9&XuahyOrz&uuzo(_SgNelBZXn16Wv33-)z~cfwV=9jrKZ zNC!6FA&`*8rhSEZLPchI>it9w z_SrTTuxZg2(jxO&*8HOyutbB`Du*4m_!Swbstwjo_4F8kh4r*xe?Gn}ycl%`KX-n4 zg4!G%*xj{W#QtkTcEda&$_&=@L6R?=u#jT{dvr>bBKo}Zc>oJZcCbxsmlCg5+`vz| zAkTV9u+DV-1ON+BD%jMsPsD>mTU7#BNN|B&w|cF7vd#{?y9oXQX}~0~o=O|Z@*Nei F{{tcgOO5~l diff --git a/000_image_stack_ram_based_reward/logs/PPO_23/events.out.tfevents.1680185250.DESKTOP-9E17TO7.32692.5 b/000_image_stack_ram_based_reward/logs/PPO_23/events.out.tfevents.1680185250.DESKTOP-9E17TO7.32692.5 deleted file mode 100644 index 528228aca1bc9123052ed0bdcdd5cff79b661174..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 8507 zcmb8!dsLI>9S87Gs6w;|La2a>ctP<33Qj2_FNraZ!UQTtSz8wZ28ad{lYm0CM53ao z6N=&$bnUcW(IHltsgPLC5Q{QlTE{3;P^*pBYjH(n8ggj9Z}KMZ{L}M%^L>6lK0YT0 zqZs{vUVRo-<`OKb{6Xw;gX{B7vO*-u4B}^tGgaXs3xb$aRpLygOpz=TDV7E)vobP7 zikzU83W-Xr2ok?JB}|n_#lrr-*~HygIob5N6S> zqPm6GbwyefV46r7*U4}(KR$x##T=%3^Fs<2$>j>!D&cY|i=7nAKAUcEw|%|-REkt0 z7p5viDJqF9la=)}o`}1>(to0<@7&G5&VxR0=DSQcv!p_lnI>k1-P%P|C-npbnqss2 zgm_I~rZ;nVf9$mpg-o6!l**J!R^L7+UBVaV(}PXHj3uMuq0gV`#~fh_u98b%&naFi z%oZsmqRbRAixK;MICHJTRyu=9#Ue$fBr{E@5UIp0r=W(gnA-aR{-$DwPYgdpu?N$g z$?PvS-n8@N!N}OstHCo&fijKe9t6fQ{h2=f0l7>nNy!nWDMU*pZ~jRbKcHn!^SLm= zJTaZsW{ad*;{I4H?;^M9Ut11NG4*cny%6J~m@n@(A}u}RK&^C7jT?V7qrR1Xbbx7S zs8G+_w)5f`Q)}RZBk|ZucKQvk!>vdF!@(`BLJj!%VML-dZ^F>AW1amVv!AvW5^s(wHD>)C6*7SkHm zQmgyMPT#Sn>Q(OSUaTf_y_a1Qxy;}q3o#|edoMCz!k*VnVUF4leJ5&YE!Yg~{B#3% zlUQ2`WB$8pTdxsp!($s@1p+VrmUC6d=tl>@G8iiTFu{EJ7}LB)u+T~Z%c$X{I%UfM zES$FrwlFV{z1!3E6S(1!dh&4Az;eB(66}D8Yp_p4fepA1%$_nBhj>mwFEo8JyQl?p_&YKRHP&4@Q?@p1+b8?2Ugw6)t0GZPSaYj z8Q9xvySSHL48}24h5nAIZ@#Jga^fxO7nbp@C;#kwv-ZJ;Y({?tJEl>;tZCF<01HtP zSoK#t(Y)y402a<$1snSM+d$}U!A?6jv<6o9;XGo<@V*PMPiUkDTYT=`0RRg*DzLpz z9d+kNFXI4MNZJOwI^!e4Ysbr3w1%|=>k~K83BW=%8SFbr`#GYxkw*b6BVYrpKVrL_jbM-8w*i)S(SyH!VPiXN$Yyi^EH9^B z-=gWR2Cxt%fn`+j-m4Am0kCl1D%h=;`0VuLL3ws=Xbr5PF^(wjsFA`xq0wxg#%~k9 zetTWGs(TE8g&Y;wph8ETYkhYsfQ6)Ou={)`5YOjpt7#2u3ATy|DFLuhO$Ix)*ONo+ z6=(n~Bqw+c4?ZY+Cwbw;F}8(IUa9jqa)U6KC<_6d#D zV3V4=J_4|iqXMgLc}sU@i`yLl3rX8xPf0&#*Kih`qcyB0*!o+}4FDFZ$zT@+yU*Fb zoF@gakgx}~{2*8R!MFkrEci~e89cKEn}H2)*v`#cq5K<+`9hK6X#`u;X$x$;C;!WZ zrT<5C0IX+4tv->OKynN(Ot1_wuK1Er5mdR>6*acQLzk?RkNn;jDp;eY%whN(yg+ zeL|zzK1na^~Y0W2i!fepF;Cv8bpVFRrNn}OA)MR1?bpPU9`mUJZg7{TiIJ5j%|Z9Xi1 zl=@?QVQoeSz@M$!AvhL6zJHuH6TXZL% zm|3rx0sDkTYOqn``~D7KAx8yv*-QsrzzTjjfQ6)Ouyv#JiFGY2zN0m)CD^u^?M(m{ zs>xu#x#GxeFHNZiu#m6^_Eor2+jHgw{+0kf!EC{1V3%+3#}xu>Iz=Y;J6zA7S3A*+u6E}?R>92MB2%YAhZB8N!C9G+kV zduZ3&)GzFr)t>w!!AT|k=m6N3t9SKn`rnKIu+T~Z%c$T5T$6PGSU7JLY@_3PcGED! zWIH#s2KMTMgT$zt&lbQwp^+Nw=EGxu0kDvx0^9!RRo%1VN2LH3lD5Hmtt=xBg-N_< z4QmNjbE)7ifQ4!@*xIt;++)gVt^gJi_Q1O4MrjuZT+XAlU^B3P_Q~ho{hccTV^$U{ zo?-<1U8@bS(!*YSZF=`<`q2Tf1y5e;$9X?#1hCLb0;@j3+s+uZ2*AR5t6&dm4zM3* zg_qg6p*67T_*2BEtKBxkKB18sYFSUPIOR(kHsm=fvqGYfa^L;oMH{?nHEF|oKomxIY`|arREwmPF2KH#^8g82V z^(gq6hFoUMFoG>C9z^}Z)|__d7yr=RNIyCNHsY2+zhiK3A%KNeOR$cd->H3R0_dovpPXG%^+h7;6 z@`;h{H}=pP))H)kt~mj~LNyuesl~CJoiPG@VIg4;>>-`AHt1v|`C?(z(IK}87?U< z;iCMUocz)f{nUc^oYcJd+|!V c*eS@x&&5%anVYJgR!}U;z#!_9ShV{e0Au4(tN;K2 diff --git a/000_image_stack_ram_based_reward/logs/PPO_25/events.out.tfevents.1680185591.DESKTOP-9E17TO7.32692.7 b/000_image_stack_ram_based_reward/logs/PPO_25/events.out.tfevents.1680185591.DESKTOP-9E17TO7.32692.7 deleted file mode 100644 index a1a8e5dd3b711301c8b8747e69c22e6f72ede22f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 41379 zcma*wd0b5E9|!P}EM*Ht$}T%)x!j~VGc}EUN!B8XmK$x_U0W$aR4QAN$}YRI4yML- zucXL!g(QS*QKIB`@9^sPe9oNh{&`=|XTHz#J@0v(IdkSTO7!!;+PG2Mb$SeZFLu*; zU}e;7uAj4qx2ZhH)jPmqke#V+zW`Tne;>cOKF)qFrv8CmUe11tOoRPA0$lw}UH=>9 zh$yf%>KA(Z>L|cJ87(qp^m&{J@wz~>Qy%F(^9vEZsPzCFIO`+Uw;EpXb+pu z6aHx0=hyJV>o-*BEZ>_cQ4cR`*QdR%k#1{0A5Tx8zyLE>UnfsjZznHTXKw>hQ4_h2 z?~I3nlYXwjzmlTgRrcLp1;G@_n)E4_%3Lk%hV=L~MgNJ0#5_cF>}kX=U@G}r}r~8&(p)#$<5DsUVw*>x53?}=G5!SQMEmP)jRj}*a)cC zPPeVD9+C8O_I7tQh??&~$@bUx?fonE`wu6arm=22-Bv$i{~j+tAKyhzo<9Em25lZ_ zXHC>{9&Gk2=;heK7V34;?WAk?D;VPI`R_ViU7UiP{XCq#=eZh)Hr*I*?%k=ckcE1> zI{SHhc)L6KIS05Jn$#;gu<ZUh1wxD66xXGL-Uw-Jkh5o?>(5wk#RF+G z?{>Mc!~-$+rD~+bJvfkl(2)l=9@I#1l0a&$dXTC229T09=|~G?J+h0U04X_~5$T)J zPL^x;4#}Nv}>Bh;g#Qyn@IzuPPBsivgoTW(IxIa}$YYC*Y z!}eO~jDC6pmbfFKskIvE{lV-=r&ctO7ff@D5}YKEI;iI5v~CDU$(nSe*JSPsOY;FK zIh+yc;WpWp&1?4ib5D;6saCfD>cPz%edr`vj~%J|p{aU+l#H<? z)O@{F_gRUyu*4;EB{DVATq!qFbH#EU!AU^+UfwDekdig&NV8=t3}+YsQgS#W(vl`c zmMYoYLEO`0Lb|kj6g6#FqYKbUvK~89`z79w04W(`Lz>xIJ1aE#+73WU2Dy_|m=E#$7J#}^Au5=aNA;?`f*0;FV38dA|k+38HxNkB>tXGH3^ zcY~!6>&6iTQtG*0^PLfG>q*<=EQvfL$V?(;NlXljH{zsDlDH-HO znwO!Vs+x{k&3znxE>sg~^r(DeKuQ*-BkeRKL*j5gx-TFl1AIsWZg?mD<#}LfTL_QZr2`{|2~O4_9XwcHb^AhZBS1>l zq$ACg1#R%y21v=_j7UFcM_RV5xZjI=dQ3>Wb{$0R7`XEv=p9ckG@iv@s`jIkjt z(bLX4Yop&3kdi@eq~=HE7f$qP@m|P6HIe>VHf1g#B@5G$+PRujql#CU15z@;hqTHx zRk7irznhTO5=d=yyrdh3?g)k@ejc}Qlp5)t0CuEPSGJWGOG*w2PSzn6g&L|n^5TyG zQnDruspyzY5g%6uNXg-hNbR<6v~*5)HsYQh6H?;_J*oI1FT9|WWIcAI`72I-1f*n) z4e5=&^|R(WR4xFdWRM$ait0~sgUN%g2wA8m(#shOX9H5QFdgaicS(|ixv!%DDH-5H zni(FYm{(j|B&4+j(grG#)t%Tu_I-a{`dVeI8ml8cUocvYG%2hex6;2_fB7Oj3QVoT zS66iYRkioq{kB+@<}~z>%*tiiLs%Tlk`bzz{!L5otAz)6X2>M(>l_ z__i5?Gi0Ya`OGH+AOkaHvntW6pB0^Zks9!;;>LV5T&pv7u}O`FuY4S@+6{Nk(mG%5`19K4R%mCKbqA98hmdw z0gq@f0rspSU26N|{$H@nU{;{Yq#WguTvYl`*f(Et{b++Yia45a!#?|)0sVl~0KOuBXez(Q#{*vDoOk}>P=%muKJ-~(&E zCR}m$*ttqU4JN>rH#W1nWchj-EVHL+*?2YB+Pyqr^K}M%6dnbzm0?v^0W4IdffenO zos3?EC*?4n5$w9HpDhj7T(01mArsg_eRqmlb!jp56DqQUP5gb4F@S{}8`zQdT3Ic2 z+1v%NkmLqCYIUvnz^(?Z1ua$+?7@(AqW~H%0ta)TZB_z!A?YghcY67s~AWKFP-Bzq|U3sE}Q4%(@bTVY-{ z02UH_V0&L$uLuuGZ6T<^1lY@6??|_v4L$_Nv~tJ^TQ%6%SsY+*=o`tu7lut29<2jA z_(W$_M2*BAz(Q3TSkZ3T;AzRD04$7W1nW_A%W}5gus1w2WCFWZ=0l}8_?ALHp&~oj zd#m%F0N5ELh<>txwUKLOO^ocA17IP^4K`t=Kb7cycN{Dh@|<8}?+pF}z(SM`HmodJ zGKsqG0$?G*2X=h*3dL64)K<`7cm<-t1lVour&t~Hem@(Qc`De*P7Sswmj~=e%h}Pw zqX71gB;$1e7OK+0?vlOyX!jk!!gxloEe{>Cw2S(RZz+fo#}MyUdHvak^0-qy8u|%Q zqMx)KcJ68yZvYE9Hn4p<)XTCzoiQ80LXsP7k;!jVW8L<9c@D?Vcc{@qYtKKzQZD5&-qNS77VDCQU0XtuO z6VLKFqX72PwzvWS3sE}QowDQCZ?CNhnqX&5zMKGHp)?)r?uEM2 z8T!i(0$51!ffX+~tq2-@1wYloD-aDPz#hD_R(h4%tb%1;JpW{h8f;D}57<>r`q>JP z0@xpiyzBrhRHcJWlRc?kY5`zjJR{h!`fDt&ivr*C%#aD}x~ns&sZ&evstZ&k`bpbi zM+PbD!ww5MHn0Yb>Sawb+Y}FAA;}F^uX(z-I&9x2L5tM{8{42yD*y|n>0lGCT&Fy} zFKq{~kl+KWmpfZgExP&yb_93@qQL~%tbP}zeVU7B!7?AsmrqlJ&92}8o4<0P{H^rW zBjM3Hu#N#HD$mA&TFZu8nTT@Cj13N7|;y8Z*( zdQF>Q!lM8-PPsM$z(Q3T*w7SNgx(^501M+8!6r5+w6tkCFqCJ8OklO+##1dK`s+YH zp&~ojOYg2n16athferN)Wld2IP6M!z2`(h1E-dP8ccwF9=F13RpFZNu*^R#o7k(t9**GwtLPKiR(KS^ zik({T0PpHTaw(q*H z_@e~Kv4OqoF3JkpVd4s4A;}H)?^heCm}L9)f)=X@*8OT_Ie>-Ibg&EF6-Z8$_$32a zNbrGek)Ngb%Xr8!K@BFrrcv3_DJh}^SmvtjJ`QTIyOKD-ijEGIKa%aj&6zV=2UaB2 zSM6S=Uj<+xN&_3ZL-uLpXrJd0xj`|@uYm0NNAI`k7NvV+aK z(H(CCf*c#zn&YCZxcuvl0W2iB!Tzy2m@-+DQ7LG#nqZ&KH+TbJp)?(=$&Hzk=#vXA z0W2i=zy{xlRD5_6I#f`D39v2J?UimaFTt0py(eaxHM16UZ(2v#!XqGju(164dTWCClEw3xbkWRVE^2^HDF z<`uh^!YKjd*uai@QL9XSE;R?RkmLqiloD$B&tkcspv7u}J+bq`eE0m8~n@Gk# zyetB+kl+KG`}}W(^R8zd1vQue`$tZMG(KoSJy>SkP)kQO*w~XiU@h7$Di9t8uz{&3 z@a7k&stLABticoj3*#BVPB3gCKD#JimuH4dU~l=arhaR;B?R2*QvWkcnIO!QX>kJf?x?=INZz2#G3 zhlQ#%u%cwy!EM*O16UZ(2)3x?mZiJoOd-z0n3Y?UED~du;%)kl+J* zqwP+`vA5k^1T~ldtJSbfdTivPr?AY_(_fv`U~6u2fPEi5NL~_twTtj*9auNFuBr*I zE1CmXs7eDHx?R>g?CBf;3*#BVF4Qs*w+PfO=b0fB*sn1=sHeNz9EE;DMRu^>>)$p6 zu#jT|`!)Z&a`>Wv7yt`NZm>naRa2{H-o}3`Ay0g*rwR6OV!8;xLX-|Rx~87wqeo&G zfQ1Af*cnNgiiDsuT?I9m0K0Loxzy>z5qw`3bsOod23uap12($REo97>UNn)i_cu#n&b zJLOCDxj&tUPZ88$0_>T~+pNClB@KpU7F=2~R}HrG6$e;R;2`;_v%{Pr`uiP@XdPIQ zZF|-6!E4vU4hvBl*ndw6HuSIE2w-76BiKv(+KRP?J;>mhA=3_PoqLvAdGnn+^b;zw zgY7E1^bB@b$gzR7lT|BikJq0FU?Is3)}{GI$~UItR6&c?1Uq&?Nk0G!rRiXsd+11R zCGTtxU?IT=*352{!YL{JPeBbPz`pLVMLNc2=UG^0gfexW8tmgr9nq1q?JUxI!@MRu?v!|pQx zEace0-cnX6FT`B?24Eq{4Yu-JGIeK+KHlvKdE%cFO|Um_`?d$L5T%1Xy{1%pUT4uX z01F8|u>Ie!Pt-I%uGvhAnv1}2CR#}H2m$`{2^KGzH# zp`Q?C2U|k*H3YDbV*`6n@0)Vd24not1xaqO0f&xIrs8vWNd)r5Vl}}Yc4_?zz(SM` z)}VT_BqQjxF@S{xA6R3(3O+vx#xsH)_ID5QlK7scJTqk4VNZwerw(3d zG7|a;71_Z)9{LyF4+}Xqu-|5VQMODBEQTExlH6e1*Y>20ns><+v{+5B`#as91Yn^w z9c<8-WUIlp^Y#H)NbrGecH`5z{=bcj5!7G;toEquRukGT&VyyvbLi==2CLl819sN1 z#eIcG0qlg_SOWkHRq0?;WS<+(7!IcdFrE?Y$}6M9i$;9KUsytn*mQ7*y=i@tx^eC0 zbLb~T*}--iFl{&Nu#jT|dw?C&YFCMak)b|-g#;hiag&ZH%=?Xg}xbhw-&^RV~AiQ zJMX3{KSUNmKOxEvcAwp}qW~6iY+zS;eO0zw*GUOrA;}H)Xu~0tsLC^#=WwuHC5XQH z<|KfH(sZyUK3k|>ZH9CPu#n&bYi}`0p;s6aD5${%*kgN!NuPH8hF5-SN*8;m!5%!t z0rrMVKl!1c1`6m9XS5FN;7^@Z3+i|I4ZuQF6YR(Q^bFWxVLT()A1ix^_r1x+AEHBy z6|Br`7xlHC4_S_6Hh(7r!mjrU<13u z;u+rj0;TC-r#_z~-CX3f8o)w=5A6BN7K(E5=K}y1UV&&Z0XDJG8!MNBR(LVw%bWf4 z)nL;uae#ezvX9*9QYHQno-?ah+mMN;a%^B9 z`+QL5ZEd+6z(SH6Y{AMARGMFzi05#y?XWkuelP&AP?`>QW^704K)ZPv02UH_U^niY zt61z}+fY!039!~_YpmM;em@G98Goa`ml|yJV;-=I75DHbGMrHW>-d+W8GwZ-4Xh|l zW;XBXOW0vyJR?};rBUJ$lXv1R<`82AJD@s;s-$+}PmUnU4))lJn|K`-a%^C`t@xkY8`v+aHV*`_P?`?*YnKXX*#Lb#01F8|u1$Iq6%hIjNv3~ubpAaSbN!wv3x&4J# z2_VM?w!7UY<>7^;mjNs!xxsobO`tBt+^7+>Sj|&{>I91d01Kt*U>!0{Bs;>)@kfY| z-~$`wv0afqBx1dw1`}XiVj`uH?IN1PGFN;a=c5Mu?F$E3k-3T7_r<+6!lQLy)5kPZ zozC!a2e4386YR^55=Q_F;~Bx;eIORg=M=oe(2TutiuVhlqYToRFenLfdur5wN z@a7lDv4OP+ey3~@=!o~jLXsQowXIcR%b4)jf)=X@cG8?vg#Z>x)4|p*p`=Tyj_-gS z77~15cfI&WA&dBJub>7KVEY)Hk#-qBk%DEeYP`W$4faEXHv2bSD;Jo^M?~p_36Iu+ zRaNMzau;61n_r-+CfKNzdy@eyjAsO!Jfgo?{>T@f!vrzb9rktVS<1~|&jjcvMA^am zHp|36E(19>utBLGmCepK(uExslH6cBANXk5dyGFmNCWc3Vl~00yWd(4U?EBeJFT^` zG|cQsQveGIKCm5)hA3LUt7rrbE;S_J5e+854so`z{u1>2K~Q%oTeVOP_QeJsu(#y; z8-+&!tcCj>E7)P7Dh+JtPMNMv!b$)O;~Bvo{v0JPH`_ClXNF8Wtm~L!D&j%X80aTd zB>G7^C774wXbK;?Ajbwa*Rxbfb&9zOU?Is3RH~m<92?j~opR;H%Jv-qEF`(X7OmYzP21ESe_{uDPOz7| znRJI87NT^pqs`qUWB;lj0bn7)2liT@JVo5Bb_1Znkp%=iqQL}M)rnhDl}X4nIHpS{ z+Xbk>-b&{HYkj?&eD%(O_>?2gXdPJV#f?>`ax#|zScuZVigwEEqTKoeSQyU;c4ec1 zV#$FtJcorCaSZVs)Ti79CM5X4mh?1N_@G4@$;pXgLr1hbV|^5$vrCWh&w*#0V)#xr0uY?mplvuu#jT|J0QPQxod+%3hc0u zr9%dD>-5~2p1af<`&`Z-%cBCYN9H9ed{8Cg(wZ| zzh4|w#rIeTU|~EX*iDZ8#DlI{PUl%16WD;bY|8Vd|4Y~apd!&v8rX=S+HU|Ba%^Dl zAAO^IJ?myIfQ2MC*pfNpsD2|SXbW1bCfF|DH}?dvP?`>QYSD4&mPZv^04yZ<~Sf*lreY+wtvmMRO!498#1LXsP7Nna6lY??Nn+(DjLtR~pIeJ|iQT@a;%{U^MV zveHh}g&h_Wd|=yWWGWh3Kj|Q-!35YtX6K|1dy??lRIN$9WooeNRyAP%rb{%bqg=l2 z0^Y5~8La~=THRRXxb~eVfQ2Xx?7uf~M=!Z!0$^c0BiNSmVd5o6uFi$G6vT*Qh+yNx z71W&i3jF2}qU>NV{s`X$U?Il_cH5hG%2ux0^Whv8lH6cV@6Mv)?_XaiXtA1L_w7xI zfE^Y})4}db&!t}8ZXN?*A;AZB{lzRrcuR}#02W?>XfOe`W^1}sKfU@PEYr?w?s7HQ z74ckPi;U#m%`=i9dTJ?0v<~dpvE|u6TnE+wScqzZ)yhhH4`5+DBiJ`N2gC`{3(a|E z$aD_dq1PA6KGQw|`Uw?@e$q|}!kz`j0$9kgfo-z1SgH5$M+Sg}BsW-Tqi*8olka#6 zTC65mnd8y<02WHq!LHhqEZOwX19wTf!|7Xbvc9=3* z{NB(u9cBnI)*bd#Rw*SLy0-$rLX_wy4Q$@5cC`Q&a%^CaR6SM}R?oyo#zT@D?0^pW z;{68C@M}HD6N}XZ>$}H05x_!}4z}EOvQ^pO17~1|g#;g1f0GO5RLI(7K@BFrHV7@S z8uBQ$Jsi_UksVj4!M;1l1vb`L{(g2Vh45${*zTiCvyE%~f&na4)dail`S<4l7REDz zZ4)+8Jil-V-VX~g;uzv7!IgP=)CJE4czYp4*}>|pxi$d6LXHjWklV#dYl|vV*kK{b z4K|{*xg@i@!xo;y@$;V(O|W;WPY(vLP?`?5N!v6@zb*0jd{{{Efz7vhu82xqG7-SS zD-aDPz{addlg5-rpM+&*ik60}!Iqri02@8Mo%~wjT?gUOIO{O`lQX12sPM$u5f^ztZyhEnOlp0wuCcU2e$d1 zs%*yt10Dldh|<9R`vh+HkAHsyurQtxY?Jp3#oN2481XEQ32d{F>(san?=M0>p(4>w z8rX+d;|c*R2lh$wVnu3k|3QKpOo073HNfhjZjUNBrcLv$SE<3~-R1!M_sq8P-K zU?EBedoggZ)N%OYlK>VHd|;FJgq?f5>Z`7x1`}Wn6Kt$of1a8R>T2VUMykPHDdGV8 zVnG}Eii`Un3y;=;jcxcNTlCm^Fo1=sG_e0Zs_2>fc?E!l@r+>CR2>r^4ADv8nIY2- zYqb3h_2=E3fzVH=$PRYX*zacmEace0zAk^PyfWZ+6o7>!H`wFj&r_7{nGu2(s|nWV zMb|U{3#I8`uYKtz8DM)E|8yrL_`n9=xT0wEu7j4K1`}ZW`=?mR3_s(w^-j@U*QmiN z-tvIe(mRGvZs3dp*wDAb+5=dK(!h##$ojQP_yS;IJR{hq<~zi(?eed}F@zYg>EI4) zdjA`Bvi*}d=qE(k!IrG^EC8^OV*`6$R-p80)MPV&g(Npv&&avdfq-7O1ua$+Y+^;b zGXNG!)4>jUJxls%*7vrs!$N`&Y>(|miZ3z$I0<8|;NKYpE^|0`OO}kSE@q znqWUXK2Z!{Axa0E_eT|_9Y5;;fQ1Af*teflial|`EVDAcvITU zR~1oeu=^q#vVYT+bkjh-e_JFzL6t zudBaUzWNOQY8GO|F~l71gA=qE&pe$qa4Wln0H3Sc3}2DbCr66N$cCUO7^ zNp7&Ok{d{-y*P$9zd)W?tR~n;u{9k4EJW#GXN4t7E?&DD4`3m|2lj~l21U;D5PVVz zyaLf+0_?(}HdbHs6rW%dY9V%9uLhf(zymh0z9~MYf-?$WCnhf54?8SGHNj?itUe7p zER1Ia+jPSj@#1+o_-_Ejh+~LgpGCZ<`Y#aUH(d}V`bh)(ac5ry3pqBhX2DODMN$WC z01HWOuv3hVP~&c%z&o2EPb^jwY?rSy_5xUl(!ur^8YW$SZgfKc8!(<=!w2?rX`n@j Y)-8OH2D}2%U;=EQb*`1WtI5az0b|ENlK=n! diff --git a/000_image_stack_ram_based_reward/logs/PPO_26/events.out.tfevents.1680185938.DESKTOP-9E17TO7.32692.8 b/000_image_stack_ram_based_reward/logs/PPO_26/events.out.tfevents.1680185938.DESKTOP-9E17TO7.32692.8 deleted file mode 100644 index 37dacc8946f938832e05bf5d5698a479ef131061..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 59922 zcma*wd0b52{|E4)gh;kfvSmr4vTx08rpCVSTRth0KCPm~TJ|EMB5ND6WQ!1{nnw04 z2}vkPsgx{b=lA(e9{tYi&fPwLejev_-{-vVv*XUpojW5%HUIq%9eJSPM8jR-3mfK0 z4Rjp5?48}shWR+UFCEfnvYB?zrH<}PJiHt{?7bG4E%A19v-etN=IiCW)X~e#@qeT2 z7CO5++SUA@M`gROcldkUNn>Pf8crJBXy^Zq+w^;b9?i6MwHqvTc5^ge=($8sBr=qJ zZr$TekH5oDZQW7T@aWi_n&F?D^)S>n&~D-7;p*z)z0};%)6Uh=-OkO?-d#@=P$g?R z{^U2oNiRp=ze!Pm)r&0KESMr$lQzYG0-NnS$JliHJH;gvUW;IgZM0iy>n{CY!_4hH zJ-s~q>|9*+#y#vJ-sz_q$vwTA)O=TGPrHR)_VbrId${XuygrB;71ipK@!xt^UL_2N zdivU}wVM)2FMD?leI%+A$g$r8Oq z5t?c5W^LJQ{x|40x7|dj*GapBcALLJKTp^H*6Fyw&d1)%+1`D=qh3Ir2KjWE8bN@;TGD>w6$vrt7bYjw}s@A^@W|i z{{{}MTUP>s&f1-{4Qc|O9K=KuQ*-BW?BWz174X*Af6J8Q??e)%~=*NAL|RA+05ldOuE)*w0Jr z3QLUlaf(nOecPD>si<5gK744`_`jUrO}h1lVm-1q&xlRwg#kRj16h|H;uH7o_U)9DH-HOx~Tse zamxFcav=*HPjL9RMjAV?(-VyhhsPZWsLlDH-HO+Hqcgv9h!Z zk&`12#(-?NL-Sl>XlmCxY6lh(~%lsuEC2P`=rrX?_e0BvOC5JO2 zUF34cvTml=74GRVA$>cqIrUu2`#p4$tjCV@YT1VgfRv1}A-yZEn^yXK_(?!Y2Dy<2 z^z56g^vJXlvQTxTn&DHO0V!FSj&yrl1FKof-`@hHWPlH8T3Ud7=iu!=LRw284XtA- z{hn|99+v29dVY^;Cw)S(BNc70l-c_Ad?h$ZAU!Lc($ZidASG+kkzTc#>h!BEASH)0 zBAry+MciVOK?m;XF(IY4j-_&noou0#WIcAIW{xJk04W(`Lu!~RN~=1vDIJiKL2jho z3%jJWj=!)?$U@bT$`w760V!FSjfq2C&3#POJ8+kUki}jdbYm(bGFL!K)}$d7DQ)yaBrgFeIh+w`pE*^Q zE-PB)a!-#5>G!+sDWhhCcS0x0dhAGpc0|_&q-2Z@>5NIDw9Q9mh67SE$c5fRwCBN1A41w>rxZkdnh0k=_ky zEN*USw26CqOh_kY)}hQ7Y&i#=BaDrm3+NxsQ*DvP+M$At7^ z*idTqE^~Y{kF3Xzw9kyPdVrLSu_0Y_?zCBTYZI zw<#bc3)7Kak$09c{)Q#S1;igv z?W9RA97rc>4%;^GSGeG0EmD!_d76dQTn#`<)}$j%w&^%<@l8NV4rfFvvHfOwYgJMj z_w<;MzL)4x7xVVNf=-h4h)$|L2KfI^oO+kuwFabQj1B4JhQAcsX3jYTNXZ~K(tw#i zhsIty)?Ua$)se2W*lrC-$-;D`yZX?QnE*M6ukj8DS!>&{`yY8?*;sMFRqXg5&Y5ARF8+H6!)ujB` zM6618df6uLMwkvP4ra*+b@Q4=;?(ac+B`F4l6r8c1?7_SS+D!w8UFEXH5z9~^pp0F z{x^M>F!ts6qSL5Db_wO|Ve87V!!8ei-9cfBgG5LE|T()!s701M+8!J1WS ziCav36vQ(_Ca}s;U&Zg{wf_nIgo^B7#c{(<0a(bffnDSML$T`N%n<+0m#8t0yg(yDkdALV^!$PRJm6@v6Dw1vQueTb8ITz1TPi z)pg%`I!3j_?%mA;cE;g-QP3gID1hzXrvGmM3sD-_fJ-*_J`KwOurQtx?D&la;yJsX z|K^z?6WE`&zr|tIAMK!@P>~(1@8q6%|yFXNATKYA^xTK5?4$$!#OcVVM@w z*T$;AhR5)LJz#G-O?VW*reXf4>jeT&mZjkmo5V4|lq5@r+;-BfeN}_pN%xGeah@ z+9!U96=Sy@hJHdtcCg9k_b&mkkYfXDG3C4BVu`^{01HWOu#(qb1FXAY-!81<`yenLfdusx@Q+XGn0v4LG1^jR^+;iC(Hg(NrFB(1Jg#`(d8f)=X| z_E+YsFaQgs>0sZ@4wNij*>*pGg#;hip`+f*PaB=-FQ~x;*n2S=(rFv_B)~GY-e0c) zyH?Htc3SdhSqqc?CBmZw*i&gI({7CbuuxSUZ1}SVE&vwBGlH%6GtJWOK*dg;88U%= zGOSSiV%5OY&`+qy4z{z0>sbH`IX19i52_UlXaD>FU?Is3HrTZeRWW-)6G4kr2mAKb zwFv+gO4Gsm9}kf9Sls6`fQ1Af*hzKH$Y(T}G*wW839v6K(xoOtc65PdN>T$4t9IC* z={#U(HMZ+2JPKe(B*tq1Sg5KF)?lX@ey{}N8NqJq`PlN#XmKN+88U&rym|m-{A$o8 z=qFTU2itLNa!UXUIX194M?NbqIo$pNU?Is3R+2k5#o0FQv7p7OgI$|-x)Fed(sZy* zDkw?B*md0jEF}2AN{U?Nfrp-Uga$j_C*TncCctX$wXnY8UbP37X+33BoC<99T@J93 zgQ{hpe9cOQM{B_v`y5ZZyE%6ufQ70wu%gR0Q{ML|gdG;fGlFe&w9v9=*sv6y88U(W zUj10?)7)}9^b;x){iMAQ+xxUFejfsIY+#$N|ESn|# zq5@m_gahoTf={yPlg)YvkJf@66?!7=-|=}}04!8h2itBy4BnUv;~Bx`#5NW;@e#G< znIRL{IcIbzllKepeQl`74mR+M!yMRQA;$(bQ~$q9f_kMH02Y$mU?n5hC7*X+vsch! z)pywT6Y3ZMSSU>gJ0){*js~56aW@-Y+yBdd{F3{4KDz&kmLqy5f>p2 zPK?|qXtC;Gi|Tux0I*P+4%YKkH_6Xl{VD-0B>2EOSQpAuHM05%YA^w|d&73pF2kp0 z!ZN+Tha6Syu!V0qz>1m_$)?=7;4C~^3s$6XQ?|WaeFnfnRdukXp}k`OER1Ia`)j_b zczUQwFP<4PfnBKGh??M`IU4#271_a#)op+`fI*H8?7KG=3WFXa@O@ZFa)TA!3cFHg zRS|wl0(s6$f&*=fZUR_{(!uIC2$nc0zTE?`kl+J*`O8rG#4DN21T~ld`{+!Fby2?% zCpf2zHKrd^fqnUb2kg3~<*CA>0M=#4Ngn_URn@_sv1@_fdWP|gU_0JzA&x(6afD}v zOkm5#w4)xm%xDMwgo^B7>pbW%7j{_4v4Nf9Q>ySc|Iih7SV;1KHJB}~>y0q0dE|RoMY>#hiL4ptLjGtv!=Ef>E3u-U{_MgT7T8Hb5h=67K&+K$u z1@`H84zRt-i)9~HCy9hdYr(c}-$R-A`9~yxg{tac4V-$tgdG;fGlHG4K~KCpqIoRO z44J^XG;B&u`F`jm^b;zwgFSLQMIXRIjt#6l_=BRX&F2yT3rTLU{eoLlcftqb6&mC@ zci3I`Qau4IMCo8V4|!#kdB@>4?68pF1G{B;p!{3nyfQ%zCcti4XDziz?rQ_*)Wfb$ zybA2Yb#>YA*7_gVt4$u~3XcNVyGLWh02Zp!!CtZnZaOv&z`}S&uuYaX79ag%eS>F) zOknHST2bC_h8I9Tp&~n2_k_0d04(I#z~0~fNuklA^do?UBsbWAhD*dJn@(#ZXtC-$ zY!|DSV*o6arh`q6945W`wD2^5g#;hir(L4u30uzZ7Svz@?6|LArBT=YN5C@Y2fnHS zn-Rpp;ms&uePHmieP;|>es8NueZuCnxLy=6Vj z@ak^*;+Vjm)9+0+89by9^b?}&U>zn_;&&_{#|Cz2p9;n3T=(e!7LwdxM|uyS(lhG% z3R*frK!ivcW@rh_dG(w6Lu-8&M%LV^$MwX|$`eapNJf*MSKO?q`oQkr&WDJ=7w z>6H_z9rpT89cy?1+aQ!4zC8VP?ZKY;G&KHHZ5b=VPQNY*lsIK#7q3`U+~P3 z3G71c`jp&YduQk;RAdM1a&CGa?68ny1G{i+h2n(IkqQ6{Np7$K&9)8=YS?#U5?DUc*9^=qK%Mt?wP?Tm!I>V*~qg&^v|B_~8Zs7Lwdx zkIqjQ_x+TE@54f#Sgbl&o%m`009c69!G`H<5RY<6$^o#D-~;}bNX1@<&+BS`7xiiQMR*jz8ZMdp4!}ZHI@k*~Uqfy2VJR@4 z5v*uNm8I^1%{_T$$h5--6zNdz0R!4XKcOPgPa0UgMoIV$amcZO-5F4#@Kui90bn7? z4OTAgLggyniUloJ9jv9{jPC#zO4GsS#&?o9OJZ~YEF}2A`b{|@@47%QMNoqYup?KM zNMa-2Xu&c!HXn6b1vc>v2iS$HD`oDck>0|iwO|)6T%jzC%3cp(p(+im=z`6N7uPFb zhlTNsU=O)!h;3Tk!CTBBMr=B`!``g!Mm0WQ+7kK+QFgGEzJp?6hlLy)*jUptMd7ZU zzX2>Hxxoe&wx!PZh-u1mI%@tp)xn0`>4fhRKxsNyzcw0HdC%UA0I-nY1N$-csC@j- z388`-On}|DBtw$+k3}a~<{+D{XH;NMUE%;MnpYvS%ksAs9<2o%S-easJ=n<#z(Q3T z*nsmkFOHt204$7W1bgwxJIe^;<(!z{Y3xpD#QLVD)0A1Oiy7N&_o8Z&NS5 z?j-;V;~BxW$_2Geah@Lp;8T2adakmjqCe9c=SQ&MyHh|4u#n&b>-T$;Jn#G$8GwZ& z5Dg~4=CloxJ`Mgg1(s=K{=5ck>>Vz!6U$`oV@-;MM{B_@&77tjd~BZqfQ72+VD)UW z@q6nqo)PTPy!)1gZa&+2X2=9KB3qA&e&FH`{e+4{KWW#n+wvFUB?08vz`kBxsF>7k zstCYBk{fJN>&=vwO(lMJ1oFi7k2=_D-|2G!EJW#GCz*svs&DMc1F(?b1N-OndHIPK zhqnl7FafqG#?^)CM);6EIe8Z_NMiErNuwqX#f_g z(!d5J+H~F#^A>hk7|#fHxQ@B_PWYNxJTqhhJH$hu^10H=2>J;X*}+EcKkx%~Sje$~ zZDL)Z=-&JSe&Ya=++Y>wJjAoh>Z}yBSaq+C)v1^k^sV3}7L_2X?OZ zMS1(iBijpVFag&4%rdF&uT}W@NNM4cb1JaAUT}aF?Jkz(KiZ6+>T*VF!HOi|%7XSw z!vHKq)xkENbiEURh4GAFvmX{(&YQg^8_prbh)oAybe+}Jq%2phI05~HC_7k_hpRsV zSje$~eU$rL;k&?L5bUs!bKKJeHJAYFb9;n!xlhv~SY~)*%S08}?L|Cb9ky5X6CMSy^A^@00$`yk z4eWo{u+#5v7y@8nJR?}mvY(cVrj=~unIY2-n`(MVY)&n$2mOSK>|pH{>}dgDA;$(b z|9YO{!Jq^60W2iB!7BE)r4ok@#@mx2PyBVNgRQLmh%dSzN(UP^v!SF@H!plH0VMdq zhDFB8TQ?XLE~vo-*g>T|tPRK24~BEP=X3q@DzKa1bAUZ`rdW1A?i1d;#~G~!d&u*! zGL~AR0I(2M2OGVvpEiJn@r+=%JR@dT+3o|dFrE?YmxjH>C7UAr;2c7X73_@A$<&caeWIbC5M>7&t$3gWu#jT| zJI(Zs!aeMGa{voTZm?gQ_ojUPn&CeukS7+a4z~Q8oi~7mC>`v9)kr0M+P4-u&`+pH z^po~3!Sqa{0{|9sY+%z9ixf*vd42`3kmLq?xl;%g;@@eXpv9_#ojqgAG5`yu>0q~g zah0r#$({yaA;Aas;HSFDX&!E-f*MSKZ57*6TH(3m2`sbc6T6EluwR2Xz&>+%D~oxv zw@P@l7VL_KVM=eiu15hZR8zP zXEq8t#2E#!K1X6g0W3t-!J2i~!Jk!x@r+=%-PaMj&9uM|k0Hhi_CroP%4u#n-u(tq zcCgDHMLEF^3pqBhht|GPSWOr@6Tm`}8?0HhoLVu@SC{8>uwBFIxed($uuz%~)^qX+ zN!=8u5&#PcKColl3gk_<57P#)a0H^k1lX6Qy3&po-|>qT+w;HGfPJ@*1MH~VMY58m zv#X&)oY7jaU2m;XPF!+y0)U06I@o~)CDpLQ!gxlo{if@QpKpoBuj)gL6>QHh-6`4j ziuKS>h!XvzT@r-28_fc+kYfXzn_8r}Id1tp01HWOuni(osk%3l@#bI16N^>fVb7HK z01F8|u!EnJ$iKWi84L}EBM=QHzy|IdBHiJfkM|N} zZFRY#0{iR&2Uy?wZ)L_89u0*KaYk#wzOM*S4!^K?Hh_hwI@mffOQZl6#xsJ|(`_i8 zDBp#f4#bFah&!xuR7)!CpVpJ1pAaSbNxLMly+1V=z(S4HXB*G;DB)P!` z{8=eq5p3ecb2`|rVb{pBI|EoKO$Xc3xSM4AG1*-J3kg23F&i`Gt8Y=W1vQue+kJ(9J4Td9(+Qva0#SCb+WzkN14EEw18cYUrD9l&jT?Z4BsbXc zD=$+WHWm!$IUQ^}thGhbGyn^w>0r;cIAzti?y4{V3kg23dRu?WjlGlu04yAVXfOe` zw8sXC^`KHmSmx;C?`y!`%;W((YTKtW;ZXpqU66kpz(Q4ZusZ^W;SLMq8Nr4}*Autw zrG;-zLW~vcdCiuT*QLF$pq~&W`boPaXlFJh6?Rz2v4O4oAY0)Ol93N!A;}GPs@nsq zY=&+c&*@+TTT&F>4ZuQaI@py-v!%0hLtOzZB>2E~zML!H>!SE7sKEr-#*KbUoStao zS6|ImWTdEeSmiSgu%a2IvU-{_E9eksv=*!=KS;T9=JH$s3sD-_fO9r?r|i##9Tvtj zf{pL++VWUIk~Pl^nJx)hM2n~!u5q5wPpHTa_Q`7r{&W=N*uc8wDpEC+zeD8wU`jgEeir(@NBI`!WCv2|lm`+7-+Dwe#Nz z4Td8S4JN>L?v*ZW*!vCstLZqzOQ8aL;T;Fq@jj(8;}?sxp+lU}TCg2f?ow{-y7vQs zg{V5%ISucY0$3Q&2)6j)YVp6DoN{<($ON|7-Q-M8G#Q|3LeVHuE<5!;WXf4<=V`7v)J+~uR zsHzTjhiG?u01M+8!LB^hOMLm%db|M=V#KC{FS^ECkEaGn-9AD;A<7QcW$*+1opQ*r zfqn1yQt`0W;%@*JlH6dU#|}vLPWfiQb2`|rVe>Qx;=2S;nhv(-qIS|w)f=h+EF}2A z&P{kAf2XO3PvC|l5Dg~4>b$ONoxA>+6qe~%SX~45_-`JtiAx)`5FQ1vt$o%Wh8-5F zGJs9Gvkt(*_%_sc4VL!1)<6?a10>oIsX0&fhIj=w14ZuQ_ z=qGK5{j;)z7woW*V*|T>NuJ`J?Dks#3rTLUPfc!!729_v@th7eu%GMPY6{n|P?`?b zr{fdp0{7Ej0W2i=!1^4#D-UsRBNEhL0&ILkeQS-8Lw>+A=Z9TXs&?2zn>5*PFI+#Q zOt#7VU31~lTCjE>4l8?yUU34jP?ZMuzqhr%Wk%QlSQyU;)*`&0IMp#?1J4YZE(v-x z9!>p8zbb})LPd74LweY109eSeflYENQoOu28h;59lH6behkX#wF)V2yXtC;-1fOl1 zeFm^lnhtj8;XtcUXX6t977~15AN;y1kJ|MJZ`Ob#5Dg~4E{=+me4Js1KS$Q<PudRqVcl%}d1A=1fgRc@PjPh5R{SMINOFVi=r~gByD$8#pv9_#O}jj6 zD}aU4bg-UAxCC=VX7ULu1A<7PRgl%&R01G)b zu;=UkcLTT4;wS(MNp7%}2?NEkkEY;rO(0J!RvqkNlY7Ph7NT^pNumc&^{3#Oac{&e$sZ>s(0-# z16athfwdj*QgQjG&RhTsNp7&weH&9T(qRfgi&Y1k@vK50z(Q#{*yp=XNV;p@Sqfkw z!3Vb0;4=Bh_{awU)~14hM>LoKt2D5%PFS1t3YJ;7!{i$(umQ;&V09*!$m(vIgwG}5 zjMjn`iOwj~R@&(SScs~F{T}=9I)H`oj9`s|oy7XhP22M$7E05>=F|zY zI^_1_34nzJAJ|hLHIl18jo2rs!30>FRSl$1^#_~5GI!?c-Bf}7evJd{LbJEB&^OVz ze{n`@!S-EpMd|jB7TymFQFXAU8@n$6urQtx>R`9cxo-tvp)?)rQ+s2n zW|vig02UH_V0Z7&l0Qo<$4_S92tU2r1yOadZEmES0azH%2=-J)qS$YR$4#EaF@X)&i=#Y4d*ZzrP?6{-ZHJvU zbns6A3pqBh|E|bW9GY~k9)N`;H`u_hT2vSJaaw{Fs}9!o_m*1#7E05>&X!3eMoTir z0$51!fz{BxAip`y%^G%CI0DgN0<6oaR@Q5R%x=LlH>YRcQthx6*&JYp^(vMvA6|>r!(T##92?kKCvz3cAHUE6u#n^id#2?WvE=F1iGmiZ4z?)dMIL~K z(sZ!8PH7T1(_nlq0VMdqo}Khg?sL5rKKTWXKs1;DTk={huPtn0hlLy)*t4Aq6c_rA+74hL$qn|9 ztv{7={)e}q#j1ln+2`vK01Kt*V7s2E)j(jH%wM)nEbiomb1`}Yl zrUytDr%%B5VeeRl-BE!pDB%HX_swtubcizwVB4P>Fc`o>R2^(@qrfBp3*#BVZmjGo z{`|1jWS$u^?XbI(W>BGHGV}o~R3!RI0~`Lh|3m-_IX1A-xAPTK`mSpNU?Is3HXyO3 z{7J9b_%qj#C;mFs!M2G^O#`qHrGt%(Cw7;GEW09aaRTQ$qx>&-yKS2-`?%R=Ua0|Yr(#4Bv%gUUk|}Tlm=FG&ZcK$ zcl=HljAsPf)PJD3Ao9;ip2acku#dJnQUNozE)>2e1&OgZ+1PeXFG>8tMaBNbrFTduEt? zXMJ5?K@BFreil8m$`-Ad4d?X9vyS&vU>~fn$9}ig|G+vQ$Tb!o1+d584F3*0EL2qo zyD2uc5nK|$ct)@Vk+a41<=ybjy5!pFJ8knWdst$H&N?`zih4GAF6Q8@cwokz(S4<>_00C6`8sB@sln{a)TA!US@f?`gAh@3wdI(>R=<~H%$R7MCo9) zW; z9yoE!vKd|nyVspRWET=2;vQ*j*-zD7mg9{)+__*};w& zlX(s<2_VM?cBJ0ldQIZFNOTQ35@LV^$M`~e-4Q%*g{Z_UCHhz1j2^B?z-Jd2C|0Gm+EyMtM( z9X9SN2iVjWm9i&^2RwyGYr!@RyQ-YpWQ8Yyg{taczx3;l4>X4Hj9`6tS&CCfoaoLo zL#7>e;Ga2Ez$&{q*Z`m+(N7xK$bU4GV26bq8(7cSBE{941=|2DB)P#pIJ_@;vd57n zf)=X|Hqt5)ztaV!>0oVlb(8F$Jf$~)g#;hiKUBTs2eEU51T~ldyWvfWWc}#wH(;6R zix)jofsM}K02{xzT=r$~NPMT7Gg=FF+WGU!XwMhd0W3smVE?<9V3osfe2@l=X9PRy z;7)PpsakmR3&e;`2Y1+<`jJ%8R=3X3Pl&REO@2770f2=Z8(2wlq2gu5?py#1Np7(D zN4{9v2DzT$Ig>Sio$6qlG&R9T6+vk_*ycmdS?PDHZVF%_!3VZ_gJ$x&^HB!`HJAXq zdjAe-fx}oqLR1}WcBFeZ01M+8!G6<~iH&YPiRYOi z(Vf$*0Tzhq}-WN1YjY-2R1(ZkNonMI>%v$g(DCR zCcrkI-dwtVfnOG!(|R}8WvjpjR&sznw7o*Me*At%i26L`h}MGLyXT_vm~NI2fQ6_! z*me8#(*Z1uX9O!NnlJWlz6QZUj5vpQ4V!#zCADJIr#sM3h!Xvzfi=zSrVC&p#|Bmr zR-o_*Zh8rJSV(e%eS4@K)x&+#Bc9X2c1aL2bw?F|h0=7eWmB42U7H-c9>79^4{U7r z=W>&XwT6NkOn^0cq#=F2Wr`~-^Fo5{Qx({?-*~_pz0uVZ9tE(iJ?<_BuuxSUtlOy! zyd;3}j9{I&dWpR=@8kQh5Mu?K@O&qwn|l2v^b?}&V6D%V`~t9$V*`6WBu_Em^k+GM zg(Npvi8RL2HGMe#TM2n$vFeuuy%Qr!0W3u6VDpycSp_ZVmknSc!3Q?cFivirsldlW z!V!oD6JY&XXj*I5&%O@oBwhRFsKEYQqs4x=R*d4k?8TnL_^mh2Xf4>zov$dzH~St8 zU?Hjwc7)FS`LM&nct)^0tcQz#`y9siF(5{qL)>AfC(NT}uC6`{U?EEMleWWpwOKh5 zz(S4amulz0VH*kYfY;u|d9~)K;e$c34PqgAFvWPZ{;+9sVd8bB0r`cv)|WuzSsV_kI!pfpZ9y7zNUk}p!vV1b^cpTL&sMA z8DV-uVrw>4C6A7EmnAA<6aMEF;x6oypopCvr4^ZsN5Bw zPlZQBD;43*|L6DlD_8VtdEEmm*S<2Xs~r2_^Xr;lvFl|ov=w$##VM6>a}qoh@!?8E zYPr0&}kv;AT&vcj!}3-#Lu=8 z6k85Gz5V2uP;`C8Di^clcXySDDm;mSr1nvcT%n>sF6CPZ_adW znP_&RK3)}<96nQNwb$^x_v2nR8`!VcoSLSLjt`Ge$)_bm z$HiLRJ^xA^a7`ZQ*3wsa@8B@#vk_Vg%}Gg>JT_8cW&e`{@#no(t9rJ?27e64YuX8I zgqF>*PexR6@pHqKakFPzm9nbb8H`kaN1!Y(brb5>p`g}L1UrS)?k|nhe=q7X)+BOH`v!t=)W_vR*Up)2n*7?j1|L95 z?xZ3;FCFE3BOj2GkJBPOe{73)W#N^9?AL2vC?YMtc}Bc1dDd0fB)N|n>Bh?mMSzqX zV?vr(Z>)*lI=&u|l7s9>i~B~1P6ys6_zbF#^xWTW696f>n2OZ@`BB1T()mO{N)B)# zU9kVJ!oPnwlEY`UB%}d-%6z|>c_JG|ycld;r$zclEDO?L7n!K_q367l{~;9^oNR3- z9ScawofM?0#nRh;Q#}AF`8X}oy~YC3?dmlm_Uq9hohGm%HmSxX!Y0Xm%t$@|UON_$ zl4DFrUsM}wmZb~`1El022hsCKGL3Q!}frbTuepUp?sk4nRT|404X`Z zh196zUSan+eRjcWz2yICBdwN%bg**Drw=sJgx)Pr@bB$T2AbBqUtO<7x_!9;v(lSK zy2{+|{JNfhRLAtIbu}gOe$Ee_T3UNP+Z&9nRHtfb<>b8+U^uuXEz|>pj(MA>cy#2r zA)VBLj|#;756s!oqveJl<2wi74N3ddK8gSPOMl6~(|-msa8o9$GcFoy{12^Y@N8+! zcvT*bjT~4l<3v;33J&lZR$r@BIkmS-OLek^_ybl`xt95_Bqn$!ck*gUbhinu!vvSt znH@J45*OTyc`cX(_EuS_WMQ_`H5fCvl}UpZ?28;0u!3}3S@L)rJN{7}SV8K$5{cK) zxlS$fYQaJ)6>NcY&&k|!01M}7!4`OxdAm(L#dSkEu)hp?FYfo;>J{u08kxZsnv`t; zu#jT{8?@6{BVRsuKY)cKJJ{gHgW?Xkn_hFg9nHh)gZ(?ls|mnDH5F{t{B()A@ZC`W z3kfc;l|A1T?uh7niPwTjVBP;}^c}Z!+IKLf`Qy}ov|vj$EMUu&ma^#q&l>qhbzmbR z3{DRB5JUl3Xr+QZCbjw}SO8$*JS|wCHc!3#?OQmU&16WA1gI!~jB<{Xx_aD55)dw3LR6h;CLNyg^Mr%`_T{YV^ z02UHlVC`++6<&K?&Tqjau(uy&N&XDkSO;Ui((HVr1^e_33)nGfon^n=TqNcn)qxcV z{w%2u8JGoNp_K~uh*Y%Q?SB9k&eMW5-CyXvwX)8P0H5F{r`fWsyh6D8g z77|=wJ?=j*{AcY5YhDW`fwgaZ;OkW!ejLU;Uqrmqf<2LL$oxgu4bxt-dZC#&|ELaZ z-6@$gIR1e@fQ42HSV5lDBrnSZz`}W2u#tnSyuYpdsfOc*bYMllb|oSV1CPT#p^+Kv zocFCY02XpgVAtCiYdkLm83R~IvV#>kr4>XeYr60nRv)Z)O-3z%g=#9;>AP(tRku?Y z0$50Jfh}-V6#jea`CeWNCV`#%ra<=Oo0MZPX5ExCAGBcC=CXhln7GP*ekH&sENfH; zHuk26^w+X;rQJm%ngA@Erv+Q8{KtD)tDwys!_k3_D(Otri#@$ypU}t* zHcR&OC4hw-6WCmVvF2m7y%~UoBscEuN&nIVBtJ1Sn1wc?-KLCERGw}fpwqNo~W#9XbbyqBlV z0y9O8ul(5z`}W2up2-9z@W5C+DeWa(t&mKG$&e5UfUD)360EP ziLPCUG>YG_`e6S}I^Q3_LNyia)7cY!&L<~- z17IP+1=iwd8+Fi;_eXgxm;`p@h%1uHsy0X9J?$Giwv`s_@+C&hpJB~%>|~XpX_*jR zyO1TS13M`Fkl$tJHIo4>M5$m8Nza+=Xauluo)&Cb;74!q{4el(=@8TYq6Qt1$N$>{_07EGfa3bm;^SaQ4~*4=5Iwegj%q<1uS4a z{JP3cy1I_!AJu`qEKBmU96Klkz(OkpY-+AFYQ?g^W= zVGvPMo!1BU360EPFO57~3}7M01U9I^NF%UqHxa->k{xX3TM=a078*(Wr2H;Hz3s$504(H~z&>7Pq&XgYHx|G`k{#^fNK4{<{=4hE zhSdifbl`Y90Q;<%gn$axx6Mf+ziMYU01F8&um=6xsxOU+tbzr@E07jU0(&j$w(rum zj$>fV?5wg5TCi0OEMTum9b{R>%2WKKIyt3fSb=wGjXoa!g>G!i+SvyK@`>EF{^%UL7}< z80|2@g4eM6V8;uGp9Zi{O$BTCqM8`2>G21Eg#;JaQ;Ff~kg@A}09beh(t=4~Gk)9R zJMSiu2V*|%KGISPcJE4K<}bS3Iy=ky91~ySAJu`aJ2lQPU`sm*fQ43luoVN$Ea3?Y z=V`&N>eW`XJi@Xs#|`PgCK>q?zeMbbg?&OJX`d9ZZAsyIDeTNfw`dOy{SZE~elLGd*tOmbJ068YG-Od?m zGLJ9G0I-l`2YWqr4H5Vwv6$De`e1!u`3(WEP)!B<(o{{v-P>ReU?IT;c6H=9^~*N< zR`Xgg3GAu^D}BEoQuzqRoX|egS_}5lDHgE#5@#84Yr;wXQ61R)n67?7)3%rZSZJky z734~1+%H@PVBtJ1*d_POMAsKs`f=Ql4s1?B2(fwf_c5?fXk-R!ZawM*JYgZn1U93L`Q$YYgm1-@gIht1h7y|1>674GNQgvB?PdL-~v17s6zd5 z(W05W7EA)07k|t5aNx_CFy>Xl!d44*=Uo=Cw+}hXr27hF{G&RsS4|xK8is_$0$6C( z2fK2|U>5)j=V`$vsl=j>Ui0uhgc#$uwa&_?6L0%XvV?s?lo@OXqa6HK8<1lHTQu#{ z7hQyR8a!bk$qqKzzdMojWT2Ge?P&hfsSnm}+^!4&3)NJxX}yp8ibF5f0a!?IfwgjL zDqQsK#YA2UCV~B5u8}0Z$`XHEm3sUKdo9>k?^wXDnB^?H{AAfzup!o{4(y577bU%? zc<%zRcgjeu`e04kXU_+)aGn;dOZq_3Ig1x%a6^bOf-SC_LWHcDd=T~tQD(5}5xv*J z6BcqzU>7GEYJx517Xw&GvV)y(ewR3Nr9&vMVfDefS9iki5E#R6DJ zaDffa_)#63-G3^t1(U#5jF{(ph^VlFF<*E3;GhM2_NP|NUvvpxILWTnjQ<6qc9#FMUo%Vv&7r)e>Og=#9;;$LHY zx4YdN1z;h;1y*+0M{P=UDB!hV5?JT3df%q9%l0tlsCk{bYr)oEWC82l!%5~h=@kAP zi8ZPNTRPTWGBIh4D}aS41?;CUy5xaPZU7d}(}I=V>?S&VbO-(tKExP566|qP61{^v z4}*O|lo@P>^P5Wm7II8r9S0d{Zp?4@2*5&;9qcJ5E237NThH-MGJS@%p0Ugtz(O?@ zY*n{RN!@~L8v!gNxWGC;=&v4f{r7ra3nqaTF3$J$dKLBz#=QPobE8&?U+nKYm*eeV0_&df+gtz( z)l{%gVv~p*Ef;Cx^BC;CrA&_G@ zx{m}E`I&@bnn63*Cp0pH_3(490Ne-|NP85t*j>O-mhdk-8 z6MeAmfpG{HqExWU(oPX~HYVQzu#n&aTa(sQSkWzE9IpkFzY|dYg)r(TX;g*Iv*%>F2ii-(+A^>g3h5UqGjr|b~er65XqYKLriqqw{~=D z+ka=YV8k1dAvxU4sIgIf|Noq%F0Q`5em(&%^E^$5%#C*Vx+y1#|M1kQnVufLF7AG= zGyOe$yiLEE)}(qb8#b`rzx9${o$C+v%#E5D852oASMS+wrqu2hRJYD0cWnQS_4@0A zhuO@?+^C^C_Ky)iAKxV|o<0i}nA(YIq`cdf5Y*-0px0E3kx;Ldk)@H@zrg@s&wu9W zHp^v^tDlFf_e?ia(en9y_YEz-q|HP<-CX^=J-lbT___MKnFdEK>;2+%QNLFI7S>r- zTn>dzj2ajjsSE%2NPpyRmRZcJ$hZ49aB%hNj}T~W)XJ!-I^gT$=`nMO%WOZ_SswrS zllboooGmz$6xrHrv^K3>270Ldq7GKXGMBA|ES3xJq zdfZ5l*L&UykdiSjq~)dhDGhB`O93evA)gwCdx!wbMmlzfRrpuM_M}X zy|huyH`aiZ3y#DZCXnpt+>2L-qSkKAEwyo=;Bdoq`o{zeIF`bHpmLo zI;lY_3T&BbkR{Utq|46#uOKuX5AkTwn1Pw5ip)CZ7~L4KqKUk^#nM7Z-|9ycY<+6HmuzreD z)@aAB|5n`fBijWl3SeEGAP$c|-$kp*GPO#Yw=cB%w{$=QNfnl+bDgh-P_tu;0W2kPF!At>iMj^ zGxQTGa)Z5pEB!94aggHz`~A3nO4*Ffl>io!{9s4g%$Mv4h^f|UvP`i4cc=XYuuz%~ zHoZ}WEXwz#DS(B95ZHq^t&(#KXTQ{{!35YJ`P=17R;{W9(;V?BWRe=}4IZ$?k?$2I z8}|&>KB@s5@z^AFmQ7{~fQ71buxFhfFRU{Wz`}S|unl|YiWi<7@JHYX*}yJOYepT2 z9JLGj2^G1)I*+h+0YUnIHJAW<{Kj7S*!-STV44G>4V~3s3wXeaWUm#Q z)9-A8XiO4MR0HBPm8H7?3Bl9L|HCZOu`4w*? z04$WIgUyILE_K?s(yf8QrjGG)$^`2gTXF%w!gyA&i~m$Q{OVh!6gWaQuu-cG zsUzN{2GCEa$PG4swGMue2RSaV$EEryuPO=$0a!@#gDqJmlhmluN~YChnP4}rtuYh8 zLTNhKBbVDt*XU;*0HuX)pngXfOdb`07}B{@#)MV46-JtX$P# z_v&)L>GIy6tJr<|X$$S68nBnWM5*fy&(#F5P?ZK&bk?bJ^QYzj7RIxJoiw|N_~twv zeSsrn1ADfj9~HBLS^)ioibOyE`|;QRK4~2mYMucrEabSr8tv3eIeTpVa{voTez4QK zo)_O6KOsP?$uhw{zt?{=fQ8a@u%p+tm0gvG)&a1P5CVH6FEuG|qQ^(A8ccv)d-#Ri zH9gN3rWsdwf2JC2JP+7U!*UfFua17yKB@s*d(wSX^9-M!02Zp!!Jct?*yVR1fQ9j_ zV4KAliqq;mnksOFY+$o8CsVs!-xl$q)9+ zs6*8G)?3`Qnk*CSP2=4w04$WIgSBp#D>e9AW(8m&Aq4ho-0P&8o*TDm)nEc_QnwKK z_G?z>VVb+Jl`p>m zEF}5C-kiCgs?qk=JFO{^7$z;a*Qzyug@h2;`IiSL-*B(}POAnJ zU~h~vl`Uw@e!B)Tg?FnEZ#|75+xn9c0 zprlv;3rT*kZNv+x6}OA=iv!3Lf1S(~_VfP9cK|Fz>0k}(cbCq16;l_$LP7{^+N4Fv zHXCdF(5k@%Sj%RQWYNV}CcrtJS?{W^8my8B?BWk!6!$tBCu$$nfDPZ5s%koW{~rJg zRq0^koQ|efHU+RSo)v6<%lhJWs-MpUj*t!PWv{l>rUw1{K|i4)H`o=^OsWAatfIZ$kSN5Qn&w7|<;+ORc)L@_SfOQ;Lq6m3CMx=dI1NOs#G}YN(n|%Q+ zRHcKBbu!Nk&H%75o)v7{rhgn-zOmgPaD;4N!}lqu)+bL6f__3pZm^9jI#~l)$Z>(4 zbWS&A(&T9y04yZ=!HTB7lT6!@v{$RiGQoaQhAslIP?`?*{+SKZT%Ucz0W2hhz^?n) zFoW=#?n=Tm73bx^%&f*VecAtiG2r=ScN&J*xO#|8Feu5QYUE+%yVEF}5CI)Au8y_-MfuU3;~f*n4mJ-+FJ(sZ!K=k%o8>PF!n z77{{Wn=DwFoa5oq02*vkNWdc+On}X8a$lBmQt}<9xpeWv05#a1`rL22?8lTUu6zu^ zFFtvr8n7L&?Nx==5HA9-PuCMwnP6`%J8>9RSQyU=)_X)VagI%^J}^0mae~dt>_sgb zcxp2A6QV>vXL#qPkPrfUs_v5H$Ez|GS~Zve8#{WH+`6Q)6HHScJ8hX7>{%YL zi}XqrZLJO|w2x}Qj(NLJmHhH=O#lm3Xbl*krLpbv0W3tBU_Tu_@EO3ucvi5Be{~bLd)29dz!9>6 zb%=7OGIDcTK|i4)H`t>~vc~{e$Z>(~{aP<2%(L|}01HWeurUr|YJylEs?}tfV6*c+ z)&sCmnhtir7i;+pv2iT`3ke~x_jBeZN0rpQ0}Zx+N5CT*On}|A(o!zFaN<5p^RwTD zKsDGx9Q6 z7km+z92?j{+uf+BD|3cJKcOPgPuiB?u6t+P!$OV=Z1iKjl;NXFV*o59`N7sQsFqwv za`~jyWSL-Bv|DHgV4*Y}?0e_q(gO2_cs(p6guuR8ur_&R*VJXu;CX8ZctnE-*jHB2D_#P_a3&(;17zo8P{iOAJu?u@_enTY3A1)01H)VU;|^E-VSL; z0azH%3f5rSCUIgP-Ae*T$Od*|WjIxIW#U}uCsZW*NdtR0f9H8vVIju_Ht)1$uhzA30QCtz(Q#{*i+^`W$hCNmcR-N2_djoM1zvIhIUz_ zRf7qz`rm`(qvw3axB8XaMeEdH5A%Q(?|-eZ=;>Gm9pa5@z`iqDs;d3`_Ba3wQ6|_; z)yF;pSQyU=c1F-aam>3*WdcXY2KJljX=6}iFsMs#ZgU?Il^HsHBV%8X-e zUIJK1@`KGj-kdVk-?Lq-$uhx)M*1%Vuuz%~_P`1=*|0;60s$-}guwQG+%Ea9epw#? zJN*~|k7zIfw%jg7KD#6mm&v{T{X^7XlX<|3g5M|{%bwaphj^nJu;X?uP4S9owKHb{EF^@$ zzWqZbw;K5!uZM+KAR0`7J-_vmytQqgLYSssaM4CJ*vC9zUo9m8CRaB879>*4}T68f+O4*t7Qv6;t-adukum zfbG`JTNU5b|2}|)sx+|we5|$Xg_#k6h4HLlYXt?0-Q;;C0!PRO_S%d?RLjKO#jwIc zMWUZHuqj>~@3JT1}P-w%_@^DgX0m=F z!=!1a)8zmb5<+0l+P_We()xT2tr|>#wXrjn5A`>}Ex{$rK4EIGVKuqmbZyK3q)4(= z)qxK2Mm1pnG+(JQJ8`f8z(SM;_Ma_5z4qVl09Y8$3bu0PdU5lYe{fp|F=EmAuR6`6 zU6!XErM?+8!MkQ5$_>_V-vo(Y-1{=cz*5&?3h2!{YycUW#ssVd#O@ON0?0Ihh3sE}Q7^hvGZ1w?I7|#l}{L~ro z>5R5>;T%GY6Kwst=@e!5%NF_xQKFx;6}D}<-7)|RIWDmKM(CtCKEAmUz(SHAtfzbt zrPprLS*<3^1be3Q{?z~$O4GqcEW0aBJ2kaAfQ5t**ly{al4mV1TdGxq39theHQWP;V}ycEGgln%C{po#R%sX!wD3ke~xxivZ_&%JgR{|SRvAR0`7?fZ6y zO!PvA7jR3jHQuWR`<4f6t1jh=t)<>Jz=1ca0Xy-}O4XJYA$WNqM44dy+dr)fU|~Ef z*sTR4#Cew;Oa+dR4Xnl3NGj&-s@VV*DiZyqt*{rGKl%t@A;$%_e3U4q)8pO004yZ= z!FF>tkRCSaenYFtGQm1c?2`a1ER?2$)y)r*y>4$m2f#u?2<+rbohD{nj3UY1X%n3|E5tKb2s!XsMdtP=2 zurQt#>^AEKVn5|wyssBx#G-?H*iS7FQ2S5K3x%o=Cnn1TThTM%27rYq9qh)%d#Pt{QpW;VNC<(Qxpj2% zZ}|mNtr|>#UErc4|K5PIglU?+9&}I*_5csq22Xw{HV=F>O#7$??AI?Iss<~4>(J5+FTz9-&6Do3py|qpsAEW^}F0f6O z>ZXLZ(tibDA;}N6(M1c&eZiCtT1}P-Hvd&AK9>MW)4_g9_m}RB8Rr8lEF^@$N)#^1 zlZG9|JuJKe(O?4XHgjG1Z{3sWFwJArbdIUP=JJ4DwBm=NbM_|u@|riQ0h<&zQ}toq zm?{7ZQ5x95Xs3goSHHpv3*%YA-tKTn+~Rvr+@M2@_*W9Q1aCUTQ~d(X&%*)$QKFx; zJ#5jPz$>uALXHcps;*8-So(m002Y$`V2yX^OFz^sUn6iP)qkB#upXNNBVmPw(sZyJ z@79!dHS#J0u#gY}d-zQ6av z6*sLu;Fn~)Q4Ls?!D7`)y_+!r7NShBd!KI|31DG7E7+U|55z8whMf_Z9NP*TrT37M zf2!^dV4)(>Pa4=6Wj*j}Ey!_!Z8=mY<^F}Y9|0^R`N2*PUM=aAQlqI>lVyT+v)@$# zV4*Y}?6j+$ zHn2}GJ)qX!%EvcdP>~yK{LNFYu);!)3+w_t-IUe+?(YGxkmLs&U{ff$72J27R+D9d zHJClz6~IDiI@r3e17z144rmHsAt40Tqi?sQ>cAGq04%%$(O?4X*u)(9inpim-}Pam z7o1jujp6~D)%?4nwOcGcxq&yT0c$;IscQe56EgrTM44bMS~Q;mU|~Ef*q;gK#LXSH z;??O8PsyQL*?0#)KOsu=leWTc&7f`oSjcgKov+YIIsE0RJAj2GKiIIS8Pw@o zwee#u$P<%gf{m|Pb_T#gln&NxafGa^$BA?R3ke~xO-Ef%3J*Q!tW|>vu+mG0@{dit z@XMf?nO$SmU~lk%Ep_;=I5902?|S2nYQPqB_E0@>>Dd{;LX-*CA#+w3fQ9j_VC`Bx z5sN>X;T@I`BhDf2VXX%hQ#Mgm^`M^+5Koo|r5XY{PYq3ji!c>0l+wQrYi~&a~USNj5@Y6e|62L-~2KJvf zT~x%D762B;vx4n<`o7q)!zNsGAV!=+1Z!{qjOvvC`8f0wqC`JwD{SA#c28l2g&Y@H z)kB?>29qp~0a!@#gH5amr26hZhHoh#PfV5x*3TgZZ$gA99c(MR8nT(YtWLlR3ke~x z3&*=9-O97WkF^?JCg2ebCcv8IER{DuxgXz1JJ-xPuLfJm1J+Acs(A3E)(hA)@kTXZ z{qv`*;-`nL1F#Tff?b=}pc#OL@vLA^B_xQ8n%P|yI6}5P?5D%2lxNy<8vqLxiGI?+ z))+L(8Nfo03+y?GUdpkUi6sCQlKf!X{)4}>kUdtwJ z?qL96At3~IT=&_@Wj)@SYt>)^tj@C{*_j@TBVn3%W{$e32D{gg`%RZ;`gg^~1LNjs zAJu@}`DmKT@~&z>fQ70|u=5TsegI%$JS$i`mw55c?2UMdD8z_G2UplZ+wV{_Tb0E? zKOxEu_M>jI@c1HeL(AFTJ_II3~}(ydxembtDlHQhu1X|(0>r2ngPgH}= z<^h}4_J?BWsTLogL%dN9*sP&ms^ycuHvq5@Wr96A<&6!1El44bk`-)vK^;l_HDB7} zHpv+03VZo;KJ`E{F$DSv6^VY*z#a%R>jGdQ#|5@~4c(L?qp|#XMl=Mf_0Yr4PUk@kTXZ-3sQbwodfLXKO)}3HJPf-L(NMjAsSAX?CHw zkt{A2&LPBzbBJ4lvlT^D(X;P(c_Bo(!QL5Qia)UjIWDki$4itKjBZ{Au#n^jYv$Eh zs%qaAzXF0hF4gxbgB{o1Q0h2Ww;OnSe*}-ykLce92eLLL#mV> ztCisZ7Lxp6WAlSn~X*$?3_J?Fet#k03E=UN0wN5#Z^tVPE z{MjRT1){+O*jtWQWE*Bl@l%5735!)~u#r4qQwn}4s{LJjphLV-4cInqd{sRTM&n(x z5M_ex9%*U@U|~Ef*!{J1B?CO}s05CX4XnF+2^E|r9Rv#iR3!RI1AAdcaS4Eh92eLn zIii&AlZxg5SV;1NEq@kE9j&}LU8~75!EU~;Qx0IEG#zZ>-%Q!fMRRe5g@h2;0fBZ& z9e(@_hX(h$O~4}>On?m@K2RQR5V`=SIbw6k4K-LL4_Hy3`-bMphcm<-t1lW7yTgx-{4Cw{aEWI(~mKy9c9~2Ts09c4J!LHl5@dAK_@vLCIx>bqY9`D1i*C9r1>u?YI^inmozq!jZ=;!!6 zqAx^0X<$R;#WMgbYS+!2Y&esUCnn1TtMj^*5rBm# z9qh&dVX~kOC*J^ANC<&#*J!TzL+^2SwQ4W{_T;W>@@G45+=6Ku{WQu@gRS5JyI|LM zMWv*>MEj@)>}c~PD!0L7rUF=~$^_fn$Z0Eph4HLlJNJ4gUKQF`N8kwAR@lp*3#p!O zobb5>^9*YLuP@wS<0Ibx0kDwc0z3ZHALUnHN4#1KlKfy_oJgm>omplElZ8Al*k`S} z;w>@|rGuUP#7NrkN^}l@g@h2;CwaA!2l-i#0v@9d}pBQ;gXf902ZQ5u=Sc$;$5>ao)zrtaTVez$2OD+ zOpXn#_3h`B&#fF==qFSp`bk@1OI-$s09eRzfqi&flyY`tiZQIPkmLv3J!uRzwBEtj zT1}R@!aDYxjlYBlrRiYn+h$1Lt81|sn6Xf_)i$T0?}Xs?1tL?aQM2o_?*qJvw4PlrEIha&Dj2Cxt%`bh&jYu%OF02XpwU>kMRN%=Wu+++X? zNq(@s2Y05D3Zlye&ZPRUlL^-E$Cq8OC4ka&upeya$d07kc7zoc5<*}%`P{z}a+a#p zs=)+Uou&2UsSd~S5vosyTHaTK&Ex}{_+4?}{qTm+A>OD4tmA+Us?M&917U@QC=KjC z7r(4oGrJ>zh4HLlXFBLeqK;Jm5I91%71qI~ka|3F$VccWROALb@pg+r02XpwVCQFx zQu@T+)(5bV5nF9)nEc_wIW02a(2>pm}X-6kz6&{LLRW9f>K4({1Ch{kvFOVyXts|Dz{O_3jhmI zCfJv+-4+5^3xlKoJ4#lt%7^_We-2eT!sH;vxx%`9`$G9{Hv9$sgeW)Igxjm809eRz zfz4_2S9w2j`+WclNq(^Lc1DzK74=Z7$uhx4wd|)4D=d_zgI%`%sq zKWyP-01Htj*nzu?ZU9&q&kFX|?Dmr1Lkv0#Opa}Zy*8tYs$*p{0Qw0PxxrqcWM2R* zBLy8U7OnuRt`I0Q>UnBzZ)}w@jF(>h$L)YOsg-z@~pyoVsuf@A~JBYQR2f zy;}94OXF4m7NShBI|F**(+godD_CmD0Lh@Ck$wV`V*^`%ZcXWqazDI)8!8h0r0ro% zcBQ=ou#n>d`=Gi?+0!<_2*5&;AFSi|AZp(IA|tIP%LE%f^w%!{3#I8`i~jh_A~K8D z0$4~0fz2!b=rFWngWIqoz$*|9Ccyqy1j(siZE=O|<+I_L8f-ET*o2#36n_HOE1*NX zQ4QG93CmUEYj6DxU?Iu`YuRD*3|L`dJS*55N4iSd6|7GZI6^kCX9H?Wb;liygMLCq zqMtOdi(Zcp2e6Ri0z22_k1}gfi}wH)lKfx?Fa1dkoLbPndA-E~o~)L_eaz#3T= zE8czyz?-OfqZ+XG_S03nntMM4un=W}UGaNiE`WvctYDqCE|iSxvk@;5g&1)T@nfy< zC+1S!m{X^qpAh8++dQfGJAj287uapaACyj^B~t(_B>BNkKfQsv7M_pyghHN}EEDXe zX!F_t7NT^p_xCoDjnOL@4=XGrguwo|b4ENYWcF398ccvas@xzy@$+&&0Q*&9^;Qiw ztS7#P9<$OZ`3rT*kV~0Pcepf%V7C0U1 z{SOmty;#VZ^63d>CV zF!i2O_hrvX?P&kDBT zc0EbI=K*U3j*x8++wodCS(*wXljtlJF)Gx{zjx#L)EF}5C zu9QBfJ|D2f$Bjdt`0HeX9XGe}MF0y?I#}PbZPLGQ3^D;MB!s}8IN4H}v z8ccwV4PPr489U+y+}^_{d{l!?=K;I+O_Ac+bCYP`z#G+oeROQ1%G&9o4S`Q9S zPXG(!S;0!W)Rgod+Sx{6a%?N?#L9B2aLl6K&`+qy4K~T>K}T3&A;$$aS@}!pcQs-I zfQ2MK*n&n1O8=NGKIR7U#9t?Kg_Q>E8VFz^N(Vcy%W3Jjdj`V*EF^@$KC>!KvNO-f z)T+S**l7`?|7*hL9od7~Pz%NmVV z4J@n(1+Wlhg6*8YxfsC0cvi59y7A%`U!IH-I6}4+Ruq^)z0}RdCvZbWZm_w#|M@*W zk@~;5E!%z=LXHb;*tiPi%xS~%$B`k)4>qKtNHT%?iC;WIo)_#vN!)l?VIfKfd);)M zv@f(85u5{YDf%`30g(u)Cg^WB^zg&kFWhU75t^xC9?-12N(p;tHF!Szo$w z-h$Q8Plyuzr0rpyPpoVQU?Il^c2ve+Wv0)zFj!$B$q%-qgQ+Apb_w4940&R*%oR2* zIToM54N*GSMjZpBv6F0Gz?J|KLSRjF`}h61R%feL4JN>*JijNeTz2I#EJB4DBg)la zb9un7eNd!m-_1T<`=|!2#AvvxveU9OSYe?m6Rh==!w~=$#T&TBI46M%&zKiJVzlPF8K!qEb! zgX>d*GY?!V0W6fJgRPf#Ou8Z|aX)~Cgb>*6W@QfcuiDQCuDQveH5CfMP2Qv7jb7|#m!vTbe2 zmVHt9(Imt;!9ML-L9M%}yC3=qQKFx;Ey3urj8FgzIWDjz`-+vlYFTdqu#n^j`#b18 z)&Akf-2!Kl3+%k46Tbm0l%|7qDr_dLHvR1nU?Cv{wzX(~;-KRnK55lp0_@_A7V?gl zPt=8J4ro2IS`9Xe2W)8YdqrQTrp6HcY0neYfGxKPP|famB@@6xlnJ&h`r2GrVPQNg zSo0_CCCaYralZpGPOuJzhSF&}!rnnYA<7MQ=cIKq01G)Tu!as5%KCjD;L{5s$q#mC zl_j-h@#(7qr-KV@w_hJm16U}{0BaUcb^TR$3V?-#5ZKg4(GI6BkGIpR!35Zpw{dbe z_fPmRxc3fEMN15y$c+PU@PM^{`cARX*0l+A=v!p~uOqZ+WGDtFbS+sf7e7NShBw}xNF zUy*_FtYB9>sS;;NvhZs>h;f3=mA|1uNA7Y(05>+H>v>}>Fca&^gSy8z(SM> zwyV=oyhR4avx2>Hx}`*~q8{Fa2r=Ru;+wAUeKn-ApvCFXPl$4ZZ4h8E3&28-3+%x7 zN@Wuhr{Mq=lKfyFt~*ann>PfX;RAVMvP`hEVy1g0k#B?5CU7Z zd#l6eh)XN9YA^xT;+M0W^8SraWD35TSW69duQB(Vu7peP6i$8;{NjK&ssX#UXqu|K zN*)AYA<6{1_+;uT*b=~aRnZ>XNq(>grgo>=hthr{1@gpXnPA)N8pi`zh| zfSsfYooulRz(Q3f*!tVAzXh-`o)v8Cb|#WlpDXdRbchk>5W)W1s3SeRW=mrL3sIt< zv@OBaFCkk1EabSr9$WcKDf%367r;W2AFQL7uC#`v=P!ZN!L^6&+y6vs01Kt*V9j6F zmL=rRX$xQ>Aq4h|MNM%V<5|^OHJAXq;#Q^X-h=eUFwJ|Ff9tBjX7hlxul-)(>~Db| z%kxGxU`Hp+Rux$9dH`S{$^^SgVK^1Q!gyA&hZP+q%Lb&x2~19X4iRkq)4I}E8@oJ( zenLfVuw8qsz+dx*92eN-1;3P?{vKThU?Is5w)e1js$9BypH`D)uCP}UZSirNP?`?* zglMQN)a@bOaR3P+u=m`4IGhbjz>i_z6^I5CVEsHj#o`~|HWPa3sEN6kF#y?@JK5t0*)r{Mb#h;gp4pAOfN z`otwK0I(1x`bk@1O*}8ZfE5;UTwpu>_@%6@zLN}KA;}Nc_rxt~>BH1d0%wwIg>7`g z=sc{jP?`?5-R}=lzqM_;!U_usA+WvMbV~ASn*Up?1`}X?))>hT)*WyZrs=!T$V3e` zqyhIHc7E0iMf|cPe5gKeR0G!CeVS^km0>i1g(wrOXWk&Zrwhijg8epsu%z1WPl3SX z*jCs#MTXK9(dX(zKcONw*hkOH9s*d%ae*~CQmwqY>I&X93rT*k*)5JrD%0xXkE=tT z`0He@uriN!_~XbBrGpKd+)-xccBwvqg@h2;w)w$Hak?X$YSmx@?7jw8@(-2fUE!SS zUA<$f1{=u(Hg)Yo#V@f=y!KHI*ht?As@Yu|;ui-{l?irsV|N$W62N#?unq&qNcPtc zu@*Q&Hn7XnYD>=qE9XEzp&~cfCpi;00$9j#f!)5eQhC1W>~C0MA;}L`(RB&6^tp7P zR+D9dJ(oevffW`?)4}TJ>&okS*PahxAt40za#shj{;T`#v}!N`_R8m5^8Bh~yic!v zeu$YGtda+;t^Y&Cv9XT}p+me;4OofMT-Ek^@)fYcLX-(saXAzpw+Z7}!H&K=Ok%0m z7$3R-F=EldJ#5F7Cek&r7EPd^5akBznm2wRfQ1|v*p+b=%5ELEs{kw{`N3LAQmGGb zJrV>?2iKM$=VquMfQ8a@u!n{}lexVs!CPb?Aq2MD!I}F}#cdZ+K%E=qmfVEufs`^l6Yztr^$^`q_?;3v71>;%4KC+@D zT}q4aLJ5d*f^{gYCEYRV0^ZXFQEsqDjT0RKEabSr?sP0yUU2R*55Pi_A8g0Bzo-R| zOU(f+Ys9g`w02ZQ5u#Z>WSq@tQ z7|#lJTP+94sV*~?2~3V{OOTsVS9+rHucgpWs7Uma_NL3>P=+pmg&Y^yo5z1CyDb{H z7r;W2A8gkHaa51~HlbQgmI=1^xR9>^7E05>T5MCv4o41<0a!=~fj#PFB{q*t%G0XB z1lT1T*T@a#ea7!scQxwOQVn)zL+&?S3H|RW25wd0k8)IA^F^;%D>c}&JYeHSptJaFEvQKJleWT6bT4oKu#n>d zE7AF`6rb=p3M(um`N1l8*OT_vuji}PWSL+?94DIsSSU>gd+*gdX@upx000XKA+Ywr z?;Kogrz2Q+1){+O*!ayB@~Mrd`oJ`!GUi#U!DjM+wT-!_==gnleeI(fu;n&=R6V+F z_yb^}DiiFaRyT|RER1Ib>sC`&(k0FU@5_T2=L)+p`xlk#R))8E8$BiZLiCdc*1gsx zUjPd^F0esCUz8JujO+zqA;}N6ET*CKe&blY_!siTWSL;MF3Ge4un?t#&5Rl=t+D=I z8Gwa^5ZLRp&Nw*vrQ$bT@CrnO39zjt*JUS_IUPXV#hGFoHP}KPu;KgeD!$(L=%#&C z12)pvPSso24u9hSsxra4y0ys$urQt#?2^n5k|obR;0JFIBhDdi3Bt_{q#+J(@K<>t zO7xQkHq6VmGk}F07g(qHWy%X%yh8viB>BPi{pUv3%Fdb9wlVyUPGkB3JfQ2X> z?3$uO(jT3(lK?Cvguw2e-XzKCqG%-SVc`{s1`}W<*Fxov{XCC>y6c8N+pEE@G2!0B zMiyi%Zd_ivQ~Rg}tmWEns!)%+cVUHvs!Xtod67;47RIxJ&8xaD{wB|xCvb#pTY{16 zb1BEGum3w8rXYAQSSjP<-@M4N*GS>0)PTP1BmK04yYgz<%9d>&nj6l}fD|On@D-qOH8SP18MaPX9Rgby9;p z%mX%Ie3l|0F{7ULQ4Ls;h*Bl!I35PDP?ZVxS3i5aS_{Urf=zd-6qmHWyF}m!*})c2 zVH3MsLO-D*H`q^hcdh_f$Z>()lUb#-Ebp5SU?Is5c2XiyCY)57_dA zJBrCOBaZ_I-lzubz*i2cgEyX(0a%DK!OqE%_JS1_#*u*&`*eRgPq@HJ6=lwIWDjYg9_#2uKCXZEF}5CwyE%;E=zZw7C0U1zfR_s zz|$~26~IDiI@lw*FQqy$9nt_SB!s|DU3$>rbY+jhS~Zven_tsk{%~R-E;OMLXHdU?TqirGfN)g&mKXNA8c8PiS)_GWc<7b^2B7B zV0R@<%>=LzrGq_oucq9fyv|_&3ke~xff;ATi7s3EXw_f>?1@{W=6C5UeeSvfKh}bT5ZI_bYaJRrPR1<(yaLf+0&H>UPuY>4a~i=k z`?`GYr3M?;i2F^KWX4U!4_kBml#@5A0c-0#MisCBxF3LpC=+b;(u^Sh7RIxJoicly zOh6n7UDK`~)ix!QB4)I1cUdyCn0Avgy>F3ji!6`N4)* z@1>S>Z;!uK4SC)z!P8e~t^rtx(!my7&Xmq6-{%5gAt3}-e7xAfVp_>ftr|>#O`g9* zesj+Crf^OVfBP&}gH7iF8~5_2;`z*Tn<1*F`-MBI0V^?bQoS*p@e#m6lnM4kt>d^Q zfbpzg&9<$TjGZGg6*xjRu-n^MN@afS@L_OJksIvFs^~ZX3pp;ZuZrF)+ibJm0bn7? z54I%a9+h-NAAchS^1NVcmjo05ScuZWUUxQ=`;~8)1z;f|1olhqL~+H9b>9FiyaLf+ z0<6yN)AG*!$Kac;dPiqV)nMQ9fE{=xP2rze2QM$=jcUM(M7>q3*RR4KmV+o0tmw!1 zbXZ|wJS*6)hek@|MZ@u15r`4z5I-fT-@cLbc&`cTpq~&W`bpaom`!UR0bn7=1@>C- zZKZdxZ4UqoNq(^5sdmyMlYiqKmyjnW%iI!-U!$r9un?t#z2v+^mb4)Qe`^*JLSX+M z%@zl@Y*wmOg9)&Uigo0J+xG7Ti_oAizvXJMfu`Jh*#CfiwR-#j?V|v;@jY9-9u}%H z!EXFAcLjij@vLBnj~*;J)^Ge`fg@yFVL!Fhm;OC;HU|0$6}iFYcvPDMSjcgK%?o*_ zym+;+4uFLuKiK??Q`D~B75I?|tK$Hn~UdY~Y02aoxf~_6iO;TF-d;oxj7;z49g5t#zK%ST^6YSOn_m%)yh|7M zU?Y8dtLo;BGJ+KrsxrYE7NoiXSQyU=wnu~766aQ4GX##1ZA;LRDyQDhHGBd6go@l? z%iR9$e|238dKjat*< z^mphdR3!RITVaP476k)X$Z>(aYxz<6B!18)01HWeu#47QqKY%yhif%i<_cT9bNxa9 z3#I8`P42`=?~m>M5x_!12&}JOWAXc)!Lzh#Fafq@h@D)o`(nJY;?2VH;cBp(8*{(u z8Xc9Xu(z+Z4LZad)qu5JD^n%r9n%M}5M_eR9eZB_U|~Ef*gZvUB*RBW*AzHHHn7%) zBB}glAN=9~DsqEe9X6vMfQ1|v*qrRo%5i3gbpR|R`N3w4{YX7Ne-WQ+0(ssQcHy}N zEdeY<>0m83eUhqPc+>;1kPrf!=vC@4_(_c}0Jh&c0v^#|0<8SrXnEg}_wi0b?;&SL zsli6^fOVgir8t?m!yh>CMm1m~eQi{sx96S)un=W}Ju+vV9e{=LtYFJ4|GB4Yd&i*y zN5}@&{k@K~^M>E}=qIR1^pm#2DpoW$1F(?e0=xWNnbPTU|2zN-Ndd5f)>2jS3HU2| zkmm&(@bWbNnm0u0VDt6X%krkbzXo6-Ap|z?jgi9@@1^)?9e4$z!35Yf#uMa2mMp-F z(xMm7AFBp?g9ogn^sb`e!=3o1i#JMut)+VHIBX+;g(ws3#oGn-0W6GX1^aP`gT!ro zD&7+TG2$HlSDm|`>r8(SA8*qmcMYT#c2YA~03b^AlLq#2;&ML#3pp;Zb1(f;Qu<~l z02Y$`U{&LHP?a;IW8tq8^2B7BTY}e%x0%2S3sE}QsyB}*17|zj!$Lv`Y}>+3iNlhc zM`_hy0_@ADb>+G{zTrh_XXa(Z&U+z;Hz3Hzp)pt0a%DK z!S*#N$D0sgJS*6AhslyAj=gZx0x{woBG~Pb22z8d?zN$x5akAIw`iO`fQ1|v*ljOM zl;K93B>)zZ{9p^y+EL?v9l9-WI@JH1Fv0qE3%?3rp)?)r`PnjAzgu(hu31P3fz4jr zTr7Rkyb(0Gfdv7NXfOeGVt$<5s`sDCFwIlJhbO7QR`P(gl-yMejolxleN+SX(XqCw z4KJli01H)_U`NbL?*J<-jAsRVEB250_p@!@0!PTUB^YT?LY+GB@CWo0DiZyqt*{Z7 zHdq5#$Z>(~S@WARuccKIfQ2MK*sWI|P?IDMO|_aV6YNVDT?7lI>0qPgE|ca2$GnFv z0VIUL#<#AWG-_`3Dy&Hs=g}|TP`aGu#n^jJN(ExYRY>zbFC)J1p8MM6%H#bl%|8V`Z7>@X^vMv z01F8ru!q7T9g1@g*V3xN1lYgze#y7~U4!3VN(OJArUo0&1J?fgT}8jA3wlF`c%vGy z5~D7vD_uNm|O<1kmLs&H#LhYnsFNM&VxL$|6ziSKX$brfQ2X>tYv?x)YiA9 z6@Z0=5ZJcwz580Nez8rf1`}Wtd@bb%E=%!2!7Y%A<#FLUYnb5;1; zy-<SmALoPkST5eE2CQ?arz-yRE-L^FQ6|`?sR|0f!gyA&ljm-dY@gG= zkHF;ER@jAM4WzOYQ}9tmP>~z#y4RaZ04(IVz}i0hs$6&YXcGVnNq(^Uc8#cBLvziv znk*A+?vdlQ0W6fJgFW!Fr=#ziVLAX75<+0}R+TsmNtkc~z``pK4JN?ap1dhP)8hPJ zm}anH%se$%B@bBVze_ z^6=l`Ixx*e3;TMj!9L>w8yb8~kuy(;w`uZ5HDF&Y9jFTE)i(#gLX-)1QTL@;02aox zf;F3aN^-j@tAW7e*jCs#(Uww&Up_|APpHTZwx?NheB37FxWJ}uc&)tDJ4FF2EF}5C zK6{@-?W(P z4JN?;ZE{)Od zJHWVDS-q^F0f2=hKiK@24WyZc!)01cmI?Oz%^(K=3#I8`Pr0T@CtkXH0Kh^*2<+Q# zcH%u7U2sK!S0EZpfHgiaUhX)hb2LnIx3u*lHQ2K}U?odcisZMB_(?TyR0B3{fQPE+ z0n=UjgWJw87RIxJ4QV8k9BFVCKX`)}aSriK*YY%DX_qD24*^(+ z68)rsy)l31JpcExg#S~ZveYrp-F{8zjiK1O@X{W{CkU<-M`#?4Mu zEIAdX57v338nDix3skMHjj0J>AxZ-)ig8+>?Tyceh4HLl??l#>C`<202pl2X3TwSV zBn=)i1y@+8$PKoIXfghDC*-)mcDnLSIZuBhUS0@Eez4|uYf9hy1s&09vP`gr;|{a{ zuuz%~wtGh%+2wH7Mu?!n@CrnO39z-q;qqEP z=AVOenlXQ1pc?F99OgMWXaVhF(oiLh!N)yw*(z2Q)!FR@Waqgh!Xvzf&CEEIR>@_kmCXydbw0tt17o9 zfQ2MKSpUvDsI4{Tm}oUw<_g=Q^RxW`7E05>N=Dw0b*USHcg;dV2y7jn>Ehh6CPi8` zm;h^%c1nJ=;OQ!u=BYt7R;$4#^MDN7*g8k3`v4YlTwq)Kd{yqg zyt_7lg(N@Ng5x(O({}~d)@rg$utygk#=B;rG#%{8kCarj!uAWSu#gY}n>4eoINYV6 z0>Hv65Dg~4epOtMkLvVgFHCdK+NiZ^u#b7bmMgC-2F^;vFFtvr8n6Rj4OMlY@GAts zLX-*iT7Sbc02aoxg1y~#yu^8T>_dUcv4QP)O;d zo7V29a{JOTP5>5?{9yO?r>I#fWBkw=^29$UOt6wVGe^M+3sE}QcIQoH-Op_*0kDt| z0_!%l(qYKjA^0GT>RkjpqQL~%s^!fcyR`ih20brpj6YTWCDK`NujAsSAS7(yM$3Jbgz!9>6ow&T7wD6t?pGyE0iGI?+ z*83ZH9l%143+&L;pUUZ*tULiMB>BOHq=~7SWkGnQ59E2lCUt1^0>DC)4z~DoGwIQT zrk?>UB!s}$ENLfB9O&H|Rs?tjqQL~%UN*DjbHjD;n=Y5;2^-a5!TUD3rc zp&xMIjcUM3jE1XjZtb-kz(SM>wyTlHQ~(R(S;4lc7be+h;h-mQglu4!rdTjl>v`RnpXa{voTez5C`?o-zf?Cz=6WSJ}Mx;7Gg@(Yxv zgT2yamGo7u(m?z8khVVYBZPTHad8^Z(EeQSy$ z`%pUGtiT)9fVFj2s8Sry;*WAblnJ(b{WJL0ER1IbYc*t!q<(C@X9AOB18Z$)BE8Vh z7yAhnxxscDpK=<&LXHdU)7a0-&f6P)1F(?f2OE)6L2Y*%gtrJoo_B?H61O-8D=b9m zV28B#lOFQ%i~z8Z5CZ#X>?HBVJuU+P>{Wxw|AR*~m;jqMzll7*;X+q9r$>4>2vdVi z=L5U)h9V;U_BHLJ8n9WJV^lu5vA1A_g{n-jk{J6?SYcs2E7&QWH%r8wPEHg!LN>5( z=9x>IKN*6L;D?GtKWQuM(egi+04(IVz?!=iD=(WGoCmOwK@&0a%FA!G1ZsS32jDjU9l6gb>(S`G>`|hEGxf*cyWfctnEy-mwA;$%_&)qVmg-ys501HWeup6&kHuby6t9qnS0EZpfSvW+TW-Ch z)kQd`f!+J;QiBa_&b^0SR-B^v)-4Ku9)UNi0V@)XRCRAL#}~jtlnM4yR^BoI3*%YA z28NnRe!36CFOMNcoWuXB(>zGS<=YQx*WuR&umC`m=qC;Aqy@_(0W9RWzy_y%Q`Yn~ zXbxZ@$q%;9kw(j5kzgup(2ta7-} z%C4(c4JN=geHtYX{NSmCX&!nSvquf~01sGudzIp{T}Zh0Q4Lsk_hG6wlaB2Guuzo- z_Mfk2*SYR)2w-76E7&}514)lF+cyXtA=?U@E7y^}iQZlb{e+6#U@cQ}afO8(7ub}J z&y>0AL-7gRkmLs&R__M2zD=F)T1}P-Hm>fEsKr57& z4p)_0d|d@AEL3HJjgvbi09Y8$3UfOzY`9r!ItoVT{bpN;dy*uOYNf? zu%W79D(7`=i~uZDrGfqDtJ%bf{XGFJjAsSwlWHkZ#fQfU93dN6mv80N(N`h(U=pav z1NLzt{?;tyxWL}3F8)8p?mVuB_WvJvNl|u^y&~E7EYUe<&dH&&Bt;8ZZj>bP_fNt(xC&53I0|kOF&hih-=dh^|Qh zc8SS_{|}F7Fab95;z#AWa3B1Xpm%KO0S(xVt%NVSQpep;w~nlP13Dxc)q?f)b!E05 z+MEJlA<6|?anI}ufQ9kAVEwmrkw3|}f_L^nj97H=qAPDzHR=#G5$`2{DA7;W3LEQ| zQ3F<3$O(dN`i3_9aQGsCg`_yx4uPJED?fstNgNK%UnduAPvvxcJ}i`GgWa7UrDQta zr~t5#kOEtFx25b+yR~xxENp>jFafqhPbbxHpH7cqnw>9O9@Kz6ECSa1e45(Q-v+P2 zMWb4<9la+pE6dm6!{8vw1>3r3vy%W8#`A(*7ac4=G|n8q+JKla*pyn7U+fTf=qE&p zezL&cFLT77c|%SJte4{(dVb^2ZviYM#lhBnxk*uWW1!UG5CR+2*sVRRuuz%}w#MYC zs+?ZVRsa?fQebcI=pc)l-W?xa23sH+On|*;;-|WMrOS2zo3bu3UIR8w1ZaEZ}el@N|pAp@_g>uygB0kEP`Em*lpPv+k@+g)IVg(w%SUdXx<01M-J!A|bGO1^U5 z7kvFH#E4_~KXuwK4zA}nq^iE(#~b1yO7xQjcFf(VEdUmBLST=Dy{CsRyJG=hAt?cN z(JaOMq`hVmhePO;U^VSW16U}{20M7lGOB6fz90Y#2`R9j{>+d)`!?AZRs`4r(O?4X z&t2VBAx&1kf@v;W@-$Hcc9*&EMc19nscL2F6FuFdTClFk3TE7#THyc|s&c``Pb%I7 zU|~Ej*tcB=$_G|!Jwsv-`A!L1jWVDn3~TWR`Uw?@ezL$0OE8%UU?C?2*2u4n-n9G; z{sJqt&QBeenb3}0Aj>3#1%Hs#fS=tSd5>#KvWp4aZbHN01G)Gus;9& z;^6Jaj`py^LQ)*8a`!1kY%5RvcLI50vRtrf2W+|nSctO0)-LjD-kCY4 zx9l^3g(w&7fd)&J02apcg5B%wCRe+i$KU@zj5vk}*7LF<_1bF%-uwblqMxi4cE~Q) z-CB?n0=vCu8C`Q)k5vE`lHy>ybn;b9*uN!0;z$ae5_ndWZ3nPWnhiG8tq*1L68&U> zwdq*02v%6g34vW_@{Ud((-?o#1xazR%9k4yNe7nWH8A9f$#PfNr~TK@1F#TfgKhm{ zu5zGH7yKL+5>jAK59=grC|`%KpNB0F4JN?uS~Fjj(P+jUP(ku#v;-sMfW#T@2Io?3#U912#?! z?C8tt?BgxE=^oXB4Ul(b+FQ=Z0kBY&3%2HK+YJB~#`A*R(4el|xm;-{v4?zMyC^;> zTw2zx4gG|Q!eHNxc{vimLQV+mFz3&7sg3bf01HWRun&D>6H}aQO7xSp!iFrIl>uNOCj_=lmBf)0 zI)^oPU%DT_LTNVG>i^uO&VBVa1+b8i0^4-#3A^GZ-OY4rFab6*Y^jQ-m~)purQt%Y}U6Ivd)$JHc0Ft z-wGRi@txw?FUud$PpBviHn5X*D*y{QA+TfHRncRT=SIN_3rTUX?Rs8TYGi@E1^S?twf?)uwOcOFvs?*D*-G-xnR9wa`9cWFrF7|q(y%@{lI35 z#2)g2eO_LT+TWn#UFauN6b8F`p$lGgK~4zl^WNX-xN7Cm02Y$sV6UbeQkYJ;Tc*=w zxnM7y```^=p)?!pgMW7_wlB58`(Ys=1-5AHTDx_|?f=oK!35a$-^-PMKl|>1X@1MC zo2~&HVJUpk)$ul?9vyuc{|AXiwO|t*T$#Xh+v5NhqFk_5uNU`+6&A+xf~_{FpIn(d zca+5B_`u$|{ax{3)s2bJPpBvi*3I*J2&}M>69T(a`GwvxudE(`g`_yx;O3!XXEm+@SjY*1y>9!NK9w@EI)H_wI9TPp zeTvBQ$MMN`kS8X~1*`mQ(m0fSlP#;IyIO8+vG%~ z@~D@=VOWH|kDq;81NOEE*tpHK+SK}to92~lCNYeIV61F(=20(;}jACzTRw?ap>K6of=Gl9W!H^ z%I=~I-jrt0szbI0>}wIQss4<5L+hE3phKcjEm-gHq0B6A`zrtzqFk``@889{wO~9i zSjyf@9y~&U_k%!85bX1ELu%6K>-Nx3hzf%Z?6DBv<_$R^u*bK)qFXV2o&s1%ii0hZ zWhus%t_hMj9714S#|Jy%3QHnjgMAiOKrJ2gU>ksios|OHH@BJW-koRo6B*b7(O?4X zwx^R-kHfplVVVnH?8()D4Q?%b4(r(9y82AA>ptD1TCjS0o=ljY8Q!f0Rk>ih`CIOX z6&A+xf_=Ysko>IM5+8{@0*8`aVcgFYQ!)w(e0a*ou+=eM*qxlm#m+ zRON#Gv8mD>z`}T5u$?o9$h%x`fOn@uOmKyLV`)f5eXYI;`Uz2@pDeIxmnONxDFNh! zz)nc{LR&AqWDQ^;DGqj4we^aEvLnAG4u{YRYc(Uj9)N|?Y_NX!+9IyIO8YfxNY^(t?|ZkT4Hy1@@LU@wb+P4>O6uI|yNx9(9b*gLmfnLdlG ztpO}l<$|>`x;qfS!gyY=2G^tIp6#~b&!4o zM}`AfsLBPa?>MM2fQ9kAV0WDuBu^eVbce(q@_~I`UYqKhb+!@o6DkUWb?BTi6joTs z34tAS>?3V{IpHyYg`_yx9q$h-YR+sV(`m9?uu*pdroajdrP*LxnnzR1naiI6EF`4B zj(rwscfY}Oe8&N7foL!Rw#y-7)x+)^ePNnK>S{$Au%AT0I;yU#DW6t&@3&}F3-(I~ zN9Iq}l4$@IqFk^?8@_r5U|~Ej*rCI($d5kC!6&~!j97H=Qv#chEva6W@%T*_M2UW~ zP6>>6+&ThaAtwa(kwL4B z@@0?RZvZSLq`)pZvq4tV*ER)K1lR)6U;?biz_+SB59+>vX(xF<{`#WKTVfCSR@lIt#?-*# z4?CcrP?6{-3#@C}*ckv8azbFQ&8VOgCZz8Lu#gl7J7ZaiLhTfbk1B#Z@z=>+VZYsP zjn5^3C>v~*_bTd_(GXVv3kfN(3mQAg=3a1mq*H?luvSx)D(}1B>cTNqMJh`)V2_J{ z^>t2HGlu%(b&qPn-nl)IVHO=924JBo7i@F;?!N#mjOPXW^UNW6#}VD|r}_{hjv=nF zQIQR(_vO{`25yK7gSGxJ{4s!qoDkU6dX;qlpGElq7Lwv%dsk0Xc-Q!h&lZI|FQ2zPLRbKxBGFIQ3cKm(_6GnKazbEj&R5VK3(C3ySV)S4jr~)D(o64+ zU+Y0$6l`a!;#U9`qHM6qpFdIbCnvn@A zq+V*kmP&x#KhF57?oj}{Xlhj~fQ71Duua^8904qh=LPGtzNP$l>5s`0d&mdY^KwmU zu5UGc=qFSZ20QEV-K78)azbFAb}y!vUp|k|hlQj#*aJzmsGUCXeRY~FcZD6Ya_~6- z3#Hj$ySNNjZYuw>5LQ@7NP!)HV!EuTXsD4+4JN>bZgNt6e=x`uruo_E%WDnTl~%&% zumOg->NkH?Yjuxm!KQwm#4Kcjy8~FL$_3kEeXAk>3*&jg79KW}+k`K)k=R2%ur^6Q z6mA0teTIHQMPab17V&iftVa`~pF&_S)_+bv4c)sFR#-@igDtLqPiFb@-~gB`jBjv-`=qWv)(u2E!JJ1`}ZEwJYsATlc_U5?=eW zsayj#S_Ev#n{0LAf}?ofjA&E~R!?szV?5zeHvkJ!F4!|M-~Iqt7|#p#(ohR|NbvCv za10?v978;ZecoB0%JnJ3YXXQ8{bZdIxGMeb16arjf!*O=$NT(DCgMt=mbFrF9e z$f+CU`HQ>b{jd-d1pB^mEh^A^=LF~{M2UW~z+QJNG6ArV69OB#tc)IcclZtf3rTUX z8^b0lw%rWCD@@1}ljVZ#(xcf-SYaW`2K&@(3pFQfet!T92`R99?mNhS82aJIFt7!p z!35Y&Coih*#f5tT*ehdVsx)BpM8KBZ%~CfnT#U~p5RGcV=EwRoQ@VCO2w)+~1$*4w zsT{z{DOrkLF0;{!O7kQW8}c9l{FU?Iu|n-toaqB~x32C$Hj0z2hAC2L@H zJ`h#}*aFdD0_+^4cxCzBefZgWi{W)YYQR>BfDMYct^T+?9dAPrjcURA`UWtgpE}~r zFA(K|JrUdtKP7DyE2Cq#*UvcR76tg|1$ zLQV*5SA%kTN4J*_02Y$sVB16-RlG1Qh|y`X+!fY*;qD&*7D}_h?r2us{=A#TFaQe) zDX;;r&1K6io9u!HFCRz1BN|MA{c&KEYVeUwM_`(toI*cqz;0|Se9;w@m!*#R6B`Oq z&oLrVE!e2Y1F-y`D#!c74zB*npIejKNoTLP82`g?*gNE9!ztt#n^8eu!lv!<~Pbw z8&tf%u6tAq)-`zn<2!4B34n#FT(H&WeH{y6VLUI`X~8P__JdJ)S_d(~752M{5jE?_ z@O0=WM1{e|jaV8DU?C?2w#@WBoo95}3BW>99PF~%HK^FCdgc;`L-W_k1-q*GTo(Wf zrP*NTnY^UNN7iltD=Z|Wz}}Mem!0`&R$ZqC6JU=o!4oyT(I+3AAAE~ zp)?!p*)4j?`jP)+16W8%fqmQmn9Qcvv6DJAm;k$I+CWw9&L7voG}B@a{?>pk76B_? zou{5#ciB<{#)7-+#jaEF{Ij=6M)Wr+c@@TRR|6{5#=-_0DoQ z0AL}?2K#!+GRinEp&x*SgcMkR_qnp-n_X@LSl9y5U;^yAU9XgVUX9a(V>)|s2fZc6 z1*-Zhe~E#edtV*8_Cv7lQ7zc~*nNzx*?}Q&N&r>4V6AVzx&$jMjOPV=v+n}=T9tE# z#2)g2J#6qzab?)Ztv~f6FucMiDX@|8KC)VCPdwMD!35YNJ!h$0!@cpd zsk0B<3^icSh=6r`pRe}(Ydi!vh(@(w!|l&9_YdC91h5e00XsAXe{lfgdBHXtzD*u< zWm<^D9`b>G?pKd`$Jpb~=Aoi6*x_$|@WpbF69PNI<28Nm(d-&P4G=T!0RVMzvr~@=q}@Y(gdjScr1L(o^-f!wL)IdBIMv z8ZQsM71>E*5Bb1eeO8xRT(sdT^b;x){bZdIG}!%oE3B}P69PME>?@jCxq2Ufg`_yx zDI<0&4*A<8>NHs{*e>CwV*xCbW`lk2UPzg=I2H_GAt42}f3*d&VT#>@b!spHcE|!7 z)i0Y?__HV3t+yr`uoWU;ZEihO?=$nO4;>PXYQZKroMK-4{9OrPA<6~&e9FBc02apc zg6(xg{?#?>5+$ z0$?F24)&1Ydc{n2iPYiH{B?4{mabV)2f#vUHrOM_>ZvBZYY+!uAt42}SMUK@{V!%u zpusVP1U#a_1lWHY_f&1nY=Liw%d?+cM+0_UJK=NKxM>CI{U6VD1hAq}Em#Y~vrNI& zsZjtHqFk^&vR<79urQt%?3S#4^1Oo=(k1qgZ-qUXtWO1ny;=hOgo;EzSu1SXgBooC zEaZg1PV94!Zr*MEM*s^+aj?r@MJN`(dl#qEWVv9wW<(DKuqrnK0UK;Ullm%?6Q}WW zSV%~LZ8Bo0to1A_{1^tdKs1;DoBV9N%5<6wem`QnF}t1yY@7(#FAodV^P5aP1|1TO zYQa|Io?%BYi$zbisIDus_3<@)P^LKTGT(AJ`3vhLqK*p=kgXDiZx< zfxX!&rz3!coDkUS%b(Lr{=WDJz(P_2Y^Nl})ySQ=!a|<-cftkRV#@Af01Htz*bnp1 zQy1IYpM@0`5>jBlxPF(Z>t9`gf|Jx}Az`}T5u+27_$j>f*HcMg;`Bqr_ zJynVa#}}W5enLf}pR5&j;b7MNu#gi1JL5|+y+2?Lz8o2n;$Y|8&QbiG+WWmuljW|k zJ$JWt1+Y+>4Yoy~6IEHiDLx+-5>jBxEI->_n>eCMrv?*X!yXu_Ue>A|2GhJf^>h;r z*l!|WgNh!jw{B0tmkNnSwO|t*E;0FYn}z^bh;qS>yKyfZz`}T5u+G;;$%9sJQcFyZ z5A4>qwW)r7o_nF6P*E7{wtMk~a7q9sfXfQ6h8*mo}~X|ETi4*@JB#liNt zZy>MqO2@DDAWuw|3-+Fu=Pm#XQ8w7Y20fKu;#af*u#k`foAj`@%<-`QZvYEhAR0`7 z4JzHG+S4Jh0@Nk^tkp^b_M`~dip7QMj;AM9=^oXB4T`wJ+)Ca%2Eam9F4#|sm_h&x z<9Wf3?PnuDYZBK^Vh{ON*e;4nMbp+PInYn2Nc58hmbq1Z6M%)B5LnBJkLY`w?rZ|E zkQ4{Is7WnF_0$^yI!%@fwpG6&jsO-)v%&t%y+=)mW%2Lz4?Ji{i z7RK{}opG>+{9*PpB^*PD5sMC9bQSikQcR8M*dF=`QDLx|;{$#ISjY*1H7hNn6Jquq z2C$G62ix{tp`z}z>t;GlmJ4>?s=9*#ER<%0?Pqm>$}t&y48TG{3hXM{&2Cea557eP zwm>wP0DI$XJyn%su?bA`pnl^v8nCZLz$UyaP^)IW!_Q$wqgt?0%}z7sv*zN1G$6_a zdwNk1y!i#j^Mbv;ppSgsrtNrI2Qfjgo=eLW39Vbc2Cxt%`pH^h_x?Wl1HeK~2yAvi zCEfmSK7L97NpY~nvx61K(i?7-IFdr25`3~AcN)M#X*SqS(Wj_$QRDG*SV%~LjotfC z|M+Wp_jPJ80oHKHT-9>==n9x--MK|=HDH4~2%p1x&n{5EbE^2HdsGWHA^i;F&}Zxf zSYe?m7wo5NIk>{YcwVsjs!(}kD=+-_0Wm?aTT6|ou2b~z*;)`420O;z&>6r&P6({+ zvS+k|Z0C4bVIe6FHe;rrVsh3YYl*`l1Xf*9Ga0}_X*Sqbol>YZ!(KIk6&4awVCTHP zA#?mLGXb!$1){+O*g9qVRXvv`bb)C$%}Qvm0lQxWY*54_b-UU9@D_K`s1|I9-z8?{ z_Qr1jEJV3r&z_#y0!|5FJTKVDl)Z9~jh*p_=nxYGduLc3YF+kfH|QrsiGH$HSo_g` z7Xw(x34#4LqmZ^Kd3g@NLQ))T#E&(K`!_*N7Hq!N z6{cOYP3`~|qFk_DYKBe$urQt%?83io#W`nK!F^3xGufT`F zK|%_wL#GjT4lz~xb!spH_FK79_1(H?4NNn_I_ZW-;ng0gSIlpQ_dN}|dKK%<~f?%)b8&UmDPn1JHAu0?uY-~8* z`~o>4u|iM+IOZ$_4wR&6+m=7RK{}-F?PKZhLG7UUWfB5Ul6rIuw)psT=eYqQYP+4ZE~~ z6&7+rV3Q7%(&~;%yy$|YIM~}io+#{Wv+zx-kS8X~{gj~d9`pME7NTshg>kp2H+S}R zfKviUNP#t*^wZAvTXzP?y;!x2Fc|=8nP_T_tmi)aOp;;%_oU zqgt>g9*NAD%l`N|EJV3r6O_jo01M-J!A9C!$p;5JSx8Jyv*_T*TJ>i9RrK2uRsj8k zio#$&7Ovg`U?C?2*7$1{U90)VD{x8xNpY~rYa19?%ftKw&_2e1%jgFUtD z8+EVV>#G135>jAWwWuevX!ad%;D#*_4JN?8e_U5}V*VZcP1m8VdwOfY9v1=Y81qP- zm$n`sH6j|-g0%=a%`_c-v^A`-5aog`Yf!fufQ9kAVE?Z3kk8zE4)4~27;y{{Y@o|u zMf*pK@M(|`CHl#_=(=pv<1~PUoDkRo=ZCcIkX@Ak7Lwv%&H5K9zWdag0e_v4Cnn2X zVZCOK(F3p$WrIC&q>*xFNyI4t3kfN(b>HXPmDrBOe_^l%qQL~%JB_SWhoftkz%+eb zXZO>9%@6_WYyLppva)oi?olmRdFUnPYW*4~0Bq(YqAC~c;6?8j09Y8$3%2#+Gx9Nu z;_!|;h!MvS!OkkQq{b+=;ZI~BO7xQjHuY5_9{>wEA+YiV59yix=HN>?ASn*^wO5q< z{I6ns7%t?A$#TKwo9<2kun=W~jcI7F98);s5`cw-6xgtr&t-$|dac2KVI%>f!35a& zBNeKp8|Rz>b-nvm_Sb+d6#@HYbG~}_#z}Z*qG(hL*72VdX4lNf$p99jT(B)Z*TBbZ z!gyY=MvAlYIw@ZG)hxt_V~AkQCbXdL-MhXV`Uz2@pDeH~)&+P2SjY*1HQV)+cKx;E z1gx--6bBm?o1s|j+qqogND5taS?+SjQvxW>20L|!4RyWKR{TvDB&5KuC=HW6HMRB9 zslfzTP7Ob9LD&uodE(fqsl?!%l zW{vl-!oql7u+w@DlRs;)P-=2~=de))CRF!vnZux;P*E7{-$$V|fQ6h8*g3XO>AUr2 z#sOGJii4fBE>khGrpZx>!yyEAl8aMwSYe?w8|={SH>t*6%4x8|LP82`twmq@W_vPu2>%<8j@702XpWU|q)L z&?AoQ*aBc7DGs)Vg%PzZaAI4XCd)k~Se=#V4q%})8|?KBamqI~S8M?+B&5I&ytZ1F zZ1#K=tO&3LqQL~%6=7B?-z8zVOh$+8RB6B_i+~LXyr-T~932cD5{+uXCZuOF;qFuC z09c4}!M3?S0-p~H<9WfB`%IMkdCkDTMu-WX63p6NkE(9ug%31_DA7+ASoi4O_!Ak( z34yKmJ&zt6YSje5LQ)*;_bDb+YK%WVI2H25WVv8HG8=mXSctO0-e{Mt9Jnto2*5%@ z3hd_k`((2Qv>gjzVGBfq39uD|>Z?|7PdEYUEXxL{HDL2Z!1_AhRToXqeye*_3pQ>} zI#XJ8zYxGeRW4ZL)?KY(g@y6FU~kcp@&KO|Qj_CbVXfDO`Nc58hc5kQI z6|llWP6+Ir38i$DeiIu23rTUX1H#J`D_(B9Byl)|P6@jGZR!hPp)?z8!m9_$&KHe- z0$4~$fqghYCi6e|tP6mJEf5VRz<$0Lrh2wwW(-X8ldN*E25glGSjXHvb?J@}TKA|H zY*e!wOydW``v6#|$_4x2&#>wM7RK{}9sRnc{AwFZd_Ee)h(+gr>a;)e)?4{QvB2lp zap)&RiGH%cKG5@P0$?F01U9JJ3%V+*<2(QhNpY}OgJTr)I-8A@I2=M?ckRA~A8SEr zHrPIO+9T$M59`;$>wPcwQ7t7fQ2X*?4|Ni&j2ip=LNfW@xSs^6E8oB z$?=^MocFIoH5+153H^kM!eHB2#6APCkP`yCD58j-o>H<3z(P_SY*=E1LjPpHB|1%( zdk#D7;N4~b7D}_hI(PY^GFks~J%ELT6xc~_>9SVKW+v#=U;=Ey;LWPN^p z8W{4#WVv9gc15oOun=W~O_{Jxxp^jy_Yy!t3hb(+0kZMC9BS#*U;=FNh3Cq|57WoM z-=)K+w=Np6#Ufx$EOOPg`akWjdz1isnYp!iuPK0qs$8%>13S3_SQyU>mfq7@UNTg_ zgTx;4t+3a3R;P-*zYK(aLPcS)e@<8QgcTNYLSUC2d_dQj++-Sng`_yxwZ65f6@jHa zb($;}tTJ%F8o)wnHdyN59qMGG@~N=GLP82`NXS^(n_9mjp~3sASN?x^M1u*i%g#w);a7Nvyv467IH#h7i=%2e|t?x2C$G6 z2W#&aqWBsdK1Zj?a=}ih-woe!0HxVrUrcJOsxjq$9JTKVh`N8triiIsC_K*+ko!a#%v-2%z01Fj~ezL$?xv%L3U?C?2*8F%L zZPCLw3cx~A9BkBtR#f9o$^|-2mJ2o})i@MZSSZZ~TiQ5Q$rLp)0kDve0{icU-m*n; z`tCY4m;h_`^sQ>p)cYwg&FPheo*J-c#K1=7s80=W!e;}DMzvr={9>4$`~Q{zScr1L z-VBJj31DG7FWCKw>*THG86` z8FU%ILQ)*8d-d8>sO#gdI!%@fwn05teC-jGW`iBG%Sw57zN-wtLP84cZ2cQDgEooz zIyIO8`?L8lmG1|K(J;*q^G1)=fXxvBYq2LwUGO*vpKmQ1)q>U2i)R*G4O$OiA<6~Y zwQGd|fQ9kAVE1mHCpWeajFXrgAJ`gw8c?U)H%49K-+pU)O$d@ZH3K`aEYq5rBm#(NESX!Hq5v z{s2}zo#>|!*rStDXoCp5SpXK2;$UYuA67(0{=zdf$P<(0uCR-)oWBWRA<723tA)LC zaNP~~jsr+YfnB{yB|A9fx-m2uwm>wP0ITkNL6v(_?-+n}3)wYM19n|k;d5B;_IK2J z4j1uDGSR3OY-%9QeD2ohD1e117i{U2hpS>JHtLJ zPOYfB%Q8(?k@viAt?^_vcXqHtCXD!C61)#-w7A& zGUF#}04$VdgKggU81++e-5XX|NJxQIxcszBTfP|I+y`4A8ccvqs>=MN!Pd4W)EnalF|YtYMWUZ9u-?6ng#cK{34wjR_&&`f+vATAAt?^F_7XFNo|oQn zohHi#>o>60MF0z>*ZKfZ^{N?wg@hE?m=>#KCaJCPUIN$x(O?2>Y5Ymm+^G$3 z!ZZ)MHSpDdrA5G|`rlNW>YXsrJ*ov;vLur^G@{!!01H*QV81szJq*CYcwVs8x=oXB z-#EIq#2)g2%~Lg?Cgs$_6&5NI{bYgdV{V401dtN~>u~G=J^pN?>9E2=QXH&h#dgKd z@X2`51$pA%2^Z{{(S6$hSctO0CcLszez>!F5P*e*6xesJM`cb9mX}~ffGrRWCct_a zM5&(rQ|1B3G|6?-G!57y5wJl;x77~)PvSTAqERi_por_t2v2_>01Htr*rfx`;yVst zJTF-HHNoIuW114GAf*jfzWT3H_Tc(W$`% zSd-N^RpUQ4#?PjH@7DLzfc+){*86Xk+M@ouSHM9uss(Ff!!Sd3k8B8FA<6~2Eb_x< zSYcs2FIbPenLfIur0qo-VI5SJVquSV%~LHE7jT_N(R<{FNtc zfoL!RcF3k%%3nwB;*W!?Ee!G3fQ{%Te9;vYoULw}DO(F1M59`;QO(kr3xh3p09c4} z!MdGXXa`_nJTKT)eI4a5{~3kH5MsnJ{NFOE{gmMRiRx6FW>${@EJTTZvR2qI*S`4b zPRI#?4Rd`#2j`yiffW{#;$VCIc%ulqTD^|M;n4hba!(0n^&hMcV4*Y{tkan1lq{~O z8i0j_6xavP(+A8Lw5Nei4JN?uUs6l;aLdenFwH9gL+5C~o)iJ=`{$0jk3ojL?olmR z8=I?)LvVHwfQ71Du*!`O8UR=r&kJ^jzl;30-#dJuF~kJH)(AAFGET=*&`*d8gSG0| z1fLHJIU%r5ZoZ-wl}}s&EF{Ij4!Cki@#Cz&oy6e~0(t5FRC+71NOEE*o4H}>av`LTcJa<)`>*5 zU`;$uGHDyCzW}fh<%0bXd~7~|h4H*#t5uGWe>NWcLt+p4P6=YNYEYR6h6O`Ep`tL@ zI%Plcr5unG0vnWBNgvOSEC;ZV6bCybx=``QWXfBeCd*x6cTD}W7FJj&%?5jIh8LAS zaAR!%3kfN(;S&eRT0L&mSEmLOV0XIqRUJA}h^GVxUc?4!z`hm%ThZ~3I$~?bJ@602Y$sU|+t!qtJ`3<0Nr7gjQISM|#5mER<%09n{3# zK6Cuf#Q+u(QeZ8Id&;^sc-vp61`}WlveQ(H9@Tb+X*y2qx<~^yxV!KH}D)$_0D)Psl3(3*&jg)}KF9UaPP)T4E3RR@hl%Yf+zkb3Z{p zp`tL@^}Czl6SyHK1a?Z+Gg^LV82)M&lHy?d?!K%@_BmCg(`30T?74Vj{FDGnv%wC| zxTB1#Y@Z2WAt43Uzr_Yw>tC^Lb!spH*6;f))%L4P>%laA?;cyC0lQxWY*cQBI?HA3 zDBYu4uyIv!jC}c=PXHFGa>0Hp9WVmG!gyY=fgzjZrd@`$me@l+u=QpbQTZz)t3yAb zqA=JscHygFg@v3D*jLKObm|m4{NezT;$SOWrz^^PkIB+$vRts^-!#IDE-1|gJMo;J zazT9D5C97aDX=r2EtDmnABh(Uumz&Q1laM3IjS|Xc}-!OwR(+PrU83d1guH-bam>* zy@zyl%QC zibOwIpAt;W9yJ`mLQV+mko$M&@>!dI!zlqI#lb$bEmv4Hr)udmSuR-R>|hHxC4kaw zu&@3Jx36fo{yl(&gcR71^axo={#HCCfGrRWCcwtKol@0!82uBbsjAy@r3UOn5wHPQ zQq|U}-|^n>gXSVpE!d!l3yg1nbq@dwQ7+haJsAf83*&jgR_Ue4>$Ua4b6AK8p2NmC zTT&Nh$Akk|h!Xu|fju^G4h3K#Cj?eqtANgEwABy5LQ))T+v^7v|9Uy#y-1KJCd&m| zUEbjffQ2XR%^h1 z5&>J%D^=~b;%1KSQ7u>t!wXE}^wypL7OHZ=2E9ue4`5+DFW8uXt@4)N_9!IwkZ*;J zac)A@9%qSf<$;RAU~l}GJ^{c&P6%ur`)72G%Xaw4cu0zaWnLIkzQ5{P=rma_*d3R; z;+qhmG#l)`15H$8niR|gu#k`f8>Dwpwk&XQ27rYv5Dg~4rf!N>$n!0BHM^AN+YQdU#q%t+e?9~IXP?Za|*`mND02apcf(_rSmcOk%ZH~kq z@`26MuT41&`t}z32^EQcvR2rlCyo9BSjY*1)o)lxCw_`*4J#}p#leo+U_gEFTa7pW zLSA%*EeM+s2P-T@*(pQZtbXH;sT~NFZQ?t(NnzvgxsqqW~5XQecNQu#%-u`o0nx3|k-?On@C#_r5A< z%ZA5rOlOVg9;yMGAp$nxJfrT@p*=qNMKr1f>-+K%GjLX;r2rP9T(H}Ib~6I7FrF7| z!^%DKe|ucP-*iEYIEMdQCbeJ92D&t%t`&OVuaF^1^pmy1j-BzT2*5&42<(XyC3ND{ zDT@FsB*npIS-w_`$k~!6aU?Z=o!nCbWsE-FzzwC@V2>J)QC6+(e+$4uLJI7+qzGA! zrfu3gRDEaZvFa=}KA{5KX>SctO0J}F#4ODB- z3hY>;G+7O|{%v$>Fab7c!zPu_Y}QTrF5e%7YrwATDSQqa^6{Gbwuvu(c`X{%f=x&- zW-LFBnhPr|M7dyH=egU%3Jc?T!A`p6B~RL7jw>w0h-1iFVe8kYWX|0$KtCZW4EA7J zU=@IcoDkS<@z3avbLDA;5_`yZ4y&iEPW?U@8w&k|io#$! zUFb3yz(P(4tc%}G+Vka$p#T<=;$SB>WE6vq)c7zs$cutq?b#|Dz(SM_)~0EYa@uzN zivSi9QefLf*vjJG5A3N^g9)%U)xWDcylWtXW18Nx*LDrqWD&5As#NuYA+{5Bk7~hM zgp@M30{%1wuuzo?cE!t+%K$8l=LK7HLSOlzfq{5WGsK8vh%4-Q|38YdjAO+BK(6PMd-+mV-PoS?&s3+;OT5z(SM__IC7H z>izj93jr)7q`;0jaNe$EyMJ%KmFu!AJzD)Gl&t#5W(iDs#BR4PvCF5 zASw)Ys7-_S02XpWU{9Nr(MjH8QvfU^#la5i{#@ZOx_gks;Sjp$8a*cs-_r%9*e0G z{&pXtdsGY7CaIKpW!&Bgz(Q3n*ug`Fn*vxE&kMFi*In{&{`viUep6kqU;utnEgIE=t;o$}e${R948TH^3%1T5`2YY5<9Wdjx<6dr;>k$-O&7!j zS6HWpHK=#{o|QsBAxiX<1$JdOGkmrd!fIqZ>M&2C$Hj0=u@?HCdC@l_5Gcm;gJoeN(mlbQL~svsHBF zJ`LEzB4E7}Z>pCp>aY|#BpTI%m4~JZFQzS(a`owxdcZ;^qhFxW|RkKs>bASVP?k1C^EKe+w?z(P_S?BOwM6@~WA@EREM z#ALZEY?VW<4}gUz8|=BoH&khHrgi`p5>jAGiYLezdKx~@6t+M#m;jrXZK=99Aq4Nj z9;@$rKm#^S1guSArn-G))D-|L8r6agw`Z8?>u1!06&9jguosqHO@i2>SuWU@Uzgb72B4AVfZ>Y^}|IUOCiAJ?xqatZ0>`V3~01Htr*uYnAjQ}i+=LI`% zsJlEMt^QewJ>&!XfA8rs_wW7+`Uw?Ozz!cYP_^2X z^~2IPw};1T!2S{e>z#i?O`94`fDVa9wP0;*(iz{y9clwuh;qS>%vt#jz`}T5usav} z$PX1a`YW-Ad|(4zOsH_{6L|9rR1^k#&!T!MfQ6h8*u;C;^qo_F%>XPU#lc1l?yo48 z$!F;_SuWVvSsnTUSSZZ~8~gV#RkAiUAHYIF3hd_hAu`z?qip~dwm>wP0Go5;w`$|- zY54u>sengEG+=kx2w!wX>8GnV)c3yw9TJUd!6utuXO>rPi2<+><%0c{xuPF{h4H*# zzn@sF13~Rg)Ga_KUpWakoGaKsy9TJUd!6u|%V|MhnnhIbc$^|=T z)uh1y7RK{}4RsEauXaf?l-NT)u-5AvQpq0H1E8N!k?1E2?0n}%E&vvCLSSFlEupWh zxUdYsLQ))T-xpUE9!wmi(`30|ZB)wfu);!VHrRij=ThwzMNR+~5>jCM9-S+5>lrvi zrv?*XkKItH!p>yiG3~r*aiRunjtJO_QyJ>MT@&z6S~RK!`+rX_obLJ6AHYJC3wBy7*;CUjTsjJU?ERTmJ3$Djr}bE3sE-M4y}7pEt?(0Z@M5M1$KT) z7g@q)_pUlMm;k%QrKalg1RH#+sCz5@(;Bc9B487`XR0TZHt!7`5{+uXb}UL}8vMKC z8i0i;7i_Lu!*T!%<9WfJXgWsT&`|HQ#2)gkup4F@Q9JIbJ)oaZQ5bA)kE{45M92w& zJu&l0k1w72?g04ppcq`;o| z&{;OU+haV3g)I;bCcw_`6tB9z++!O|b5!7_Ga9h#dJCV!I%a05{Y%2|F%_awEm+5r zvy9Sb3ck%7qC8+5PkahsVLUI`>kTaAzawq&7($F#bZ~_=oA6!H) z$Hv-PzzPdFA+Q~o7xeF^opJ#zB*nodT#Z-M+OgeQ;z(-#I=Ns=Htj3~uuz%}_RJ6) zO67ke5x_!13hd3igLX$RhE0PN0k%Lim;mc=z+5%=_d$Fj(}gyz&uhTOiGU4%lc|0@ zx}ObnNHnSiYh!bkae1tVH*iCg3pOaUR}BCQ<9WflXPd~6{Oy6CV?az0tjpRmh1-l4 z_%uj}68&U>eHmEr1;9d12<+I($Mn}5avH!wQXK5fj)xTo6JzlV4f4cfxnPSf^b7;A z5M_fs*WN)hT+QF352pkW<$|3OJE{V}!gyY=dmSlxa&vP$-+>r$ z3~_}$Y@kPZMp>o zewQ_1i$uWQ3BIY`;y4jMB@m5j!KMbDV(QmVGz72^<$}$e=Z-%@gz>y!YyR#lzxMe- zSBc5-ox>LP{i8VXDCG+D6DkUWy|Q`e0ssp+A+QFMO6g8|eog=ulHy>C8jMzyWS_jQ z(`30TtaF3)mtcj3(rmEaJI+$+5nuKJSV%~L9rZWKZeh-OADtRZfQ^aFQm%O48^66Y z?%(N}2JANxun87f>bpT!1E51QokXHqu%-!#j7OUTcmp>?xnNy-cg45Jz<6G;%cC9T z?k;=qv<_l|E3EyV?~2A1LHJ-2hzf)4R;@=H01G)Gu-hvh(NBkY;d{CuDGql0iq{Iy zDHnB{EEjB+=b5em7D}_hmiB6^EI$^2ukM6|6xf;;zwIvRov8${umz&Q1Xx9uiK^_r z0w0bN5qdO512&?M@I}}EJq(V@v;GKRzeI^dwP1Z;-eC65$({@=EJV3rKhr;a;gkTz z^MW-V(NR9T-tc`Ad&sxKx;Rv)0;-BeJFLatL7wk~CiU9x?O0&VX{JWO=uy{Pa%^MO@U~L1;WQStP9dv3i z0d`*A29+x3`5>6);zH{*4cL<+V1wG;R=b@UgTI;;jcUQlO>Q#If4?jSun^^fHM7}+ zU(LdJUa))oSISp+=;SXkIXrT z{je~e7wpP&PV$cR8<|V&As^VKA%@f{SumawKt*A&9LAxW@^B`76B`7n4?Z^*aPo26^&}a23(<;q5n>J1uHB> zxnO&_j_MDm1TdZ#Y={1By+U4sd0D?3ppXM zo1?PnWb@BP02Y$sV5?nQr|8!#^MOv2<$_IKWakWEp)?z8jPD`J z*o9?YsHRhc39unvsj3#oGPc7sPsQil(tr)_D|`-XaX&}B;JI^Y#0hQk4QVzOMYQ|mOb2e1%jgQZ)pqOw=K zUk6|zAq94h^Detr_a<)EslfzTCZUh&F0%{44h##-(tzDB0yca=p4u?0Gd}WJG^zz_ zlXR6i5NGujz(SM@w)aK9sQ?zn^MXBpeVE)eXU9u8h7co;A%cwwt476koIDiz2~lCN zP1=R_0kDu00-Jc?EXVjaC z7hC`=B&5K)8wJQZDq6qLslf!;GltDn&8`m}4b!}})g)H~_Ob}rgm-yr#ayRNx<|EO z!}3UmIl<>-ppU~%IYZ+mwF_@;eb3bSuWTEc`IAM3JXy-*nZ!a zs{&IiA^|KUq`mf7nr|CLn(|9wD=IEJ{w*6US<7{8i@oDkST<|+N)Lt}ig93;iTE;65>@Q${fD{&-+J|$?g>I~kk1*O?w z&m6Q;M!(uq6Tm`33aruncCt6!gBt=^*aFdD0<7uK@hUUt_s?LOeUJ2dpaJ_y1Z>A& z`D#5?e|%h?XjBU}s@WxGTzQ8X02ZQLuu1hU)&j6Fo)_$LJumr&j@iW$ljFPSdNa|0 za#*0Z9r_6siGH#!x}I&G9S^4jkP`ws;AuW>&wT3&D=Z|%!9IE&rC4G)b%ain<*u+B zHis{Q6&6af!8SD7LH)gUqzizBgcR6?8AdXr7w^C7)L;T^@1VM>CDm5_foYbP(+@RZ zH}@01=n8pWpl;W?BfddEG^z!g;Bb-YS>%k*hlMB?Y_w{f8GwcHykIRnm2%(iH>XQX zjt{I$4MS?5${6n@fQrIk_sOgN0kDu00=v!gIsM^4eNO-jNpY|xU||bHg9)&m+SON0-tiAUA9h8g zQ=tazaS^a_yB?@5Ei$s9L!wbF*nF!b=0M9|QLw^7lnXXb*62Hch4H*#3y(OGrA zB(aBlU^l$0LyZfqRUi5Z6^VYbR@lbVd*Iu=AtwYjVo4z#H>>MZ01HWRu)h?i6z}$J zxTn)(xnLbuwAu+^p)?!p=&QAq8|q#E24Eo}1$NrFi~qe!vDQGH8ccvqKIovbX}k0x zOf&9k?qdzu3=yzFX%E!(ehkLNSv0BzTakN)8K}4%0bn7@1#3OKUn_Do#}U?C?2_H>sgbdS);1^^b45@4OC zD5Bf=rb-+R&0i-M?Bw?@!2lLYv%yBcx=r=pWY7`7LP82`&hy)LDT7^ob!spHHg!j= zs@DD{fiTTh>ocEez^=3vK8H={{y=S=b$g8NQ7u@x$zjH5PkVgVEL7!!-EydH1b~I{ zykN~2c9AFE-*ir55BXNuJpF3aEW>(^&`+o+47OlU#3TR-7Ho)L1oQY(#UEHRXpO;bpQ(qDX5>jB3gHFkECK@pS z7Pde%m;k%)r<48Mj}7Yp*gx`1Z!}=@M8N75{|DCI$w>F87Od~fM5b$ZyEOn7s&c_* z&xxN8U|~Ej*a?xr@-NGb)=KOl-zmX{cg9qkx*cffCsZW*$vTJqcx^*p01G)GuqkWv z=w6#A4g;`|6bJjq=$&Fl;O3t?O_mFG02WHK!M<4^Ywr}1@dLm@LJF)&%N*I0 zRX?3|YA^w|u;o_O4UeYyO_#HQ^IHwrDiN^xe%WfnmOe+JL!wbFSR0$8%!oI(_*?>r za=|)G>WWVy!j~(7F-xes_%^2iER<%0HQdoo^~by!K3fYCQeY>ySSwp} z*akm0ge?#aCcqYqzoxoS)LstLoP4P8od)d2{=yesQK#;x2Ts`BSNEtE?3WI)OqKV` zBv@ggDi^Hr*^utA!oql7u!p`;@}IMQ;e#|FM*Nq=Qvw^C-wOX3vDN?>=L@>-nn@Ww~SFLI4XD ziGH%cHhKL|ZvYE9A+W;_J)&FHU}gYVNQ#4<)GJ)E_~alwC4fBf*U4RBpXAD204zk= zV6Dd|Dg9?pOaQQukOE7MtCFRz8j0_kefgGvM>LoK+jh}q)q^b?TEa2Cy1n3&25g!L z*wo><>H%p=Ki#8Rut5>)n9q*~E&;Gml?&Ft#nmzZ3*&jg>OZ%X@7-sLU#~-qIEJ{w zn(Z^7ZeD8T0$?FZ^pgd)ZRF8w02XpWU?luDe{_Ql|zJUY}*!EdZ=&R0}pCeKqsMw^a=Q3sDwWz2gH%n=5SrER5#`ySk=Yp0lyI zp2QyVt+09e2Gl%iAwK5;Dhh+G?m6``fQ6h8*tT>k-Rn$XD1e2eI9S($>eRvF*?2D{ z{t6bDQb~ZNZPVM59`;Ha7l@&0QaSR1rkEU~Bhku^m=e7|#oK zNcdoRj$tZ3B?Mx`qJyUd=T8_>Zn2?wdm%)H!8WdVUJPI%Cj>Ssq?ncs`C17pEF{Ij z-d$3ln7i;7K8OeM#ALZ(4OiJk0$7N$!7j<$M;S(L7z1D-Aq93v+n;vp+D!a^jNN%$ zOz;0c{-nj4Exbg@l6{XX%{eoZLH0xnStDDrW{K=1TVzX#qzK89rLrB9go+TML`tPX zktL$v`}>*OZGP9|tmE(NajtVc&%LKJGiR{_u&@Q9zy#PqC-jtW&K~auU^kCW`lkVV zSp;l&{a324_qO9rh?!GGqFS)-?laXr-n~5q9TuWour{&A_~aKD&kJ_$urZXP{oWO@ zIEWF)5WyOM|4mOw9(HZs8}d{WMMmU?Cv|)~4?>+u%M7zT*J4Kopn&`|X{9GT>nS zL|EoBcdFXzny-}g*QbeqUF`Hqb$!-J{NYnHss)?y-9`P_!0iQqg(w$nlEJB^&|zUb zFW7w+4Jet12i`RcF+s4K<3G|f_N3r1T@WSe$pZVuB6$>mg`5!B*}Za^Jh^KobXZ7= zgLSDek+denfFS;bs4Gf~ z1t!3*xNuid7_t~o2^@MSSJ!|o5drIOmZ|!?`;;G87maGcI>wGx2b?@R7{Ef52dvA9 zLI4ZndBH9SA3(YPdN5035BbhvGi@s9Psg(nEX+vMlLfX#-GVv*7IH#hx94Xw&33L% z0I-l02fLnHKpn`MaYv`ca={Mr@;C-yVQMzmP-8=deRrR701F8zu=kd?lU)ltWeleT zumz&P1lX|j7s~!F9_6siz{%TWQi6g1`>*Ru+z2}(~fQ6~qVB5&X%7-*QhA-uS zgcMl256fjPLwg76RA2&Z{*J}U1vY;8*|I#?v8D!WxCGehpG-bOg+!wOHZQw1K7kve zT(I4vTl9er3*&jg9%|T=nzOjaMu|P->#z>Szv*3rWVfN7FrzTovq4IHWIW`Az+Qiu z&OD#;b1i^{q&Qfc(kJx29{KnQ6Y|7gCl_qs^XpCk7NTshOj?ca*%6Iu!BVvp>NEQa z?V!U#lnXZMLH{=Z7RK{}{b+T1QQlnr*>wisG|a{7G$ z3kfN(W{LsvN5{{^I}TtAM1cvgzUpvA`O?vi0qlw43rsX%vqZp}{(GYe9#DY~gAc3QA0^|Z1bUabW&;ux~P{>q_uj{S>Y6GD`z zC+n18)V@7C04(H$z&_uY#eA{;_zb{8QXK5gpxN}9FOU0697&;5f;g`+j5vM_z`}T5uwxDNsrv^V@QXKy34--X%cWaY zOD}|aLX@Z{3vAy0xUB#dazbGJ&%b7rzsfoQSV)S4HMJN=k9b&s=dh3`7R&9h&d1f3 z02ZQbu<1WWD|)&)^#QPukODhve~_(7qgr_VCTxKyFab77eO=kMt6?mt+gK;2kp}F3 zned0MEo0xP9@73tb&qPn*2?IwcHXD#4`5+dF4*8peaZnWjOPU_4@#A7@>#TBVh{Pw zVK1yqrmJ%LQveobB`v6!N&kOcjpq#qj zGz~9+gcxxQ@svPM?-yOV^WZzECq#*QvcP_`XwekFLQV+m-)|XAw;JU!02Y$sU|;_0 zPOGmv*OoYvLZ<{1o1gUsu=n)b|9=E*uxq9?wwpI^GQJ5B5>jA)j2I?++_n&J^M)-D z1t!2QJAF#&lCYr&mKmI6)l366MFecibJ?neu133bk7~iXyLV7~9=LrFz{0Ftuvv>< z?gg+go)_#$hf3MTy_4}_N)QtS>z-ds_vl)V*AhUKs3!|-jB_##fX5ecQSS zIs$BgC@=x`w=zvJx!uZ9u*}^d2b*ia7D|8}VlT(%JBmgD?BK;){QxXPxnPr&#-ji% zjOPVAW4#^~653*%#Nzl)2{LUy)4OheONDyEj6^+IV8i}?-U(nKCj|CowHJ)xHM=AL z3rTUXze-QgWrODh>$F(zIjq;nRJ>~zre=f9Z`EG@!K2R!01F8zuzua@4;Xz~iI0c; zdX9ic6qo=zX44r(y=nFP!7>9YYglN&Zl;9KVWX$!sCutFX0Cfw3pU4lh`RBC7JC3J z%*qAZ;LOEq02apcf=zDuLZ)8Oa*o6v@_{X~yhA?^H|_#pVMd~!EU*jKpHTr=$O(a+ zdMTZ`JgY0~hXe9Rh=c94{h8K;44huWY2D>BphWzkH2mD$K5>jA8 zhJJ|OeMp7(Ai)-h0ux~W)R?X4zbqUd(%8v*i=_r^s0dii<2t^)rBlC>LzEqkdZfER5#`8~T0(<(JtFFMffT;3>h>vY+(-eq46}un;Bc$pZW4 z`t3si7IH#h-|l+POtE;2=dh3z2RrSV4}G?%VT8ot5IQArSp5JW1_x8K!CoI0smORf z>^gKIRdB*nqjUviV4+b*|2r^RwR?3!)YcR+`Q zso7wuj8*ddh?Ecj3kfN(F3uffnc=Id=~Q3>?7c;Um77iM`oc1us7F>BurEcx+Rx2X zElw^-(mkpL8*8y#ZP&C5-f;l4a=~_(W;_zW!gyY=!83YOkUN7pP0b4Et z)_+O9s+Dp@echv4usPn_)J|)?m2gS`vvR?nh&a*`z`}T5u)kaNqB0_KpGxc@A6Tmg zhVs9&&g09bVMd~!tPUI0xczVd3ppXMS$bK_@eTp_a%4z~gWa>^9KCmF@l>4_%LV(U z+m6uy7N%x{oocdCe)#hPd=nxhq`=mgVJU0SsmFHc2(SgBzy#QF&r=jDE+z%SGN;`C z-AMy>4=wzm%e8%>>U8l0eAI|&R0}qBM2LD$oiDin7NT6Ru71iW01M-J!FHR!o|;_u znAGC+I z)Us{={PF39umz&P1lR@NtCXQ#D)F12U!KN2G+^(Gfc;@#q*|nmY6uk)jcUPC+YhS; z*uNYDU?Iu{yXQo+g8&xB^MY;G#F_G$N#Xep#00^nZ!nU7iMwzTz(SO$Ckt$H&i`)I z(9`^j-nI98O~?s>{r4r6nYO3KOaKc>aj;#M1kfqf##l)l4k54}bWeO#5lqbn>*A%B z4@zxT2f#u?3hcO1yJf9>!&d23U;^w}^9bb!)fRm2yW@wAy)J8v{Q9v2fQ5t<*wvoHWS(9}FX&WY0_^P>*2;tvZ+5^k!yDD;qXD~KE_@EVWm2)~ zgI+kEG>JyFU`w9tQ4c$$e-^+(lneHovCTIC3*&jge$T0rQO)<_jieA0?63~Ld35B1 zf1XfJhzf&MPOiW=Awo_F>`v+pqxiLXG=PPqI9MakJUVXO+71#&QmDh8fAtBUO8`@| z!Deo=lskWl_5!ewkODjOLdAfldS;P26_@~P?EO?>^~D;0t{Rpd&{qTYhzQu#2<%zESIh~gTWtU=B*npQck`otl#gEPv{-J3&8syXFE50t z*j9v?z?AOZ+=<2P6Z~wT0B0dC|cPXAM#pMv;F`L*jN#;9hZGl zSx>)=_jHLywP0QA?NFDMFT%TKA<6~Y?&K>M01M-J!A8I6Lyg?~>pL7nhzWMsitRt> z34MRvgL*<#7;K9114jT0IU%qvEgv%((Jik4SV)S4HFDfY*WBiak2-@qu~;tH;%XPJ z!zlqo*Ha^dVavfP&Lt+p4I&8h7 zT5^Y(R)3(LFrzTo;OGdv%^Pw;U}sEw!OVMhW+;G#q&QfW-A_7c-vj&(ul^ABkrX;5 zI6mzN-f;j?HrUfMw9nJ z6bEY={fd6JWCnIv$P<5^+*5+!k}7=tJVe=GudnH&Xjd@~pREN6Nw9V!WCNWo44}Y2 zYzTNnfeEnr0q+zggZAPb2g6sosx)9DMZjk4C{X29KY*79iAJ?xQ%CGp`@Zet2w)+~ z1>33G$c_LO#`A)0<1mWa;>r91un;4TA$C}=J=NtYxhI!FJt0celLgkc%Hu!iu#gi1 z+sZJDxmh;126R|Rii7=SwvY~;b8?eTi{*mte|~#8oWsJ@Y_RSAJXF*jh;qTMIbVtQbisIDu*Y1|sJTxAOCkU7mFz?qBUn~a+ zDX_U0Ps>8z7~(B5umz&P1Xvr7WMzDKfdL%T_dga7)qs5`0(P;}dsW4uHA8fdYQct= zZdNNMja&&}VOB2K0>yMY=&&%J7p%$0ca)jYcKoIoV#G1T4m)+RnS9WitN#EjM2UK` zI_&Lu-(CO~azbD$8b4){{pL0Vu#gl7yJn$^-dfrRFaCu*u~;tHWshub16YW%!A?J@ zRQ7F@CxZ?P2`R7_ZE|H_6X{Hy3QT}KIjXH)(yI0wK;357@541~pu@O93q8guuqueaJYisKmF(KvEp+{;Ej&cV-s^3wdI(T(Aqqn)d{-5M_hS zp6w@JDZk(XU?Cv|HmbdYY+8;}3!Mr~fZbaCt)gvN?m_^&@$~Xh8nA&%;SXK@!*W%3 zwuR$4tY}mVw&ckswWIlwu>cmLT(Cc*g7Hm=FrF7|lF2&Cvv=%SiN*1q64=gZD3^U` zv=r(IGYW%srS{YYu#gi1`@3a25^f^EBwNFrF9e*sWtIr;DzQCH9aHY(=fQ@~>0o z;j^`1Mq#ikcI|Nnu#gi1+degpIbA+80>DC29BijzLwV|ie)#m$yHnXmQnOfYhrOEb z+z>h}MA=|}+V+!2E{U)Mu#k`f+u0{ZcE9!(d>9;TfhaHmc68%*$}5}Q@t3YC!&i>g zfK3wtYaNrTvbz)<4ID(HTChQfH>tPJ2wo0gA<6|itHX~402apcf^GDyGgXw;7%!B7 z7}0cCrvxTH>296Xub}}zl&B}`9CoG4_mcn?azbEB>AOrl55uDX7Lwv%|Gca&|8O=8 zucd@Mu~;rx=edcU0W3t>V0)hTlzV zU!WJBDRN}~^O1o77RK{}y>-c) zdUg1Rox~pUb=V!}_2elNGsi)i5I^>QXK5%=_Pc} z_1o~pa*!7VyTxhx9{>wcHrN)A*CR@nLX~69OwQOkh@@?@$I{At??v zvSI^0?oKuQ&;@x>u&d;Tc$+sw*KaTnRxBDXjBU}d{Kb>qgsuMfGpZs0Tx*ensSwT6696(6&~9}YyLTChJl98u4=t8f6Y5aoh> zU%aU|fQ9kAV0&3vQP=+K=>x|QVuE0YKGl;a+P1)V96(eU?BpesK7fUs5ZG^uD~z#4 zpDq9vlHy>eq<^71{YPEWX|Y_eiBs|d04z++27AzVi+uXjBZmkyJC4|RA5 zVB>rVctn8-uy>DsQq&rAZ#pcq_U4*y8nC}az~=PISKa+M4ZoHbjcUQRGz?N-y_7o| zz(SM@c0|o9s{kyF=LLJA`C@9W%g79g#qpgI9klb*daw9)BqNyW`lLPo-V)G=#e#mg@hE? z&ZFnZUc@ZE4qzAVC*TnUCcvs*_$hC?CO(8^-aQsHO9OWQK;aKvK@SR4^X&8SjswxC z7OboP5q0X*nm+(6M7dz^B-Tm>urQt%Y-l%ADk6@;3m_pT*kQdK3TfvBZhlZth!XW= zft}tu;5~F$$O(aEB2t*u?yE0BhlQj#SlOHNbaKp7-4@FQ8|Rq14Zyezx!0>wkIv|?{ZyG|2Z147ev6iN9U^|uW!P; z-bABXus=GSQ?Hs=(-pu%lnZvwOqUh_7RK{}{kNzgW%lX~K8Fcnf?$h6ztHbLvhG5L zC{a%q*wMWW!vQShguwPTPiC%}c9;%eAt?^l^y)2I@AuenXg!c87Rv>jonN^hz(SM_ zHev5wMK?$5&j1z@QeX!?dtiHT>SVm93${QMm;l?qc1@*ui9;ex6<#24G=4FW93|eWRMD$ahL`?UR9g zLH6r|&|zUlqMj_UU9P%r2e6P60(+4FPw0;d>VLUI`#}}GXKRYB!EshWD ztr^Aiti>JhTLPGos3!|-=yxY801G)Gus4oBW)g0P;%(lL6bHN8roDVr&!hND7vx33 z7C0X=0N+RRk3R=@IPG9s1|I(_fzUVb=+D3Scr1L)}6HoZ}W!nykHjw8d8CQ z=Z`^$g&1)R|4*Iv$uDaL714j+FpHs{5GCr#0&A|pXkWKVrvejT zD+g^*9NqXC-_vz(ip5e5*iaF$EuFroESj0%8w5n7TClGELFy0xDc=EDh;qS})acp_ zIxLLm1>5slBdR>X4j;D(G2$2^*mPwfZL=WlCe#z6!eCc=hv1tKAtwZOoBgZ*y{F6M zG=PPqIM}F=KsxAw$3gh(ggmiWF4(Da4yOQEh_b=fNSmcxxyvRPIxHllz&39jV7n>K zWw%ZRCcrMN*FZTjv`fIP{6c9`ct~*%*RJc0zjQ%f6zs_N)As^ch_b z!0s3nZu_U11%A;DTObNdfbG@QQn|9#a%@83@=$LL*m4oD)-hjIs|#P^H)5huEm+6c z2=$Jj@)`gZqFk^R2j8{@urQt%tVPqA)MA@`H32Ndh+~MS1hyUi(3T}Ff&nZN2C$Hj0-Kog&vtUqiDNnym;k%{#C&Cu+pjUO%tPnDuhW2y5&;{#yi7HC zPyamKqgt?f>#wO-JKWm^U}07+*p7)S+5uP?&kNRfc{56X&F4Q7d&md2$<(j((^7AI z-Y(223^pYF;uio5IU%q~ho3Pm>A(0b0VKu2wmr3#{xN7Yp2I?3w8L5r2xtpnA<723 z)U>(s#^@pifQ5t<*u6G&WVfQa;l(eo1){(N*uV28D^H!7`2~*YBiGX#HDK?HfOV}` zq}m=m0V^aL)q+hO@lb6zzR6<%3sElE1Ou~a02apcg6(&A5M^-eN0`Lo_`pVP`bW1N z;(rJl0L)0#lXXf!-H#0cu#gi1+uu8xDI59B1Uf7v#lh}O51_|89%!S}V!0jmLK`zB zfQ6~qV0V_@Q+Umqh?f^aLJDlRlp@=b%@+7e7i@tjFafrgVvO=nlMnb~(3c47EgGjw*;!=^4PR1I0WfYCjw1siKopg!2`NkizcFe?{q{e6p*04$8> z1$(OB2x@OcLS2bHiHhIYpH`r!xZq9sn-HDHg3fTbFKR4pES8J~?K8r6cWl~Jfpt3e$Dun^^fE&m$5 z2Ef92Ua$|&?V&c6_cn)P2r;7RV29n&y{#c=mA)mnhjP>@00u7Tvq^KAt43!TEbzOL25?1 zP6Z~w8l6j0rki&71j}@ad$v;pHdX|z_556w?<~(Ax<|EOJGz#tyEJga$8Ex_T(H^W z)r$ZujOPX0`NUw#DZgtSi9O`&uwH4^!w#;$TOdX+%%m+83YR40+^OgrzH;;#XlE&|rIUasoLfexK?k7~gNH7i#qC!Dl^4hyq# z!M?CMG!($XcwVq$72_!8`yI8!9`b>`_5Lq?*f<(*LWCKG!H#vh90gz@Cj{28K^)V^ zrT8wP@d9p$ za>2d}{n-P+!gyY=UhWjt&#x_>phJvkI(SNuJHNVoMYrT5&;TGx)RT2ekonig6Tm`F z2yEi!D@?-}>*fF!lHy=ru6RU`44B{mU?EQ|mJ9aK_W9!gEJWF0eJA`R^o>Q*aA^t0&H(ZqVoK_P5AprUuNQd4cMJSggB!iso7v- zW?R`Q8};x7u#k`f`=pGK%}oxo)~Ub**eyN@%JD8k@PEzXh3N-1U?WAqMz_yVogVo>nM*(0VCj|CT)ivh8mQ?tS5 zDg5L+-aq{hz(PU_Y(eZDnN4^;p2NZxhyoK}<4$f=+L|AZg=Kz8nQ~YI_O1xnpt5(W zU+bIV)uy6REm+g&3U!yy10w(|M7dz=Z?|~_U|~EjSW6pg>Pv&ba}tZ=JBOXxQ%{~+ za13AF2{RJ)WOdjx@9glWS;z^2?Wag%e*c?13BW>99Bg{;_w+>L^l*#CC6W?zU_K}Kazk=Ienq0W6H?1>1UcJ?gu~K>U^f zVuBquw{rnqXT6aFbXbTI^<;r9*)+xoIxOS_!7fW?vYxHn3Sc2A4tD>Bv-F<^-GU{K zq|hnBYU^N)B=jzh zKB@s*DFQauBva)pJA+S~7maGchA;Z1UVmhFdjJbjF4)tnp3DNUFrF9e(DSyG^%zI| zLkqA^}e068JB=SJ;kHnve50kDu12kS6q0Nr)ma6Gw# zJh51Ahh6saY8ilqC>yMvv!}xDNcSKB3kfN(<;$&Q7R7N^Iu)1zd-P(KG9sxHJ{-lr z^PuAzuz~i%AG)YsZ&X>UHe-hsjcUQV=l@Z!@jAW(z(SM@wrSyiPXH{8=LPHHWl6cJ zo$=xqh!MvSKXg^pDy9AN+Tv#dhzf(%SGkRV4huOUu&c)$U_2MDzYAa?DGs*iLLoh3 z{6c)(IOK`Na>1rLhHL_`5M_gPo>^aU>U3{>btfdGz)m(alSTJgI1IqT7Kj29UqQv14Iwe>f5$6kFVQMzmUOxTgw`~mOL5GEe6xdzKDYjFJPwMGZU;^yKWnqfE zZ)g2snXA$VpVWX&69Jo1{9bjxAgoaLs1|IF_dj(^;PX@f3$t>;y5GNzw|T>OUa(V} z-V zw){=WinJQeYcC$h^KG;6S!c1t!2|mDnpb zF3Cc5X*W_LHDF6bz(zmLQN^~oj1N8(jcUP`JgHJ2opw_JU?Iu{dm`xt1sxW~^Mai+ z+lX3sy%j#x9%6zW)-&@yz2HC=eoFvRVXzDRO!EOO=e)z(P_Stm*UP z^xFfI)&f|_6N}}7-H_{Q1z;h{2K#O026}U4Ofi6kgcR8MUR$pBo>r0oU||bHfeEnR zV!A6W9(v(dm0@?roYjEcHdOc=c5&VJsBtQUa+2@CsRS4OH>kj$k$;VjH}E4`IX>LvoIr3Pu3|xru{p7PZ#8bz#g`L#*`gf z+zP-#QXFjCZ-%si<&SqdEtU)R^00b004z++2HV`Ti@Z*fR3>PKt9hKqo;ubHE&-Mn}eR7fN}OqhVhF3*&jgnj82~Mn`%}?I9o7fILI_x{7^opq>rx6Llf#$pZT*_|6&Vu#gi1 zJ7tNQIk-LT1Av93IN12fx9QqT!tnbZ$cuK^*(Zmd2e1%jgSGEyth^KT2;Xr42`RAt zXANZU2H)+XQ-KMvTL#d|;0D`$KwaDX-4`@q84<9qL*A)E(*EJ)L84JD*aWXqb+i8Y zcK|FzxnR>m@8MfyU_39_RkwCh?%NyT{{avqjv;>NN=?z1582di64Vo-!eF!RpUMHS zkP`wstw!_UORd%Aetl@m}qSRwgkTuvsEt^?tokty*f30~HdD zYQa+5zpBkQC`M7dz6W}9U}hlTOHU|()^r&I^M@g_uw34`5PLtfDC=m4lEM2UK` zI_%f_hIoq%G<=&?U(}A0-Zl5ZFOib}-OkVQMy5!$Xtg zE80cW0kDve0^4HWXxY)IC&fAym;ify%0#78k2w=znUBZpx}pL5O9X6&?K{=ngiO5J zLNuxc8+5orJ?2skCjbjk7TEPs0}bsx@KHrDo)@f_tS6Ou^|Xb=;`mMpj_pAGKFrF7|_rWGqPM^Nm zVId~iVVk@yrF+gVuz-3(l&B}G!}=^;Wt!#lc>F zaEMO$y7|6Ni{*lyar!Zy62R1Kup91gkykA{-T=TtLJI8GC1YjotsmgU8n6YTzyw&E z$|=h0HfvH~nNtl;-_(Fj5dmxc?5(PA=EIY^N3~#0yVXc|INjnUbXb^`3${^N;5GmY z<9WemOzln0YH$Nzdjv6}>EMShW3OuR$&Kuv0a%C<^<;sKuDXeL96(M8tp2B)jQ7;T zz5o`I;$SZf&!vN`yW!JMAx|up3wA@@!jNR6n`F)vOWFVId&})}*4V zY(V$(W;zv^0DI+yp3?NhAyl_?VUk({cJpxIbJ$u#-m3JB`{NUIMWb4fbqOw-(B;h4pDyl;QxT<>)4CqJ0-AQT1{Sicjh^$Cq#w87WDdC zAHYIR2<#-w7$$J(v;Y7LNpY}eB5%;sOv4>@S}YgrzWLv_16Y`v4YsvB*iQfR#PI+Y z5>jA2+(TtgtIT@qRA2(^81t)2r&ovZ8o`N++!8flLq)(+0dG|oTbXZx3W-LwVC{2^ z65fs(dKJJzlnb_f*0wRwVPQNk*!t5tQPr%r;d^c%Ml>DlutOV`(_bq7t$}(%R2b~* znl(lOSjY*1ZRz%aDZ6%JD1e2eIN0SiSXc=)JV3KGYLt6b5U# zg6_^0q_H(JCRr1^qu*`#lFFw?OeJKStFu_~*D1v=^JPW|W ztX#03iA%!)ER5#|JN&)u~jyzxYD1Z(2o}~h?Fe?{qjd$zu0&W=3 z3%1k1OVl~~82fQ2Xz*gBc5 zu)~sj$qUwS(O22LzEmz8LzqSoY|!D`^edzMO8^$4L_JwwYdyAGvJb#QP6+J&?_rEy z&v!cjEF{IjTI49?`bU?o)@iZa4m;z}ik$!!re=d}Zk|pTc3eLdz(PU_Y})uf*BwpF z@Y!0h1){(N*!8k|^6d@!AA)7x3Uzp@0UIR(HmK)U)y*62D|C-)!8*pCRbM(Ytq8!v ztX!~*4o8>+SQyU>HprqmmE!FlBC&^jrv#CkUefyl+tvfHFe6b<7TBr%Yc~O~kP`y? zcW4-6p1wi}U?C|E_EyLC^6UT;sly@EVb`X;F$AzMH5=@sOZJL%>vvuN77|im_w4t% z-f&1GEO4uf1U#a^1lXk`{S?m+_s2GA?w69T0efErY)Q}Ws&mt8;9YN`Q7u^4dMDL` zX1opnun^^fz4XPi0f2?^ykOto`;U6=?LQL0LQJs39^YL-U$~u#p9vsJ)RP5v9rOJH zfQ6h8SbxWJ%&4y$^#Lp-#ldb8quETnIoNaGnJf+1 zBO+kkAAME5Op(c;LZVSE*aWX@>X_i3n*l6DxnM`k&hiGZFrF9e_t@6d@2GhEYlN5} z*d}kwY1Qi$c>oroL_Jwx&-PsF17IO11UBkNFf(k&q6YvLlHyeq0i;;}pSTv+%`okdOjfGx5Id$>VwECt>V@LN4Smv_d z)^9anV@1HOE-6*j=@x!k_ox=EwKb!DIPi7@01LBn!R|d&kqTg8JTF-1$(N}71>=MN!L6`5@(V2!@SPDbBT-Kl*!N!zZvt4z34uNG_!hHt1l`&*mM!FIc8r~C#`qlrL>|^E!ZvdZ>VR^xG@&MLX->EJ>{tiz`}T5 zutO#fqaGCaD2VkquxWDGv6X z+MhO7xZ(K^wxvfeEl{)~;19 zt1H7->h}06&(nY{6#?t$Qm*>-TmLg~5RGcV{)miMdwcx*3}7M30{g!^4kp+we*s`& zJTKUmO-E42w+_e4b09_>!~avKJ% zF{=P9B*nod&o_~$C~a;^91fvVf^U8%w$Nc=YBpG_qSlIf?nV0nEF`4BPHQnlW;N0V z-_r$KAPP)?T{b5|S-s`MB3S0Q(dv8+*qx(;x-Wk76~MxHUa*b3x=<4h@8TT?5EBHOe&-Lp+Hfwu9UY=XJy{*L>$3xs04(H$ zz!pXXFe$C%HUJiq;$Tgm{-tLsVkSu(4k57iX}kUcSeTj()~KDIJm)~aQUD7HDX?W` zrn278=i;YY*aA^t0_^j4yOln*RU=@TPk-5e)PRi?0c+pjv#LC3P#fK&TCh34ud555 zW)}chn3W6G+N1F*01M-J!OpHRo9dd6Az#bnD- z01G)Gu($lfm@7%&zXMoEii34+S3>J|c!ZBcfjsfo$vua)I~%kcz(SM_HZ0(v!e!<0 zYyb-hDX_-Z7sLz^&xtDlER5#`8=ta_Iy>GwTVip1V7uI^CqJ~q+6n3jGYW$( zto5ZFz(P(4Y)-&_W`4f|asUfSaj>nz+RCRN4(+VdV!2>1=DFh4S}-*mY|e#4@`%5k z@VNw#kODhDGC;Q8t~=f|2U{QtOn^Pu(^_e?@UR&yvwdrq&l<4rM8K9z_^2{pRR?cE z6pd=ZI>z2quPZW80$7N0!Ty)*fp7DM@w{MrP2NrIxcK_4#NznC=ANx5@AjO*Z(U$U zqMob{+qz$aApjO~LSTmkgfSsiQ9S`HB*no_`;|;r3szp!X|Y_eC(GZ5K!=5?*pi|&(?xGu~;tH zp$jH&1+WlhgRQrGvtsJzt@!jpNJxP_?PV!z+MafU0`G|<;1LBTz~*EQQo1~ue;2^M z&Kdbl12%B9@Q1D++j3OzChx;{9Ee7>U>D!Kr?zu2?Y-4+8_n3@f?-7`aF^Dp*M&|x7V1=gU=CE11>nI<|Fm;jqN)W&X2 z#RGgIlkv`??;5a|MZk6(m#eyC*aq*I5{+uX=KOx34z><^0AL}?1-m_T0p8{f<9Wfl z4O>9{GVDGNjv>T|rh^@JYR_u&(D_~n7NWvnH=cQf9TsvzU?+52##FC&-3Y)!QXK5o z@|yCI`)XL}v{)|K6}Hts0$7-u4R+@emGaYLt0n*z5>jBd#Cpr#rrC!8Sl9wlU;^y* z)XqxPUfC&FW@ER#zcgUeM8KwI<*EARDVOOU)q;(+c&MJz-}xzkg;}{^r#$Oh3>_B6 z^MZ}2V?~|#8~a9L5BWN5x0UZ`{LSQ>P?qZZ@Uhe|1 zkQ4{|`&A2haCg0FIxUt9_P1Bo2>=UIv%%U7@R9$RdsGf!At43!alaih_oaGup}^it z33x<-39!TB3l++c*-o&`?B8a8G+;|a!0M&ts(wba!l#dkMzvtw-5;ng>2H_{U?Iu{ zJAJw59{>yEdBNJ|T2bf9pSF}(93NO?udnpkrta8bVMd~!EU-1~8$AcGkP`yyN*!XB zKNy+a=#LJD_>~CciT_TxV9(a=bO*pflnwSz+xPMXZqE7u77|im4`()# zt+{QP31DFhM1cvgm(6-Bt0H3d!Z96f8vIuScAJCnIc#c+d{x>Ik$5Pq5$bbnFi{k^^qt} zz(P(4tY_P8OqzedQ~(P}aj+f6w3lBU_qJH4#d5*!8nhapUIya*ly=ul4bJu*}VSO!d~(e5I_vK3oLs>dghJi8)j8@U83pqn!!donXtTZsEF%Io<7}ZyHl-)t zgeV%-g3UN_OC7i7TulHAQ7+hc-|S=n3*&jg_U-&x_AB|x0Exx%fi)kON-u8Qdp&@K z8HswbI&9*>q`CkWazbEx{W{JVZygy9U?C|E_SW1)`gR|mXq^_z?XbgkmFxqsFf|)& zacQKyiE0@>fg2K1VB2ioU>lc|sMe{#1lYXb-HIzyep$mZe|`L6paGjD0=A@Dkt)aL z6rLf9Mzvu5?c&rMKO1-fScr1LT4qcv0I)Eg7wp@uEh&A=i}=6fq~Gkt@qu-z{6deI zn1N4&gs3ps(H|lr0W9Q%z{ZY@WY$Oh!3SwTQXFh>mXZ8O`k7&HBq1-_VQ-|Lbpx;v zWrO`)Yo_9_%d7X$VId&})@a2vnMvW+c>or+Kopn&d#hn9rA@oWuV9&9vlbg`!2S{e zYhO{M>X~^EFTfOyYQZkP8L9qKec4$63sElEHD#^d09Y8$3pV*?1In!2Vu!@y_`t47 z{7ieR2jaB^Fe6b+P6j+}IN?D!FSMX_jumz&P1lS(t!HN#Cm3UFU&&>Rq z8nFAv2!H7MF{fCSsc3?Ch>J$GU~4%aQSURK?Fe8Y$_49Y^dH_e3*&jgo(-8#<&9Z6 z6OJLoh^F&@>a>>^CT5h<^P8u|Km&j%QBM|FpO^FSS^~%kfmIH@!_0Y8!x&BpASn(u zYePT!wbQy)IxUt9Hu(7Xt^gLMW`mt~c9*=%yk4sSEF`4B_TIbA*0*(FpiTuQz>XX3 zr>qKl>k7-fIoz?12J8h9uzEedsN!s`f^?5+!7jdeME$vJ{u}@cvvR>U*%w&|9Tvv( zf*sYwj`E0E=_9d+d>z(m=vTV+LQA|h17;Kkdu6}dCg`w`69U_~^a8W%X!%tYnPz~^Sv0BzYaMe~eO&(sK1c(iT(AYjOZ5OO zjOPWLQCXcj=|2~5r+}DXhwXCf6@6uPaBFA)5GCr#>ag}sIp+Z^w-c*RafgW2puju!SOEV~>7Q1z(i;=^oXBwa+=IcKTZD8gy8gl?(R6 z-On}v7RK{}eYpCyY($%z$0YWUufyh^O{d#Ab?plEgc*gw2AI?~1+b740vp=$G_yP8 zD8301lHy<^GY; zn{u5BOn}`Q{!U@mEUY^m)7BoPjWl34I|`q}<^+_ho=)BFpnFsc*57Woy4IjW__$4& zl?yg2vF$Jb3*&jgIu!m#4XwWNxWpdvfpzdLrK`H+KY)6|jKW||roR{uU?C?2cKUUH z=7n_*zH1he;$S_e8OZ0j9W2plv0Si+Ru69j9Tui$gUu?`leZr64Ic&v2`RAsE7#ke zb~=ggMuja91t!3LYg4I+ZdZm^VYlD7r-=q^s0dj1!R4w~DJ^25LZVSESl4=6)$ew%AQY`54{um)Ju-u-86)q@DM7dJJG;MxvgqQ-Z&CoABkx zkP`xXYFGec4tBii9Njgk03S^adC?B*z;tO3U?Iu|>)?7ual$ecUq25C zDX`B@S;_7soSdLjfeEndu69$tezy;=asHTK(@X>Qh6vc$Ti;a)<)7SvgJ@I>ma65W zX3`d?0a%D~!G;yiz!%HGcwVq;cUGtBs*`$1>>(dmtDyz-=ts}9p`I|KFxd6_oAI75 z$O(bHf9yJw8WfNKU?C|Ec3#_N^4H4;8R@iGZijug!MOs!!qjZA_okXF%tu7vZQhWO z0^4WPG23BgXD35}N2C+*hyoK}r!S9FY)>@CYn-ob&S| zgeXx@R)=jow8>&PC4ig|*tRKGnQCj6P64ox6bC!4ekdJW&j%lg0(sF6JFau1qW~77 zY_P8{C=?2%G6v3JAt42JkwKX4ubsQP=~Q3>Y>!J-inCdl)8LpIzg=LV0b4Etw&c|h zRoL|IRk}yDV1IP*QpapgD*~`ED;I3<=aqN?H;m^6ySBJ9^K1c&%#4-Fob=vP? zbI*RJgXfnwgL*<#7_7W#Uj~4MoDkTQB|*&VCR90qg`_xG=JH(nx3wewUkQ0)vD^+j zN_h)kdjwH7*seeNC}zkLk^n3uq`=0js>ue`|FcP_0ux{Z$44rQJKLTFb)klBT4})U z87usu%ldkSs>@^b4BewzunFI%tC=2w_+mMjl?&G8%s2d63&!(;t)KEjW~Xd|x9UTT zIEDzeDD)})r{1ATs3$~)!EPVFjA~PTJjnv}@e}oeE5V&28+f=%@0=&z2{~ zROd((0G$Vdg8mlvXsV1?#U~tnOFS6mRo}C>QLP4&C;`DFKY<1siB+Mz!ng z`4#@8AVwTR1Y35XfcF3EjlXn3R2XdMb^oRSSjY*1)oXN#*?DPJJakw{ii3UG@)m7w z_y>QQg*>rXE?8=jgBgH@C>!ii)p>dL>H@qT77|imr(Ruddm?E7zNZVeKopn&yE9~( zvSW!wEjXs@FW+pZ0efEr?CRd%RQ+lXU8;Lj3pP4wyL$h8<2*PefLXa!~IujtrI9L%ws^sbzoY>^H7UpaH;)L_JyOuul9rv3kfN(%FB0cH;fyG-y6af zhyoK}Eld8hJKN@cLs(|vHJgqauz4b2UF&^THSrubUiYXLY|vppwb7;-mjEox$_0Dl z>$lDT7RK{}{r+YR6?xMwSYi+Pz*_kk$nQ-_UkzYkMxvf9uqG#Sd;u)vgup(&6T%eg`_yxQ9DBDGyhdi)M>F?u>Yl<9S>k(YBtzjo9f!ltLe7@z(PU_Z0P2bGS>@5 zAE3a)?-THd0ux}Jvn!P`&z-zsnF_ayoi$+Bj}tzJ{b8T4dRZ>V$8Cl!6^UxWX0+L$ zesJ{MIsgk%F4*Ss?QH=pjOPX0YRO(|dWSbhVQ~;6{+Gm4f;EOs$F%dShIwKeE}>?%?3O0=wtbz zyn%xNEF`4BJ`OuA`?$w^q)r7Uz=j{WqC9@<&m&mox5nMNX}}&40qg%dPt~{kO#~|% z)q>U2+p3=2Fw_&kLX-=3Wz6vy01M-J!Ip08OLg_0-9%z>d>wYj`AT~1l)9s#o-m^@ z*niFT<^fp934u*7+sizCX|x2uj&DaC330HdGlS?31M;fDVj)lbb#lQ*4|*~Yz(SM_ zwjJF{xv|J01;9c=3hdxWJK3qHlknmf*aA^t0_^<7-pZ9>UGV~L>w7PHXu!sbfKBx% zP*pEYH-id^Mzvu5)tlAko})SfScr1L=Cw+|C%?dWUa*gxTT(S@#o!lj5F?Huc37(i zrL=!^U;GdYQKFu#4mLy+&&I!SN&w?|!QRUq zOs&XD84Je{VuBsEtnokk>)5u|02ZP|Jy~EwK2{un4huOUuz4l^%vMiZJLs^G6bIX{ z<8k`NWxq2zEtU(mzgL4&01H#I!CIOZ*j>CAy%xYiLJDlY>lm5U={LJ{Dlh>yXh{hW6IScr1L#=BY=09Y8$ z3wC3EPwGx1=BdQu_&ThE?>oA8`Z@=wC(I}e_TdY6?68m%0^97sHYP97w?BY|q&V2t z0bA)K9^3IZOUM&{om{Z(yT8P*wIIp{o2Tz8A3d|&0l-2+3arVb0^8H$8hq5Lzyw&g zm2Z?o8m#kzW4ffra9a)7ND;8s^Yc|-qpk6!LZVSESl4fdv1b^=(4a=|w2QfC~1 zh4H*#O&%Lj5rLI8B^JjAwhMiq_S@93KGYLt6agF4#T+^;LS8nAaoz}hz}RDCw+))F{~Mzvt0la8qS_o5#HScr1LZu=8j8^FSN zUa-S&4yLSH-o#S^h!MvSKXgqkt0s5%n1HX5f~YXq?6G~404(H$z~0;9&*VG0#{gJJ zii7<({2%SnxoL{T;Sl=J)%$XzB>)ztW`hm8-&>h8q0AM)LP83xOZf}ioTe?y04!{Q zC@=xGTY6_@{OaD}u*{!rrz$jH--&>A_smsoH9CsVB@m5j!InG;Q~%uLm<(Vc$^~ng zJ>v$ysDu#k`fo6~fw z?X1rox9U`20_=yGxeC>mHh8aP@_~dEK)IFkkSgs3ps#^*P62C$G5 z0_#y{Kck*>DG9(rQXK5%xm9##s(cXqbwZw4EEnv{Df(*xEJWF0SFh`%NN?(gx5z+3 z3asnH$)x4rS{Ul1dXA$Hi@ zv#;s;EgIq}0Yr&iPrGZOV=fwdTRvMZbtKu!qk&VZdvjkn#809Z(hgH_M(B{!k^ z#OSnG?kRz@UgQ)23sbYf7T&L`NcK!!2Vfx~1-4+#5}DcRllT$|*aA^t0_?o1cFHv= zpU%TFy>4ZW(10xw0c+ask;*XA0DlV&=T8>Q>CST0yS#}nNFEKJP?`*!U(#r!^>@o}4wkOG_GI6>wSRg8BWz!r!C6JU!< z?)dH(PR zfQ6(u*uisJ$WyZ8@!}WA6X!o%u$_0#Faod;WrJPR+SYD_fuk36SV%~LZQ5X=?8&E~ z1v(X&0Na<2P~JRM6YsT*A8zHS0UIs?HsM2>>c7Uj@xEfws1|JM&V~uc2RG;nU?Iu{ z8}_S1F8~YUdBJ+NQ&Jy0uEZY>AVwU+|5K;Er|UvLeR*-4)e%rnhzf)CX;tYCU?C?2 zcBjXAX2!%;y#XvF#ldDZsi2+H8m@uAPRJ9B<${&9iSY!mEnEo%Y_P**rSf)0=LP~; zNJxQwbz*|7>Gn4rpun&NqQC^$x>4B*;}f^>@l#)_rHs>nWkkT*e|)0a*D`TCR7f<7sGalf;(d7#BaR`0Ej#d)Znm~|71R@= zL_Jv@_S3pucoQPzgupr$ZDV?t`?>&FNQ#4vO&%g|{^tn(UkQ0)v0SjNqC6e}SctO0 zI=zpO-%dKY9>79E3ha#mJ!QRaJ)WXdfeEl{=xWOG`^@Y9e~jIETuf2_2k=Nr2_>>* zi7Zh>w#>}EGfWiOBWnoR*JR7C>}#S$Swl#&XUkQxhCzv&;`RW8^O z-yORGSQyU>cGU4S`M=D8_$dLzh;xWwb5A5vt>zs}hkim-80@BoxvOA>g`5!B)PaFa z^Rllm0W2iN!OlO_h~7SPex}6f5c-s$%axpG02WHK!6t>SQCeHws0m;pAqBSUq-dGZ z%+y@H8ccxQaXMO6c%gVZOtbc;+at7KOGUtDOh{EH{I$f3Uqquiu+BftHCg}pssq46 zlnb^}$mt0H7RK{}y?xwPv8*H= z0y!bD50)Qdg^TdJK+&iUtnU#s z&EE6X?gLnea>4f1WSRq57|#o~ex13B)U}bFBqqlPcI@{mw3Y3c>(EcAC=B+`-|qPI zLdXe$HR&J5G*~vZ9e{ASuWVnQ~j&~ER<%0eciqT{kCIjX8;Qc zDX@ix2J&?mui@22a0H^k1Xza;DazZ=gL=X=10VGmuLYYd0ybdcQ}yUEbsy*-)qyRE zG1a_i{jwc^g{oYz1Mly64q#zCFW4>bhAXm;wdyPJ3i-e`vNEQ9taI^N0;ovzleNP7 znN6DvTLQ=lfqm61ifQ!v^*aCyNpY~ZDIkg@kP`x1Y0_Rs)?=OzfQ6(u*lr7dQr#Qxd9T-GxnP^DWLyC(lxBl{o!E+Y zXmhMOfQ5tXr)k(VV-hxV_N3$|i@co~3&(rmD? z@s7&qvSG#m77|imEibi}FDx#qq*sFpu>D_tQkg_Dc%R;^d)KCD!R{9U>o)hP`ixt9 z{9!23C;`?=j9XRqiOiymfaUy&6n_-P5R8mGSV)S44NiMRy~){HQ?JQ#!QMRh89ya}(rmD= zew(O%qz}&pu#k`fyWD-c-2ME>H+nUg0DJ0ow5pST|GO~FjKZRsTCkZSU;~zBsfz-9 z@p~lEs1EGlQfp1$xh2a0EJV3rJ%W6G0$3Q&3$|e+14Xqz6Y*OSh!KkpesNH9S}N7` zV?!DA6QaUk7xZ7S1i(U02<)X7N160bRVx8lNQ#3sXq`>veXNZ>`<>os?4ZvEn%92)A!BMf-MpOo3ZAl z`sm+zF8W7xU`z7qYlcr~w+FyNRW8^Y`zvJvSQyU>c2incg-3=d-gO2sL9otetI&Uk zo|yyFRQS+-TCm$k3cu;Huac$i zI@%Q9mhPJ;64ilq_G_YP5p1Cbun^^fbvRht6u`oGUa*6$>L{9bPsA?{ASMX*wpRhQ z_0+r002ZRcU_W{$*#KC`34!$*vzf6eOA7?BkQ4{oQq_PCvbP-%XA<(nWVu^{k_BDf z0a%E#!KO`3R#n^ATm@SKNJxP_m~A0{9cF+(KMzMB8ccv~`q4!-(54U{^7>=tYkw`+ zSP`(!0hwy2;y?K1wP;ia*0*I-O$Mz<9WemZm6kfV!7K4&LPBz zbBJ4lV7nJo>BK?Z0W3s`ezHE+iraNQ48TH82yBw`CdT^0hcy5elHy?huHH!1ZJ1m` zugP-3=FJ=J4`87*8>~%-zVrd3uNnXg2`R8tXkGcAVOLM-)nEeb>K7kWv|_O}OfzQD z)J0mbNg`n5nmkiKxVaN|6QWTa*og2pnlmZy?f_Vba>0(@crpUO!gyY=4U()C!AlwZ z;0y`3n7ns4&>SKcBe(SjY*19r$oF^Jmb_7yt`Naj?B=n$tZh#Z@IgcR7R+bYZBYCNR%YA^wIN9IOV! zEdsP)--&?r{qRH`f4GB8|ELbEVxxm5eB49_01H*QU|%@R!v|@=cwVseLVGD@$=&ga zU5E*S&29UYD%jU_7xWXN!eIB59Bd9?AtwZO$@CCr%d~3-02Y$sU}prBQDaiw=1ZIo zA+W0zsyqM-rP*MoL@ZLS>2>}wfQ5t<*axTn$y^4!83YYJKAeC@G?)Op=Fke2`ACfc zOfx6r?J_Ocm7|3But6sts~`F{kJUe_0~-+1M)T*0cT)fhRk>g{#+CGk6&A+xf?Yj+ zn!@u?b=+k`Ob~2f_e!++t&pA2PlyuzWNit~pZvTZz(P(4Y*u0*Q*Fw%hX59m;$V}V zZ0JQ%$#_pYK_HL85TaR04!AHg6-!ibOwIVBIYyj{&fd69T(u-dQF)dm60eXC?8TWmRCbfRF3?Y?C=7O7B@Z=#g`5!BouRv#vn35e04yZM!M6O`iXOcB zB7%jyC|KpdrlkNDqHM6^CU>OkIWBqxU?Cv|_QoW;D}FUD|9}Q}awgyr4JN?;OY~GO z3N5mLbGmnXaF7;kx(Ha)H<{`kZpXd!kLtii&*`KYTHG@kz(Q3n*qqhLw_$~a@w{N$ z`PeBA{=V=*;uZ3NJy4^Fy4}SHKXrkML_b+8?9u%0{Q)fGguuQ&vW?kOqwNC#3rTUX zZo!WzMej;(dQFzQCCIHhFaW?pX*O81<)ySqBi8`{77|im1rv1O0@GL_b+zmp01p17IO11a_QL7&F_e8-A<> zNpY}g@)Oj@w3FTRnk*M=!;CW%0W6eegME1K81;3`n;`%e5>jBtO>HalHCsDbuLcuf z!;gJZ-m+Sg1k-Lq%b*JuSz41+b740_)|ujfwAj5pR)! zq&V1#-j}J~Nz?H8u#gws5-cx2F&V%@lnwT%mxdnMuAdQrg@hE?ZNn?cZ&vo224LX` zM1u*iv4)pb$`;AE&HEcXXNwkWj0o7dGt<;Np}guph{gfQua z4e@hWNQ#5a%+94gcbm3eugP*(Sli69SO5#9*(WnmW=$dLx-K@C} z0W3thV4wb4u^+&~cwVqSyiP0D1dPx~OpXt1M0iztT9)T-01Fj~ezL$C$a04RSjY*1 zO`ICaST9?18}_h}6bHLLD2$p>HSVciljVZlaV5?iz(Q#@*uvsjO8M>LkpLDFQegel zF3NXz&&J=Cf+G+OCcv63Z{EW?D0#Ij0T0W2h> zz?!%#D2Y%rFKM*6fb^leTd-6-&vG1w;HS$pCCq#w8wxh!E z$uE!-0(+|ENv7SDJbPGSAt?^lbHICQ#F>f!iPNF|>*Rt>?&^RFl^z6co zSpXIiQedzAT+%(cZ1ya@8ccw_QTANEsZcH0urb1Kx<(sksC)YSErJe- zMs;9)Te@kcc)!D2WFX1~`*ner1+1_zo)_$tpjwJPHE!OLc!hi`Y~42>Dfz%|xWYn3 zVXz(P^y{!CfSeH6&>{Po_rX(l16W9kgB?7!CcXaXLA<>J^2A>!7i^P{R$~AxMA=|1 z&ex&K6AMoPSV%~L9e1U#e4XV{d;l*TfoL!Rwq3I-D!17+aI0=%;Siw(drkywlbO%d z$6LI?M;eGmbzt3W-8EaS_f3Q?0YtfAk2}t;31DG7FW70JHj0Oz4)+GI5F^eZuCVTw zU#aOQqCdj|08yf!tS!O5qWw7l7IH#hADir8)CTtWvqz8=2it8`d-|Z^<8^vXmJ4=b z@H}S#3#Hj$OCIl~tIT}a1i(T<3heQZe)6y{Rh{%|FadUPd@a?V)RFj6WtC^ABeh`D zM8KvLJXL$I4(kCO5{>>3>;Vr=N{99L04zkgV9op+o&c~go)_#?hh~c1FM=W@ULoHK zJJ7g{O2~N-4*i6R!eG;5oNWOt02UHbU}q2aknbqkfcGH55r_s8V3$sKtsJ>ejb8?J&ve?S z1zR8jHey7k`kwz5yxKxEsso#_x0l9cM8!1#3sElE(^hw80azH%3-)_Wg<>b&YdM@l zhzYK+7f%|}m)5sZ09c3;{ba4M8Pz*$04(H$z(!R{WF9Wgs0&~rDGv5(?_1O#_meO6 znk*M=Vo@sIA_Jw_U>7+bQWe?V$D0r#AqCcbP#wA4vxL&C!30?5$s*OsWUq@b%^qR# z2ee?JWDK3i>oA8SEE3T#8$4sx$2J?cS&S7s9Mhz1j2 zS5`7rEn!+!gL8VdX~+>RSVjbFPQ+{V+;yjC=pWUAjR<$uB<>4*0brpj7wmy3bvb~A z@w{NK9raL*c(4PnhlLn%4)IOb@bZ7uu}O3`^b?{)KUrYq{!6aF3JWh0<)W!B0%-2fk~&!U_usDX=p8b+WIW zHdN88!30?I{J+X&3$p!SnlszD9Mgh*DFQZP)myb~dec<>qdKq&dwXhPJ1dj`7OHZ= z_S)>d2*AR4Ua(VBOXSu*EAe}0hzWvil>U-Z$@B4Nq#!B`HrT}Q4uFN65ZH6K&N1nM z#h+k>g`_yxw_#b7bK05-5~o85?DJLL`1A8nnhkcwf3^gxQ)4>;SV%~LebKs>>|T7k zApjPRKs1;DTg`U7vexbQ-Z0J2Q%X)~!Ip}EHQ4`FeYw-NW%@^TU`MC+(p-xwvjebD zl?!%=(=bZ_3*&jgj`%fPaW}_hp2REU-x5?%2WtMi4gG|QL_b+8Y(_+{3IGc^A+Rsk zYnW~SD*FRiNQ#3kDcw#v7`?)~?jcY7b#hl&SJ%uhu);!=4ff)keCoyKmxlo?BqYI> z)Ry_}-P1;|1`}Y%4Rcn}J3ZpzoE}|rDozVFWUTO;uFvN?V5`o_!9PpBvi_IY{3Rsa@q zLSVbvhB6ITr%wm4kQ4{|=V~HV((NNYn-B7$V80n2=?P#V$_9IKbWdgFn?-g277|im z4_Ri)Eh!JY9u|&3G?)O}#OZ`8KIY9eIHzmtx}4U6jTZyEFIycKACJ#>6piY@ZmZl+ zb7hKuV_0D!$^~l{=Yx;igz>y!&y=Jq?4qCANKB3oY>RshXuHOi<^UEd68&VYuovG@ z4*@LXguwPR*~|=R^B^9;LQ)*;xh|>H^ZTm`^_nbqg)Kb#)Ca&qX*SqtCx)M47<}ek_O%OVwP2G)z$$#Q)luI%WqQ-qa2VF2mAQ-d8*Bmz4(|L$P<5^T(Iule5L_dh_b<++_a81 z`hC^Q5{%Q>z*3B3lBp8EL7!!we=e|1;E01Ua%di)=|7J%))QFAV!=+Twxn|W>J&g zI+Ordh!Xu|Z3%W*xZv|)Atwa3s$whSykhKDSYaV44tD3A=5)u|M>j~E4((qj7wn_; z{VM}lD9r{td0bm%Lqp?y01F8zutS5c$eevg?boZp1lSn26lK5p&A!7ljZd|@q6NEO z1Z?#FkLt*oM{4LF)q#zkqtb+bU4(mBsLBFsaI&ZCLCOcf!gyY=V^#Kwf&Wr{C0-%l z3Tv?P2lb~`=OfThs3;6}+NL2iYzZJI1lIXP6qEnY5Pt~~lHy`Ek{+}8yP;Nar^DV z*R)`-ihy-~@3qEFO*E-#~a$xOVCcN{>J3${_q8~DR=FrF9e;L5HFt2P_( z`DhRmTw#YVEvJ_DZ2uU*LX_wyYlY3Q$j$|@kP`yy_bZe+BrCxmmV=}?*sRj3^!g!n zw*gql6O-kFt$XkD1po_CHrUI3jwrA8HmVF@At43!RI!cx(w#c^FAR=AG?)Mz88J~6 zX3%aoOf%5dmeGRE6agFb^PPI;fE9Sxn`l%AHXuZ$Ssznv3Tz1=$_2amg!N8XVPQNk z*d}9T3h$6z`1Br#5$6!M1fTa8QeBRyI{{dT68&U>9r58p9Ds$K5ZGEN`x)m@F4;d`|up01HtzSd$qUR7u6J?En@MQeaN4vNn=_xF-`g?w9rrLM)4=5}a5=qFSZ20QV3Yu4wmWIu(#?t68F>2vUW zeEHdX{|!Js^K)1g;S=^xdBHBfff z&}$Fk^{`Nt3pW1lP7?qN<9We$yf;K)?lcv@6@i!_SO=;KeRD_T8~_VZqMt0VEegD* z0$9iifvuvx#7tS7kB=&Xq&V2tmnKs-*}iy-Fyx8Ja>15IcfAH+A<70jVOu9!W?K(` z;{Xy;V9R&eUmlwC9Dk<^jzBb+0Q=KBNM-HO1)r)uz-j({E!ZRxuyF%EtKZ~&%LlNc zQ5{%QYZpz!`X9c-3JXy#*wgbH^#ZUko)_$4%|ON3N&k!`ULoI>Abyb{{p*%jF@S}N zL_b+zkJP)?7QjMI2yEBkmzad&&PlMsLQ)*;j~98A$GXIpdQFxKHgU|Y0RR?Cv%&t` ze2@BgeeptAVId&}Hoe+kS?$AjF6z}_0_?t?r<8{+pU;MAe(%{kMGN+w2-wjV^VH58 zvhb5?(Wnk=K)Os*Y4f^<02ZQLuzq_gJOC_==LLIkz<7nlJ>T{clj8$>(b0r9KRzM~ z`Uw?q|2`YF~9dQFxKcHW5P82}bav%$VP zTBQ15m(d8oLP83xMdomM{g!i9>(yWaY~Nl-RhFrKcysWR;EYr)*p)uQdsx%4pVj`o zt|mf)g{I@Zux9`kqFk`WON^UT<8U0A<6|Cyw@ukR#+I%3wBfCK*c1wC`IBG@_`-Op)y@P=H>_J zCsY&$8*JOh7{EeK2<(@_{mjH=2KN9gB*npQ_iskmSDh)x?z0B<03Z}Wi<7$Q$Y`O^8pr3ha z-`tyv^^fYn#`RWdvO0u!1F%q)3pRb7*(U%C<9We;?7vyDY`Sc(#4F?j>uzaCZ#HdW z0R4oDL_b+?x{{WUx(Z++Cj@rL&}hc1@zA{h7Lwv%y$?5{E2`D|tJh??V4o$tZvZPS zlxBmibLf=n@ql!101F8zuw6FqklU`XyQNoy39#RihN$x6XV->l7M_{*TnqM_2w08L zXY~fVrub|?(Wnlr0i)79+xYVofQ2X*todxaaR3&^^MbwRv`TTK&=0S;gBbBi&wthF z9#!P~p$5IAI)#@PLR1)RW@)e002XpWU@ufXz}&5W{RM!9q&V2;3?rzmp4KVLUI`)4O*o zEZQYNd>PqXioy0yb`Tp1NgV9sC^D@0CbY2e!bXuV&5mX-M{BN{8b)^68&U>J@F^g5WqrC z2<*SA5zMzQPfP$TB*nq@xE4csbarS5OAq9U$#TKYJywBxSctO0Htgc0+Ln817=VR@ z6xgj^4HOG1U+n>4;Rr;739x@A+4q>=Y|8_f=B7I-Ia;u{M8KA;&r|;y?TmX^(Wnk= z^tV2m;--)G0a%D~!462dbOpe|cwVrFzjstTneE{&F*&|H>~GWW)ZfbHc(oQ(B>Kq$ zJ96P!{FDH4LST1|+``yDaT)|*At??v;ZZF*GSBmXUX$g5{k_S@0=5KDnhmz+-_>+t z$_V_~BS=VreKqr_O!<20YXA#JAR0`7-7(ZxwM}*kpU717W5zoz*lZE7zF+dxX{)N^ z_E$8j1FP8Rp~-r`t~Y>%C>Lz^+LLwxSQyU>_D!R43M-%Zwr~z1Ml3qG!p0{U(3fVr z89_fGO7xQjwoaqjBVdJvoDkTVv!j?Yzs}zQEF{Ij?hR;8*PmwINUzCq!L~`tx(#5V zG#l*4>-Uu>x;x-=2_PW__WhV&vSvp28|l?x0<5)>o$7{hqyX*hR@SA$k=>Nd>@z4ZMtd|d9A<6|?_GPp`fQ9kAVBbfKQ@HdlnIthez7;n2L=Aew zmzz7GpHNX4?98f%YXVrv34u+m6Uumx^?C(hAt??vAZifZa#jHTyb9!rzfLY#^_c~? z04zk=V7vIZ(1+3=+=VRxB&5Km|NSDnd2t&)TMLdrG?)OJx|LCeo%;I=&grJE`#x#G zhD{WH(`COoPn~CauNg!Ody7PMV6DFN)y!=Drz(JjC>QMY_Nm?g7RK{}wOtdg*s`JH zCy7_c2exh#3)=10QM{=WDiZxiKBPXB1J zWQSgp<$_%^sGT){h0<)W55Gk!9fw9516W8%fh{z!8WB6JXCRnXbw; zIOzn_T%BoKpapwQ1g!6ePwLaRH}{9=$2^g!4s1ktU(Jl!K7Rl#M7dz=Y;}nSurQt% z?4Lq6#h#?Iza?HFA6Q@CBI?zP5?|;iR3!Sz0$clv^?3jbIU%rzJk~Hyn&J%r7Lwv% ztquCoxBc6E(`&L^upiZ%LjWw4W`ni+_dvPuhz5VB3ldUbSG_Wkw`^C`L9YfAVCz)x zukyRx4R75);Tiiy3pPyzY=nJ*+HOh1J#86MNz1g%IU}eP`*^3c$j6 zUaHMJpvRtyqtS0_@SH(+p`TDu80-kUz|jB}azbG3qxUlR)-SmM zU?C|Ec63?}wN2)S8+OPOf1O;g8K0}H1h5cggAE(lg8rL2HXOi0LJI60V}*Qk`dGYc z7LGtPm;gIHW{s+G(QFFNX+x7sKeb@jPZHk4TJ0`Wuj;UJl>Sj2SgS8?n%BP=1%QRB zT(A#vJ*@#OjOPVweQ=24dD~-U60eXCZ2Y2sRE*o7R{$0&68&Ut34R7VO$M-#69W70 zV=z;-<7d2U7Lwv%3+_FjEDp579UA0C!KStuvJAjNlnqv8c!4@+;4>Y-LP84cqQic& zz@NwQ!4E6y5%7ox6JY6P^;LV0x#MHBFIVYNq6Hf*0yeiGtz(SM@wp-2Ac>os1^MbwIevo44l;DE^7GlIX#4W+B7ggxXE)DQ5WQY>|WPu%; zF%q8-3ppXM|v3ziW9J9k-uI%4+> zd;+&1+Xxl7pzyjlfv(YYMR94_*U4Zx4%7Ig5^YIIIDbs>|DFW7XK%v?* zIW7Y_BpTI$9lXd*)BbwJNB|2_F4zr~mN)=d7|#oK=&1dQ1EcbNBwisO*x}`t^z(0a z_~<97C=9lp(*?Yi0CGZLOFx7$O+CEE0$50jgSE4Yr~LAo9@lHKT(CJ_K?(p1rP*MA zAMUA~F~<={ApU;^yg?FlNU*7^ATh=2bJ6R z$UX6ain6+bTLOp@{ba4M;b{jt!3qmGA+QelJDJUvi|qg`B*nqD`{_hmPp|w+ugP-3 zc8FhF0$`yu8*K4|#`M|H^fXvuAt43Ue8E-OR!tP%M-N9J8ccw#m)%D7{YvownC8(H zT@991%Tm=^8R9GarYpeVhdSoU!8Q6vbzrT&^wNa4X&eV&p(+<_mSGY;ZWG4yg0&y4 zRwx^dm?QBD`BvEU8^0*k(WE^1j|CNpezL%x?AOu?z(P(4?2P-nnPa!#wgs?|6bJkI zw;g@!_`;uhO_mFGY-%oEO8}+WU|+Y+pt?^w;09nJAq6&lk)`aY?ZI5V8ccw#ak7)D zqQYerOw&Fqud)_wya?DJS&`byC?`q(s19sIeRoZG;BprL3st#bsl?Qyu)@N4Ua*xd zr8*JT9yr9At43!)&2vrE4|<1O^BO65%7ox6JWpG zs8FsbABnd;8Lir7qy?KS0yaZdtd9O!qZ)KbH2OcVS#Fw;Cyu=UEJV3rFWWpn3}9hA zFIc0jhKgUmY7CWlg?wQB2NqJd76a0H^k z1lZJHd8#YTE-!*<&c3QN(Spqr0XzC*u{ufk>Aj#E z02apcf?d5~iK6*e1H8=%VuE|vnxBg)*@^j902ZP|KUrWaI@sc`c|%SJ?7-Ih7=y_# zdIDHTii2ea7}Lh7&J_}8Qv27*1v~K2)jj|gO0&UE`hAb~4lC*gU?Cv|_Ti`JvY?Vq zg?crZ0DC?2uBz+EcX-!qrc7h11sgb7cn_t@?WQz_)zasUfa zF4*fX0X6^@#`A*R>qjfj{Vu`Bi$hEh?AY&rsN7ahr$Ij@*;sdkdNr5;TVq6#lAif^BdF`ZsLZus_ltnd@%gDf<9!pizoJnc*py^%dPFfYG*JQb1-`y-}4l68_W`m8c6i&O(GA;tJkdOlVyK`@O zn}Xo_dNr5;J8*zpI>%(V#K2J-~a2nn-FC&mFUpCxDC)xhzf%pW_sEP zz(P(4?4QJwjN$Ql4Pk|aq&V2thi&LiEBfH|^pGbe%LO~)dDRpE3sE-MSu^|5(=SJK z1h9~h0^72Vy}Vt&&|`Wvm;k%|!egcFy9Id3#OLMREVW=WMZo3+|4_Rf>x}m=ibi!{ zGbXre#vD1g9l%1A3wGp}peL}x!gyY=%oI1pQ+b1l02X4zIYh9zZNE|K`@L>JKOrg% zw#Db0O93q8gus4lc9pScV?PDJLQ)*;=CaE4d)FEGzY_AqWVvA1%#W-DU?Iu|JH1wO zC7s*#CxC^76j+xv_2i95b~~h3g9)&erUj~+sop(_RX3ydDR}faMJ=Y;vC`%`{KeY%Kb}2d>9-= zg~7H?SR4#sAtwYjQg)J|Px}}GSV)S4t?QpbJzKV7JN$J*o|r6mg|+Ft6ZfzXWrJLY4Wp1;DatlQv9E|4$n`dCAs9yD59XN*&BhDd$P4sz3 z~#h*<)=ybrVEZhG?)PU%F#<1 za_uJm_DHRlm29+NlSII7izrt|nS^x!4x&*V*#G}();9ZO0j#hP<$_&dl2aX4SQyU> zc3it;xqae_Z4$4LZ%a^j>_h6i;|zS>E>tA?$pR}oJE}f_g`5!B*>2~UjyaQi09Z(h zgN-)+O!*lbJL)xAF4&LtJRbpAD9r}Ds?Hobvfi`)02UHbU?&e6?(%*`jTl%F{0azo zM1u*idw-a!6b^QHPuHAE0gbg_--&iJKt3~P&bh>J#bU<-Ei)GR1(HweH&lneG@ zbTR%;7mVixOHEjzxUi)^-oyhjV$s1BHhxhlRddfw{2~UTL_b+z589;Q56eML2<-4S zrdR{#qMDX;~n zljM_Ao9za$k1YszM1u*i2hJv`YX0ct2h)suIMh}PcI8yzJ*=j%T)iv2GT!wj8r6YK zcn&z;Y7_-vAt?^l^T~PYQB_a;rVH}KWVv8JEnoW-R#=F#!L|+C zrF?p`o*#gPgcR6Zx0&)+^IqT6tHA`=+VuyhT2)Uu24Lq@IM`{yMv8!SK3l4OH!*yi z{!ty+j0wFpx0@W016Zia1zW@4A`!sCcwVrVgN+nTYVF6*>>x&*Lj+rQ>^my1s4;E{ zASw*jH~i%f*b+ca2<%Ab9n1iqnhO9dB*nqTHp-!S7-N3kfN(+wTmN)jJgS6~I0*cl;kbqQL~%t({_2F9Vu-!8AwO$5saBi4&geB+?h4!A zC9^Srh0<)WpUl70BWJje1F(>g0^4@S2>FCzZVdr!q5}bsXfOfx__`p~$>FA(V44*J zm)mQ>ri*~}-CC-y`{`%6{!ty+jOK2drzT$?16Zia1-oHltQmlX@w{N29OfuC-ATsB zZ9+_Nh4tTVM7Q(&gFh?>QKFwLu!R|yrvO;U34twq70aAp{(c3pkQ4_S*(#HIZnx7_ z;&ceDu$|{#9t>ciG#hMaR~!0Sx2FC8wz&_%MhfixPtD}7j?OCsuy6#T!35Z^#S1MF1AY^Maj3jZhT4xxxBs zgEKk46*f5fH}&LZ1YWKQ6^VYbz<#hgF9)!Y69VhO#4vrjCFAp9At?^F-M9rr`u`4Zk{ImrtAM#*lq3$JfTCPQ2^@^Gp{~?g(w$nUrUo~02apcf-P*-P|-fD zO&5t*$OpEOXC-=Q>WekdPpC-rlLdBR_M;#G3ppXM9fn_H#;2+-!U_vXaj;W*nbE6u zPnfRPWVu^{Sc|UV02WHK!M6EKD<2;C6A54;AqAG1x<+Q-_Re9w8ccwFRC%3pX~OCr zFiqQqlR9X@#)yC|S!v*U%;or2{i8atre5xvTb^D902Zop!QS6guRnl=@w{NK+|H4& z?QXVM;uZ3Nb#_joT-J2ShJHdtVX(>xTZRKz$O(asyS|^faDDnt01HWRuq92r>Ba+2 z;G@nUPwaoVV5`NaTmrBVWrJ<57)3i?46P1eAt42}Z)S5@zpppC>D6EYY+z57l3x7) zuMv!0;M7SA_Ld0Pf)($-d8aRkXbzlc4^wtC~n2S$-fhZU3`(*`R0W6H?1?yDU zTA_5jkDn4ij5vq?T_$x`YmNP$Lshb$ijRzks4&>Bl>!U^EaZg126&ue9P(q@16W9k zgDqG0qs`MQn@F4vp)JAm0Wa}E8c>=I_FW4f>eAj3_{exjNP*qgzMia#<=}DvTXP)& zk7zIf*6qYQ<=fnMO<>i zrgn6z-2fJn;$W{fYC;t(4#P{+AW!^ta#z?Rjb65c6&9jwu*PP4DD!W}KfnqL2`R8E zlKn65`}6~!7!5}t8ccvqId)ZP`eN4$IH%S}I=X1VmWzN5+EbynQq{xluV_>U)-<%2 z=3L)#X|N@LC>Lz?34O-G3Jc?T!9G0yT7GuL=A{yo;{!W(?ky^E`BZ#X8B`?t$pZUx zotHU)g`5!BGhG9imA~gT1+b752V3HiPnAa8!%rC@FABDQP)#L(g(w?rz1Z(`%V{UC z0$4~$fj!!Oo$OCm@K0C~;0Q#639wm@ZmSyaQ4WH0>fiLFOba$_y6~H>{|DQxebj3G zqX2gJn5V`77OHZ=4ox@z2w-76FW8_p6BNcb4e=a8j5vq5C2+SirajIiJ%xTkl;|f5 z?4GYX@#p6uCj>S;GM4f38(#=uAt?@a|FfM`>EsT0;RNJ~$#PfN%6@AX0$7N$!ESGJ zitceFbtr&^gcR7AIYIL1tkd|pVWtxSk7zIf_J`3qRj0ffwLzU-MHfm7_M8M*H&wgW z`bPoml)k>>0W4JIf@SKr+YVr1JTKU|JVV8vr_4EtSID=*-p=?ydF@HT$8ADIqMt0V z=G_m+!U_vHA+Y9kFEg_r{v82eAt?^l?(Ji$W9eADferGaU@e0>p9ZiHWrH0Vc9E{X za!xdWg@hE?zh?_Ct*4`%U`2o<5Dg~4ju|*kxwU2RQ#hw}EoPi9-uuJ+Sc%E;ft@ufi!$A|_9*ldDiZxk{7$Om@#(g)O$nmKquJX910yL-jy zG5`xXA+VP7?=$&V58zFRkQ4`d*}RM@E=$H6_8~92!sauP+W;&?*J|UsLBOv^NrpNU|~Ej*iEPJ$-gcbhS!rpj5vq5hn@98Lv66|#NR!G zDA7;W3VZsSbv}TFoDkTw*N2$e8%ExTEdeCO!R|NhOSe5X;Jd`>(EfFDSJ#R|J_z|vXR0r08anoFP8Se~WA<6~2#-r|h01M-J!M^C(UNPX&`l=F><6B`b z&Mc&SkL^r{enLf}pDeH~!Z$1ju#gi1`=<0Hvv6vIQUD7{aj;$9pP-sF?R`zJ$#TJ- z=oCEyz(Q#@*hxq0DnIo&xCg*q8cDE`0^8hTs(jqXZSSGMa0H^k1lVCcHmj_dIX_^U z&0-DuYQZuhU<(%iXNB#MbyxqW4s1f>-kOFHN4)_oRONzI$5xI3urQt%tfgONs>&#j z2@`CIXO zXvh=)PPkx?zN@$hU?Iu|JF`4oS@13ZZ$eymm0%+Uwp;i~`O=&rU|~Ej z*xK{u3Jc|ieG;#b53I5OPwJxkpbF?GR3!Sz0z2SW%UJ*xazbEd&i~I7xX1hB!{8t( z4mNwpA*%C(j`;9@$cuuV=kqZSz(SM__QhaNWyQOVIk3V)LJF))f}y;UvEt9Kb?VF4&I7Un>Jx z7|#oK+VC3GveL9LiC4%6Ht}FX+OXQ(nb1$DC=7O@k@o@s3ppXMnJteoPtIQ01zQ40 zii0h>w3hnO*1f)7ljT`q^DUbJSSZZ~t7%tV`Rb>CX8;QcDX?}^6Xl(IFJ7oug9)%Z zo~5abH(eS5(=-iRH&_ccWTx<&F1PoUU1zM#sHuNc2Uc;vpJrhXqd)))Rk>i_HU5XU z$iR4Bu#*bTDNZe(j5m@(j97I3yG-h?CGg)~i=O_<2EXZos4&G5`xnaja6t9^m7~Ax}(}3$}r#7CyZYqHM7Fa~+f+H$(AiEl5a#^;;G$ zUozGlFE4~65Dg~4E^#@eidygrw*=DzvifSQ z$JL(=U?Iu{8(#96h7}gZ^Md`dr>-K&G8>Wpu?wfzqsGfH} zK|i4)(N7lGW}EK}0kDu00{icHG&7GH5CmW$DGoMqm=$eTbXLE~a=|{IwR;nQh0<)W z2Fgv!qLW z0XI|>20O)UE8cMcIU%s_?_-%&FNf|0u#gl7%Pfzjj=$OKtJh??V5gT2#77lDX*O8T zj92uwA43@c3kfN(jlRv5f6CsO2w>p|M1u*i!>${tsy;Bpt0>E;{iC&D17`{EVKa_a zam}Cxt%DAUMs;8d9u3qCV!o>ZEJV3rqdfg904$8>1)DT4Me*lLH2yd;#EAcrxFv`& zw4|%VIO5X_AxiXDC29Bi0tEY)$Z$3uzJq5bRR zf(@8d4WIl1rP*K$V;8Hc=g;&7u#k`fyWiom{6vH8{Q)c-foL!RHfiwyRhnbR^Dxc4 zSv|*U!R{9U+hl~1YrCB%AL}30fz8MrsEJ&q*$7~vDi`ehs%|d;ER5#`8+M?rVx{BB ze0YT(E7+6cTVa2j=2Ja=UtffNLX_wy3+#dJ)3O09>G_E z?Kt9Vf?kv5g0(qkR|H!ED9r{-l{Qs2-T3kkfQ5t<*ne}o%YPU+j?=5b1lR#L6IEyC zcqYR%*Vq3zUJLfB2-uvKMy{!&&f`5@qEQ{#xr+Xpy!v?#02ZQLurABYX8~9k&kOd! z!S;&K0biO+OpXt%f7(xKcF`7mpfOYw2K#93h<*STazbFg=7ceB{$alXEF{IjK6%}j zR{q^xSFg!(!B)QU`5%CV(rmD?ch@M@y=pW9u#k`fd(mf-eDw6DY5)sIAR0`7eeKXs zbuoJqzSaMn?>kWoHd6%b+#5!&&!=_3=g5ghbzrS#xohetyNm*`5aoh>wRANDU|~Ej z*pAnaDN3&{p9SX-VuD+OrMK(Q<6AWkf__4j=qGE1-MafDK7ku@LSTanjxdLdAJ_s| zNQ#3^pD>=Pl=Kb1IDkAcSuWU}Dd+A1SctO0UbsI{Y4*b-1i(T<3hb9zXXIlCjr}Jt$j@JD&w>zWQpx7Kwn3SZ3_HBFW||a1f2^z(za$=d0N1J=MeX>FG>vPq}oSsLq8!(^pgd4XX&Uf%lmL!EG?)Ne<*kA0-9sb%DVXhB=1(+eTW1-nW4a|?il@w{L!x7wsgAG3KpoI{8Sg8lxq65Zim@9F>+qC`Jg zU>92XKLoIl69Q}8a2vB`)0>;H!a`CUY+7v%wfj(Ts$P@juCQCbkH>2Xpfnrose&MS z@$QbT0W2h>z&^OTK;Fkuffv8P5r_s8V84Z}Qgy7G^d6>JV`lzzE!bEQut9r_UHdPN zJgk3I2X?N)RkP@2gd=PTpeh$^deGi<01M-J!JgdZrHGnidQ##Q^6g<`)|62@<}^MJ zV4)(>PZrquw`Jh~7IH#hvq!9F`h2h348THC9PEXst!VpI3-MYc$P<5^T(F+KvK(NA zg(w^BqWBrKPqJTS01F8zun%1q%0t(G*`im239!Bgij*U(El05a7PDt*!6u1--DYay z>U?+%{tA|8R0lTUwOX^1v_iR3Wf9IpEQ7l7;z49OVFcH zIknwoq%HIlqQYREeN6F(GvnHL)M4Z!AS5LLNgldDdi4PaqBFW9cezKTx8Q}KIehzWvy z(WNq-GIm=a^b?}OVB3$G=?W_>B;h>~ z5F^eZuCR&Cs?*IX>fz%{Au0^EQ@bqci- zVIfaUmJ4?M(rKpvEJWF0&o*b2uQicA02UHbU`@tQ^0S&3_*?=w0?}XsY%}E}_*N4ybO9e;&cdoO7QbVKW6|7rP*Lr`GKlsIm3+sEF`4Bn#QKecYmujMz01FV6#`O zQw?xG@CT-Oc>Rz?TCfQcVE=!qC9JS8o)_$;lBJ5x z&7a(om>l1muCX0z(#3a*@Hr1qQ5bBa@U8f`O~?s>^*?)vSup=>I{*twaj@}JFWPx= zGTw0jdE&2=yTU$A3qJ^8A<72(BYrk*=3^5BU?Cv|wlw*&e3WsEjQ|#oKs1;Dd(GvG z@_1Gad_Y$5(|=2}VADmw8pNBq&a;g;1RO-8ICq3i1Q6wd^}nKW0I)Eg z7i@8QN5$6dW^*K7As^U*#-Awp@LKq$3n~)*WUa96dwnf{6&7+rU@O@KFhjkKR{>Z^ zii2I$UPkBb9B!`HWVv7+FI+bQuuz%}b}!wDp8KH1eE9o*JQb1uUWB*npI{yRW<&zlmj*JQb14?MHE0$`yu8?4fC6uqXCfjxkQgcR7}@^D$b zs{QZ@+;9Ygul6wX^M^L!wa~*a8b@jnkon z>9E2=lneIgwWD_cER5#`+jw7;VybcbT@tU54{VP{7IgLfiEm&5fQm#vSu5=EGHX8o z3ppXMOM0JYPWpN-2C$G62Yb^vmYVo(+-SWf%LSYCctsR|h0<)WfA3hS(hj$`1h9~h z0$U|=zx>)_|7LnMm;k%axU=eFWK0T7v*^Z%AT8KiB4B+J&0J?z9_p%pR0no+&5oK~ zcLw(buuzo?);hci-Zcy3dBHwCw@lF}TfSc674m_t`=$~dQ8p4E1_u>|!NwhEI2XV| zP6%w^_P zkODh=?GgESvpT^57LGtPm;l?R-Vjy)+GhBC*uk$e*J;6Ki-4WGtGesizP-%has@f`%0qlHy=r+m%tTWiIvfnk*M=MSUau=}suk2Ah=< zsme~PuLQ7=kOJHF>}{Fzr?6|VBES)d1`}W(?>ncemv#@Y!v1-%*%mF>uzA97x<-$! zcu-RNz>`ws$GNJxS8E~zK~lK8$AfQ2Iv4JN=28WgOwRS!>xX-0m%y-f@D zoCw&I_*$-KlfORKKdJ*ecu{+eZ~a}L0W4JIf=!HEicjE%@w{OFmDNyu9<$X+;uZ3N zUFw=kng07w8TttoiGH%c#&uiWAHYIR2<+S*XPDmwY53$9NQ#3UX<3Wz)%ws(y(Y^A zYu0bhFaQgs*4On3zDGs*uRyH;1Tb~npO_mFG zYNt@VrwdB6!G7r0NV(wCcMAXuiRPxZrVX^6oilsJ)Cr5nPM$Y@;?zmA=8v5*+t05~ zgH@~K?%Qd+j~@zMR}3F9-;+XAOd#u0a(Zhft?i^&m5?n*d4$^QXFh8Sq60?t|AG*LY|l`7wnKn8ThdlMA={q zRvReICdEAju#k`f`!Tew{IWy2sa_2xz#1O+Rec+{AD>H5skCFL7VLUI;XQ2J-I}g5 zckMg~9TJV|!20^O)BLpQ>IGmS$^~0@%kb&|7RK{}jq4SrFilPBCh-dSR@kLRCiJzQ z2k>J;s3;89+t2$mfQ6h8*d2wDOtqkg_#h2Pii7Qu7DX)%4GYn0vRtr>lWntMO8}+W zU{70n&`%DZs0LsmAqCd$#74PC{Kc057LGtPm;gKEVolY_0yIO4(Ea4pzq5wHo< zYPw$Belrs~BpTI$bsO)bIbX2r1b~Go7pzOno4x=R#`A(5=4Pkp+vnW?iC4%6HrOtY znlgDpJ?JM?B>Kr(VYl~p-3nkKCj_>|?_JE7mWH^8g`_yxwXa`M(^`73)N8U_unz|J z`Uqg5G#hMH+YQP;s~cJaSV%~LEl=Al`?aeY{+c%&foL!Rw#OtJ)v+;4@jCS*gAPV& z!7?IXx4o|EdNS`DzF!lK>cA#6cG4`~&b$Y(5aohBI?`+qfQ9kAV2!@SD8|pt34(J7 zG2*`@ZV7&ymQk1X9YC-UCHlz%yXLfVA%KOP5ZG@$qL@>6*0g~w0VKu2x<%chR?L_- zL$Aql!8V#Wbv}TF(rmB~w@;xTCN4Awu#k`f8{GM_yg~Y`<**{a5r_s8V4E*YP}xuY zj-SJ(9OZmfQ5t1$2LSdSgp*Ig`!Ip}Ewfb!8YMzpfKW-`-)q%~J&_?s^^wx3!3sElE zh*nE#0azH%3wG=C5QUG|*zOXO;{)5{Rb@KTVZJ%^6Dkt@WPzPKYv4UtVIe03wnx1P zCV$hHN&ps;;$S~tsGzL=n%>lFvRts?>(2)RSSZZ~duX)}9b+^Fw*-)o0;@=@E_bS3 zR0Iw7KT5zO8ccvK9_Oi&C3UlaX@05Z8Lb5yGGF*jm(>?j*T?f`XXqc*flX-KO7mvz zlwbf0Rk>j8%XfwWSQyU>cJGg!igSTA@!Cm<32q4@vdn1152Ns&E{GESWPvpvockTX zLQV+mf|zK=tkum>01HWRuv-^3r(5=HgYQNlPfV5zcGCqHyhR40Y_JUuJf|DqEZGbz zEF`4B4qGx@o_Q*56@Y~!5Dg~4W=C9BjeWlWpRILv#fu|au<;^b?f09wzIoFCzq}TW z>cHkKX`=}(o%j{NLX-=(^N%|v02apcf-UoGs5soFTYvbIf*5fQ|Eo^-vDUzKpQwIk zH!gvGLX_wy3#^h!z7Jp_Cj_?4JDBmU6=wrrAt?@afnjHQpsW-AuY^1?SuWVOKIc+k zg@q^^?6QMxlwYqEw*;_|kOI4MhogM!ghlwfQr6oEctnE zf=w0yo6y6=wcEf~czK~{R0r06w7q84%+O>23sElE0T$`404$8>1?!g6PvO(-_XYq9 zG2$E|SogukbS1NjlK>W?L_b+zZ(XW`Z@M5S1U773D3dq1s}X>Oq&V1L9wv0PRf@@a zO_mEbB-s*wrwdB6!CIuQqp!bPXary(Aq6(4W4PRaad3bJ2TUR05e+85Ucc6+N4as8 zr!dXM-QJ$ig3S{Fo8nZ>b!Oo29r{OgU{gFCHPh}i`V3&9Di>_4@kKiUER5#`Te!TZ zqO|7nDiW`dZx1_m?mwz%uPZ)+A1V_4WPz<=R+s}TEaZg1#&+D!csumo31A^94mMzI z7rH~bYlL2t<${eJF=rL5uuz%}_W5KNn!XZl17IN`1vYN~H(BxBjxqoXM<5zZfGvqW zuAH=RnE^~Qu>bTpE!h8~?9St2iogGXw-8DT(n6{1*^-i_xpQYSk)5oOWZ(B)mQZ9Z zl&w%C*;AHeyG%%wUC5SXNhlH_exJ{0zK{9c*InLs_Y(hklH-LrL3xeJ1p`x;f?))yXheBX;PyLn; zDNi+lenLf7KRI9s0;KHDvE^Nf4|erdZwCMi zrMY0=dk>`Zhwgp_U?Cv|HoYKN_9k^to=y#Bfh~`3sce7YINpBBykJy{2JATkSpQB2 z-lx_u=FlNxR14N^R&({;_&;3$EJXQW|3-{@023BoF9_BvYdaP5p~`59Jrn|ap?)oT zVd7W()htvL2b^2-dUqFX~SB?)b}R zh_Q|#zUi`$bfV2BD6T?3Adxic@$2C$GMgH^th!WLY4eGw)sM7dxOMMNk%FCX$Az(PU_Y|lUoDq`P==Q=f*1=jq>BW0jp zGTsLF`Oc(N4cJlwSZ50Z?-m9(+CztkQ7zc;%MR+_9@H?Hun^^g9q*mF8od(K%6*oe8}Z@S`B^}YYL*pFa|Q7u@v6i0R0zK6{KEJXQWN5*-r1hDXW zL9n$tte`RiPNoA`h_Q|#PS~lrru4d2=D%S8K$O)_&V+pv{-8gAg`61JOpk-iYeV1l z02Y#Duy-$6(04Ch#b4b+p0!y1gk9p=YzTmbC>Lx@3om+ksZjucg@hE?y2IDXO5Pl} z2n}u+$b!deFbnLBlX(hDOUn&#OyyR^=QUst6TlXA)%Q*|?>$oYs21!F+xqGw2P)bF zSg6Ved)X)iKbnQt3xXZHxhF-9F2>7R5Mv!f1l#AD0o_@z8h(KrqO5*$z&0L7F9NWT z69elSvy%B3c@l582}v^8AI%!krGADi7Rv|QVt`ByU?Iu{>(O-`o!aD)8-Rs` z6xac4B4xLSyzU8LVGFDVv%n@_w^AM~ACGUOV8?WGUjSf$U6gnl?)bPH1yUn4q&`+qy>L&;6p(y2101G)W zu!*C?m?81rHDSU+k_`4eV?}3deSp8Xggg;!?yt^802ZQLuy2>!(8KMf)d#SUkOFJ= z(^D2|*$B_MU<<4Uv%uCIaZXwIZ4Ukt=+c_^mo;Et6Tk*l`m3@(yKn$-AV#%d$2M-H zKC1Rp09c6f!Cqb&J`=#g>jl9Y`y462`-z9)37pz%GFU8)l)x!ZS zB&5Ku?OR8tZ&#@eG&t}R3m&V%EU>TWIm+30J=(xAJ$NMlng(nP0jzq4p7+bc$@t+l zG5Y_(zGqFk^}2NLO|$0hmz77|imdwD(dobaR^@5v8aU^SQp*7;W}rTrAc08rO9sM{?K z*kS@$YR4DVvh`J~=^oXB&HLF@z3f?^b^sQt^1)hHlUV~;c)cLl;GT`Bxi6RFQ)D2< zI)*r5%h%}B-Ku`ZpU6Oz)lbeT!Q1n_5G>@xz~(L;DYYbsE4zLJI5^`o3p(&!l=V5w@*m!DBU;1-5_QBZYi- z)4{OJ>+VQ?RqLQ4f+XDRzEplukDS02on}^VqjnWN@09MC*UpPAxQ>1 zv3+GaOMg24UkQ2EV)+yHdintTE&)WjU}N(26k}R6$EV0ZLJDle6@O26{}_Di5p03g zU>4Yd9;V96bswz)bsxU_-q(OlB!DeC^Idf(cObq8Cr1B2*b$A?8w}fR0k9C|gFO)B z{v9SPyj~FO)XRgZL&YP8N-R$3O_v^1gLXae)C0gmMOHsKV3&MV4nDeb*zE5QHDJ>TV0~l1tGY)SrvV3IR14O(eM9vF{gW907NUHx ztNS1517P9xf?#{KGpC|w>VJ{gLm{x`#+mYWIY~pHpHNX8?EUlyfdCeAVqg!9TE!eJ zUmp!%AxQ@NwyX+0+-28NofgZVu--G7!vGdabHUyXN}$^h?Xn3@2_PW_c9r1|&vZW% z{7DBB!h*+YFbiyh69*Nx%jIohnbzNqKGuMJNdTK_^g~r%^=+c=Q7u@9%JtQj%xx8b zg{pk8%g&_W{bAwtf?!i^mQ#mlKfKZdG1kz*bJ&srRq4gceJcPgL|OghOxW?YdpriP zkP`ztFXAvm6=dWBSV)q=rp+;@8Q0F6Bo2qzIjq8^w-bPc(p<2iQB#ykL-&mU77|im zC;D!ZrFEsgPN&84Cv5wf=a&LlD9r_X+A)eYn)~h|fQ5t< z*vWUkd$x+Yg}>>7EwCEQ0(&y$fU@!X-T2Pw=&8)-8nD|Ih`;G7di+~uaAqi8!X-wv zVE_AVtuema!vQQr`C#`iw5$qX;q`)GkFK9a`DHeJ3day)q7$~ywW@T;qOaWnEJRuT zA-cJE6MEPK6wXfS8z{2YV!A>&{qRf~%9V8YfG-1sT8q?bv zb-V&#p(3lF9I*Eco8#>^AtwfQ!pd92 zLTN78y6zpl?l;KBH(ijB0^6bbbJTiq zPurje{e+6*VC`%1JkR8@<7pzl*Szy(b>naCQ=|!;2=-B;lG+>JeVBNZZ zS4A(ci}#TuMzvto-|DEJY#l!uz(SM{R`&4e7XS;d7X%yiMMcf8I|0wKA;$V&65n*? zH?NSFo?VSMh=!;**j-s;z5`guiGjUnvWtmpSaBb~LXr&j`5yz?>vF$E5=T<(O;^yD z#eM)5N^`;1Yx`WW=Hv`KhlPX`SmVzbp0Cd9{{*nG1y+MuVBbeuD&wXM=mE>zF?GOu z4cM@S;^(k#`QKEP3nt@bd16!x*8i53dhGoie3~~z`C!{;n@@OnY8L!yRIf7Z1= zE3r7C3F|hi8lAi1C_V}mDzf^?IVF&H`DhGaAtwgbsOE7dr%m_602Y#DuogpK$WIpz z!z=2LXZ>~ZC+xyW-&z4!h;qS>JW^R1b~KxY2@44+ux~v#%3dV*!l$0V7FZ2tf!)-y zk+NC&`95$=H@M#apaC0C02@@jRJGFLh^6jPE!d*IHtPQ4H`Rg(3sw1G7rn8=J8;A6 z1;O61jHC7)4VfmfheBZUCz;ZH9a~R;0RR$=gGI!j6I>#V)r;b5U#Qf&YWQ9jt% zC6|7|goW1&f}L_>GZlRIrHRBI3W2p6{zWd&mi2;uLPb_TIbf#+pBM;WAtwg*VB8v} ztQf^27;yAo7k9z(SM@HgEq4`gNO(`2ZFYQebB}U-!H- zKX|uJ4Q7G;vU!K{P4^aMa7>G~-6+<8eM$hk!}*)4d&@r8b&qPn#hkokP`zN z9=nMN4D8+yz(SG?HgiZTdfTf|eA5Ma)?)b+wxHs`0RRh8F4&4MJLtrDX`KNqB&5KO z`~1^$?%rE704!{Q)nFFb)wgOm)^1;&66@>s6UM~oC!We6+q;T9}iNy&`SUtU`^52tX_(2R*Wc8CXVfR`3 z^aiky69YT5!%C*o>vk6aEF{TbvrcxRyT+8`qst*r1RFK%QVReJQ7+gGSydFLa$4bI zk02ohwp(CF+3KYO@skM%;pZbB%iPN}U?YRX-*o*K?DCC|!+`@a z3Sd9Z(F+2w5aoj{Y+O7Mz{2YV!J53Fs1sjC;_byD#yW;LVOz-m$X8o+o(Tg0qO5*$ zz)rI}(j34-P7LhpkaLV-x1H|+EF{TbU;AXrU7bG{NE{B$UnhUUTHBuO3Sgl$7wq@Q zrL8D`ALP84c$Kks@C;!UAH(js=R)bk!JbJI^V^{)494PYTj2HRTwS)TjY=a^25<%50ps(B!Qh0$IScvk$c2n+e4PfE*f?!v-dMDfQ;QVZfJrn}F$or9eoZG@2=qFSZ z2V1;lVj+NqoEX@O;Iqt;9fb`5EF{TbW7@gOQ|q3^XIes@IAL!-x^N1>LX-6jzcZSRUP5_>2F_VmXu z@_`w4cym3d$m%Eel%VCXUjPSy_TIWHBh*2%rvhh~xb_R7R01Ht**e9R<;AJg%y&%{N z+muwOht~y(JrtU-J8aA4-m>Vm&`+qy>L&;6?$Wix0W9Riz^2*mV4j^$%!X3}NRq*h zO|zpP`h<7UX|enXTax~6CV+*~T(DG%>&)op9kdOjf@LVPv(QI-Lof^yn8^3p@ z(x5CAe;hoqY*O z5bV(!)2YN6!IvfWPzY>ERCRjP*wtg9pHNX8?A2OZ?g3cHiGgjn>l`zp&8Hp!7LsJJ z882?je;Y^OyAjB<{yX7=J+`g-Gyn@xF4*c<%oJPiEbs%ckdOjvQ-7N*Wq++7IyIOD z_QK-T%7Nt*cEB+$IAvq30b5D{8zlRxN?sI$XZgga7ObA4u6j;rU}pdeQ4ZMPBb|Ir z0{j6iyj~Ejy!Cu)x%>8W5{nZ8o0MuqFS!575Bdoe#la5vbOxUy1359Uxo#Jk)q8&r z1h9}KgKeDhS+1MTXmZ{^Bw|Ni1NXj z?#}B1VBz(GV23t~r>wo}eU(_85ZDWQ%;~p5^Y9lOP*EIgqUY)AFkvAl1~#b9QD&|> zTo1rPk_AZ4Q7G8=G{aY6K~oZj;Y_xA7&b`hY4WgBT7{-qDRluJ*owpRoz-0YP=GkA_G|g6m zvX}Eh@95NE7T86FwUyhxHojlC3p07i-c&CT=rhyo1=-^cX`~E-W;f=~iKtCZW4tD$LFuY|v zj6RPrKd$-*iEqwOBsbuSxr^0$7N0!IrLxS6C`G9R#qD zkOEuv!}qfT8hPM-31ADX2D8BanY2}LVE(qnpzcJUZk8IbuL)qYLW)%5{vHMiW89r$I3<9pe6U&T#^bMM;q`)GFIRD)Dw6f_{{V=wjv<1zdht>26uA|DaR5

wM*r-H`(HiG$7AfEFWx~i=!`qg(w&7 z8{aXCg_V1>0kDve0&CdB+w*w+psz3yU<<4Uv%tn!E>q@rSd72vT737Vl?H6^67h3b zHt#^7VOxuwbc#J-*f@65aold>FcryCM>*O5NzhkU@E^!^(pWt1u@n! zM6jMs&FD7B!?Nf9teZ zKG@Oc4{QgpP?`(&=Jp@7ZS$9SLt{utfh`X;q1q1Uf%k`nEwCEQ0=s3~GG&8>O|QW+ zFK!uWs{tEB0PE26y~^jxIlK-_jB3HUxml{in_A&B4j{@0+dBKJIe>-N3xldV8TL_4>o=4`ilS- zUM~nXFrYs*ROOW{u{a^HgJt@3#krexpr25Y)lUxCQCa)(-dd0o0~?eP!St^mfIstw zBpGbGUtQ_G-M^>mv{*jaYxSp_16U}{1uIjeD)cUmehpwDAqDo{ZkcRqm2u0U!S!5N z@K_CIfi>K3sH|R9-vyRg?~!jk4cPkxu<^G)sJ8Sey{mgv3)aoeTD>^@Cf=$Ds`A0Q z+C=69Sa`i4*nm$Xs2e`3@cXb36Fnv9y2+GYsy{3X`^oMLtDhXOVRn;o!a_+gu)U8R zWA^wJ;|B+jB!k^Eq&vOyddnP%!=d@>xNXKAN(=C1YjW{1@?m1 zT-iyVvM)L{m<6_-Pcvo0xtVw(YEbu%qXz7M?tT8hV>)x%jl9E_I0KlD~C~V3?U{8Hqo$5 zK5D_`$<*P=^oKb!-wkdOj9_5BRbkn)UFof^ynJAQbnqUDsaNwCb+9jXQzu&|a3(-BQ1)G;vTRmz}DE>qSs`9}OIsVfGz{2YV!JZlQPUczp8vaBEVxnL- z#Xpt%WQJNnKOrg(_S5$2>j5m}#K5Lo9AsQweSH8dB*|dggmkA%5^APN91gJwdn7IT zGk}HCT(JFzt))MBwAuk+At41ezO!rEjm(&?(BL|USnya4W`Ui1&r0!q`lhz9Ouy{Y zjWl2rNnjThs|NMifM z6FP^@^>{76n*AjX`Uw?T{p6ey^t@U<5x_!D4D9oaEM`W_#dwtfl4P(MSMBKi8D>hI z7R#ToRP~@}01KtLVE?>zkw3{_Gz`E(LJDk;oej_J8S>dprv|gYw*K>%cD?rlKOd<# z!?~#jY&rp~Z=Yh-%#X$R1x#X83)aEAmfBfu5e;A=$_Kl(T6bRn3$GUhJKQ3Ns&mvj z1CAlYL?`V1Wz}f8eR4JECq%`;{*LV37QjMI3~bZJnaqq+KlZ?cg(MklV6|>k)YSH& zIxUtD_H(xqTSLF;pO0W6AqDp7^GMm~m@Rnc7uW);!7Q*%-My5BtD54^ zp7QPYHPe87NdRlPvQ*X7)2SFbM2u>|Qknmmu;wxNP!5Rl!4@<9>jGGKy&zbFlKE8S z!`^t74KY!$p5v>~fzQ470$7N$`pKEFUQLcG0W9Riz(&2ez@*mug}>>7BpK|d`rh>4 zfv@ng7UWrr<%124I$s~adbeUB;DR;nUr2x6VTeEThJ+N@8Tu<_%$h5S&|ugCtHCU= zSMKB}N}@Y_0(Em&*J!B$`USH! z!s`XWt~ESPHHo%wEU|||rvxo7n9+*u%^jhiP?6P74%m9j6LtYu$ccfSv1bd@*z1)7 zCM+b$U;~#p(+Ni|z1C^5e6S79CU*j`P?`&N=7(51z^jT3P6;3(1$Js`y6mfM%VeDz z%mQmPe7*8?Yooy}^fdoUkKXjIw&mp=7Y*2L!TRFwx-7&=Em^m(X6mWe z)L)$budaSjQ5mN$->fp&d>AYccT^DVuh>XxaMv4~rFK$C?OK;#a+jrT5}f~UC)@oU zuE*I)akg)kH;Mo}xU*tzYZxA5F2>{=y8d6yohw$n=hP&_ZER&sAKH4K(QUzex%Tnf zT^jsf@uc1JI&q3~>6UJ@RrvlKzSZsjBGvah4&+3n?5;8zCY$X3)J3;8v+!2zDpe%M zUm6Qb{pcFsMuYbR39s>sZ>o{&mVW<-tQK!xM^p9rAp!n?7whuzwp*<#0lXLx#CvB| zL#oNdheM@yQV4IAZ(rr^YoqHzSFxrzUhh9Q@P}m>6vOL%HJ)kfbf-Gt#V8r?t~KlB zyJE+e>b77$UY9kgEdehU=i+VgI9l;G!ngwPVnhnB)x3eSZ?Aq$(5=lZybFW2C|8W^u}J5jG?PoQyg!rhjw-_c`+!4_u$(Lj0^ME0PtdzjMvGb7VUCM zc1E`a^YK3ZRo9!W-1$x2lGJz|numYVl^RtFCrbMPCNISeK8tzvH7wn7kMe#JlQ{1NEeK zo#|3LDTH_MqEflnuk{z8t5{PUuZRCVd=M@M#qc(rpTV4Q@6rSCVw8+m&)c0Y$Xl<} zZNYrJ$G5t70=!t9i`V|dD#iL4JL&>nj7Z^)Iy%nNwf@l;y0w{wcdL=FLgjn!IxO|a zMW2ouykW}-=e+SY6{=zOTg?99hT(_c(E=YZ;#Hy-oxa@fFRz$#U518fPJ^5 zc2Wqh9-~jUsPdpMbQNog<29W;Xat-#U{DP2wGQW*PXX_gfES}=ys;mj$ishsZKd0S z`FLacp0feGSe%R35(nye&&CWZQCcaq{9OSZ!wEeHi~narBDSOIYgB z^2@XaFGIrX)AgsS-phuF*TPs$$ZGKhSyofK`1frFcrnYzo10=V2=HP+5bxj8T*~TH zhpu9lfH!qMo;F}m3~$Krv&^gK15W~8jFR!D zo_3}`C0=eWbyPI})$s8qUq5vk@M3W;UaOAp6&oLf8vtI6NZ~E@UnJYOm>#WLn^}09 zHgHugxm|bcOXn& z3<%==P^Aks!=?XOsht!$Z77VbkjHtA+zwsEn&Nof%7X)7@?ua7uPdFz{9Ic$9q?k5 zjMpsqko?u#r&DxWFduJBpYN{$FBa$GEy#GQIC0l!72w5)6yCtiMV`ia`}^zGW)|La z-VYV(?KdC6QWM@pbkX3ATuykycC?+IcjlVVhyRe(;`Q%ssE#o*QvqJA%g6g+U60;? z7XyNLmrvSFskU3pmD))myh-yd=_6C#)P$~LO>w*(I#0k4*D)xD_u8bh%;N=mDS#KF zWW15*R>`YYxZ!C7Zh-Y)4Igj+b^39D7qeWv*G;Vyw~U<-FGi&B`bKP*eZEx#|AWI# zu-eSRo78TTQeTlf0*FRc(Ep{tDJM*-eGO|yd^L<+CdXa||` z$5Xp?YcmV4GT1~}3|>yb9P3!()rPnY26XUu=OfTn%!=c!Tk`=v$pV97c&9Bm z&jdVNp$5DdCF5;e?m)++$5w*BR@?wN&{eD{jyKgbSRdZ7 zVNeY3v)<>JdzE%>0=yU{<26`Ni#~d~>Q>zr%*PvIy0RnS#o}DNvih!yTW{w~1H2fK z!aF?wk!R7h@r`tAGYfB{&vleP&o9EupaCN*4bb3?CE?Wz{-#>D?PGsv6FIBJ>-$4r zy*gpZcbL4G<>Pg3T#k>Q!GIv%xJ`$sZG%o^OYNi(-od}k=`THZ)Pt^KO>w+dNy&Hv zISh*7-Fz^av0u7zG2q208SlF$d2;>TvS{5F%*UJdst4FGnT7XqN_XYn>*MePs3E_%4$|N~N5UJrqFA->!-x;iCURDb*T=~~ zefdpS{Ez~(9K8Rz>0-QH@lu$)7!bsJpz~EKFTHmasht$U+h>&peW_}a8*~+GisL=r zZ~P^gyciV2yW{amri2-h3V1O}#{0;&SUw?f`#9Ye%*R`D&7ck7#o}DN*H^|WGMjH1 z3V1Ohh1V}~lB~}a%2T&Cv+&MXu}XO(TYVaqTHDHghz9Q?65jav#j2N%6>a_@tHry+ z&rrRl=M`(1yjYiy_f*Tp`vETo1o77R97@GbG(9A>lR|i><{Hr+ac;+;t5{PU?~)OH zWq=ohVt6xGXE4^Xmw|v6qh!3viX!=uV^(;b7dJpW=UskdXb#}TEEjKjT&Uvo{NxP4 zixDZjdGVcPCntWaq+6R=cpT5}YX9mw_(qM;OBrB>+m(eY6H|h7{hv8?F8&3wU=poS6=I zu`VBP&|(LC+BF6Q@%r58N6}knu9aG#5Z0CDnGpS<@c;KeK#ul4S7dDC47+X7yUNa3ybz)N;_ zv~LUD+RVcHD)hL*I5(pg9NSs7JC4)feJzEzdT?KyyyPt4Jy7!T9N_)lh+UVD_v699 zbuf7`Ac(i?+1gY`*S3MMK+Lg@CFes5vybvqC)^#NtC$tXyL`{IIKYcRF}#NcTwuEN zvKt3@F-pce{=E}jb4D)<-4@KByro)Yg;N3BR7b8-5qh~fcd&@>% zS+_Q`@Q%GQMPazSqzsl?yVAo68oa@wq;uX$zf^TM+2a*Oa#oAi?Q2!_@eZGi0WW6x zc#kYyiVwlXfFNFD%dfJ_L%hF8El_CkX5D-*f46(aIp`|Z6vsQ$Nsf~jgJO8wu1#lV z&3m#7@M4sVw?3UEZ?^U1Xx$df$2&Ry=^4O_#kqKI9PJ=KJfj)@023opcs&M$bTFPX z7(X7yO|aU`!du#`g`#h<1D+C&thsKo25$@ruW!?zsyv@55zr=bR*N_EP*wGc!L?5U zUd;0GDs65*g2{^kLA+&st*DO;?!`*&q!8XXvwXR!yTTdpVog?8IbY1lnCzzqlNWS{dFwxoEIZf zctg%BJUt9H;8!AX6Rb9~@J_ciRpwg0S^~%Rnrq-R4c=5D-q;_iIlatH{voTy>*G{i zZQAkmXTXbf`FQ86KZOEb3<%=A<+GMrpR9D0+DRe2ZYid;?W*WZz>76mUFG0C+dte1 z@M2I5uiHyCW8U_R1>nUf8L$63H~MY7*<#%m%*WexQXfN@yjYxz*VE!Kea6B51e`Wt zL<;ZJlpIgLl#~a$wV8!CFYby$7IymuEOr0Ew=*<&@00NQoGDkG(hJM^hpZNFPQHn{ z_4Pw>fEVlX@s56*i_aa!fFRzu+heHy3DfaMdYEGkB0T4vTDL0gHaK+zbQQDWc$+tA zJp%AzPz7QvsiUI#Yvtpe)AsLYz>CGXc$c)vqVK%V zw*kBuk-{4_Zo4e|n?IiO;wD&aX5rmia!BbnrEW)9>iiF*W^3>klkn;}{!$&%x8o;KkxxybI`G zim~&2CjwrKNa0Prc~Pbs^7w;pZD!#;>Tp8YV08RPSZZGGhq)TO>sAupu&Gb}Rt-u{ z#jg#Jvs%2){x#GdjZLBfFJ}38ReAY%ofiXwcvs$Yp+Z(%Y#_BjA-rpky_FYzsPzZB ziZ#XYrrT712zW6lhS%4015>cL`B%V;Q8Hep)RDIKuhLSt1@rMf%z7&ayjYxzcj2LB z%5lA)^as2ck-{6f<$>n__aJxO+RVbcFuO?6GUjMCSZbKV-US-Gi6p#5XMU@ad(u1p zA*;oEv`S5N(y}o&fEVlX@s>Jy=D_5|fFRylX3o^reXH@L9&@6n4Out|0(@w{$GT-mzCJR3GPB z;bk^*R*N^j*h1a&ym>>wi&;Kiy{x>NfENRTcq2luQ=4mi{3EqMp~>r(VnL6QXTO22 zVoh(VZaB6BZS|IF@V+GBbw2T1wdvxp z@PEi^@j5@XP#3PMmkfBZE+22NekV2oUJMB0t@d&QwdcctFsYps!aI183H`NyllRb7 ztSOGyw2i@Lz>7gKyj?z@WOipg#Ou5mCFAYdTtRo9{Hv*M3+7MWje&84VDe&dF5ak# z+Z8dNa~A<#j7Z_N|1m+<&T88P-P+8;Yv9mMIqUHNyjELp!n9=?yuV3!)!%-p^p7sU z`w^0}TD;U63w5_u8`}e3%<}Q3d|wa_crhS|_nPepYU5`2T5v2e#~MUCGX zc!QUQ(BUDcZUA14NZ}pQB*C+1)$W&dYcmUPrDnC1Ek6BVXDKvTAQmWDi z_pOSCu3}Abyd&>g8p7nopcvkRgD)^cX1DMFyci|p9Wum>{-NhQN4Ev@@vg06TmX2n zI2W(QH*3ZC)0LoYms>{b8kk?)&^J;KeK-@4b*@{234i1o5iBjG`{|3dWy`U`}-M4lk)p zM~}JI8oG*EalDG`J@~*q42t1hVR@Zt)qQz1;Ke8z?@|92v|+;5no>ta^ViD9`)oV4 z0PtdQF5Xj*KFd!nbou~zF(QT6bFr(;eTLptX!Bha+aRmWEWEw53KZj6v|9C7 zYw+GC;dL|lp-NEcw}&>7vs%2NlWf$hmzfO!yqM+V4cvYU&v`K*h&Q0m3TmDGV^^u2 z6q>xb9_IAKZ$IZiSFt9mtDNh+hw>YAfXRzNF}#lZk1>_$E!zMuM#*^B?6jw2-W}J| zZNYrJ(`G*!26(YJ7jKB%N@+PK!3pqUL<(=gh-0#$1|6E|)@Byow<+C}7ixsz@6cL~ z%~`9#TSUSeROzeA@?e=4w27S6;?>i$SKICzG8*t=mXEjdFmwEb4FiIBSHBub4Le`= zh}2FB;cc^?rHO2A1x)%Hr@M2I5uT#kpCaA@mqktEqWW4=5x1`7Rn1dhM z;|5s&)$s8?tD4>p@M4yWw@>{Jih+$*JpsHJk;1#sq@8Skt>d+!&0FTO4YJzI!doqU zpThNa04~*Y=*|rqykTL4b6!icFRHo~QTVfYa#o8s^n8Tv-cH}+hQm28 z1_bdYe;ZHr&FXCccrnL1miUG(>4!djecR?b&{fQ`y2_cn9Rdz-1iTm&!@JP)0uy(p zURA)0Q8He)xmD?qv1$6cEtrot-e<%iz>CGXcjro+B89i^hR(96TJ`bc zVcZ0(%`Cj1`a~<+n-9nH);C_&H)`<4lkt941uhyt586b|YVlIWw(8~2?rZ?OnC0WG z=X|9Z;KhI-UZ=q$D9_D9Cra(4(B$3m*pR;Q+#g2*)?{^+gZEtDZ-IapgJO7_*xh1U zH=kS$@M4sVcjltk@{vb3@6>IWIUGK&H%g^CF9+6y)8ZNUAl+V5fyvGc5lO(^?(DFcz-m9Z5mDY`|PQg+e75<6R;C)KM8ya1rI&yeM_kYO#f4q~d)Fxf# zZv(tomydUEW8bTQ7XyNLC%#%mb)K^oCokqi@y3}M)9*&r#}6qmD~|VR?NL`@@?ua7 zZ{(j-%=>ySlK?M9$#?@t9+wZ&e~rIy!40q$%%8jqqb>yjUd(dwp8il<`O{ zDZDqAU6c)}yv7#r;wD&aX5n?cxk*{gBJ}|Pob~(uHVxh%B)l`m6se4kPsU#!le1d9 zISuNmyU+Fd19&mZ#~X9Uye;6xfFRyps>_twP$do`%(0Fop7XACF{7RK*1r#3#Vo6< zoXPvK|8yI`i$O8G@r}+f_JwCV0bY!f@uudR(%Jj+uSy+JvB`U>r5S!19gB1EE;@W# zS!ijz3-Dq@3a_e8ip;OO_X^$G%);yOp-_3S;o$^WYPXh~qcwOVR}^HElzP0tTwaoE}vJ)D<$1xCM>l_e~(=nyh$Xy;cJRi z{o37J@ef%oUY|Hy^~!hSTEXPSx_rEs#t)nglNSSmc$>DEN8MW4VT0683gI1_P?LU9 zk%{-`#hR?HawhN2Q!{b_F9yZ%&bV=w$(+@o8Q{ez8Lxqv6`dH_2|rTA4Y2;J;o}{6 zv)(Vji&-w-&GAd<*1wzW2D})N!W-HtQdZP*Dc;)!H^FK%3vXT{xpH0YrZ_!I?GDFk z@ZKch4L$owwfy~Iyq^a-tHm2%Tt~e=*JB#s#Vj9hP{i$CfENRTcngagQgau)!e0+# zj&&^Yw4uKwq(MFLFH1iSQ#fTK%jAh2MeV*Gp=+6D)#hs zz#rG153ajcgZCW??~dyws+R|^;2U{zR*QFRf{nU)hf@3{1!nnpH*B~22zW6dh&SnK zAF9D{N4y6I=2*uP@rI;Tq7!Fy7zJI$tT^6-HV?x9F9yZ%j>w5+TBlr-0bY!f@%Hhr zkhk|4;0btf1FQw}@pe{5Ob5J}<>Gz0#Ef?7vIB3lhY=~f#>vLA%J0XG*R9Pgyz4iX zD3U+Fc7UaRI=FYA25-n3!Z~kzaEYpYr+Ur*A*;o^!>_LTScIZ0OkS+Z#~YRwfsbCt zfFRzU%g0fF7S-z{wUdIU4R4HSo3}L#p{rO^9B*8b4}LKRgJO6M{v|xib$p}Sg87qIZogtK;KkxxybGSzRlIm$RRX6C7?HwT$uUe; zGqK_e%m~~BtIaID4eT?NffsLk!&2uxbv>lPdya_rO@V6PrxqRlA*;pfHp^PQJJPxr z;KjOpyxHAdjsRW^2;x1WU!My2-5I~Ij5$%fxu-JaNn`x+Thf?ib(MoR(!@O*@M2I5 z??JCs%<1@r69F$q$#^T7+tU?mdViNXDq@$)qV^7*26(YJ7jK*Ot?6nVzU~LS7?Hvo zKif;T!n_vVNftN3YBLLOl%c({$HSVxaj78}j%e^cBH_*3Q=ppa+T!9rWVLwn(rnb( z1*U4m3w8N;%_l@IM!XOZ#JjM22(`*$5MC0Q2RTu^aT}`BYtrVwf{}n(R#!QA%_rLR zMZ8c{4DV9QJ4`R5NpBD@M9Fv!YDUTZzs6Zf9ThRWiRm4~5ib&g&U*IrFK&2oL4WnOm29}xfB?WGP_1DTjZE)PU37*bt8G^b_ZjHFzV|65g;CZU3OE z{pLR2n}wX!;vJh%TYcYtgADLumXG(Q>HhA37XyNL6>TR{?_BPgNi9$a@9^V#^m&i$ zF3?r1DUR1^-_bI_i$O8GH_UG^d&fHBqpUDW#ykC3XZb2?m7i`4=HuNMb?-P#UM$YV zYdZFn{7>Q4M8Jy?DZIP(>&epIetrjSzL(B6$Z9hSZRbi>IX|qmh@E#`N z4PRKKYS5|us(;98@%o!vsaGBRyBY9eT|V9`PL_WFF9rnh&YSB`HEDKrt<+8m;l01C zGF?AmWN+vy)?{^+GkMQhOvd{*U{DNi@ylDx%B=4>FnKXb#(TN=jr_;HW%zkGZh$y> zpSLd=0eCUX#k+mhUi#;S@i=)gB87KDX}YJ?*11)6YcmV)`jtl%2TX_egJb)_sd=gf zZw3kP4%d&WZSt&wf5>X_{^!FhwQQdQK2Qbg^6?tUEphTR~;rV2F38ci8#(QEmaQ&yci|p-7utBZvFGpWZf3bpS*W3 z-L4OKu{am+oK{MD_4?^9FnKW|h4+1{?XsqS#^HZ(xCvI9S$M6yM=I0h=J@yx@AT(s z8oaMbc#GmbshA&w@Jl`9tQK!xnx)#wP89)@7qfi4AqgMzVe(=?5U=Ouy3~z7v+xr( z%&`X1|EA~InIlHco-l1{?JL#>^wn9OS%4R_tgdnIGshe4VNeY3 z`es)d-=|fK053+#c-y}nCf}@lcSGu^X#T6=h1a{;9_3}fLwHJf>D$GN8oV(iykiIEt170+yF;7ESuNhY zpN{HxXJ#w~yqM+VwT-&H4Dez=5O4nd{gh8NN4x_z=0x$9uQ8!*{j54cS24@#DhIEx z)4aJbc`+!4cVxFKOs^eZp8;NslJWlVUN7&LY5r2`sEFZpRPPu7c(FJa@03sH6>d$7 zf&ni^r0~wJXd`)YN@z52KPIKYcpKHfFGhi3s^3<%=w{O}&Nb8GK9a4az=ig$R46&-$k42}fMisP*~ zcX=t`#h@5oeWmCiU#j}5?(b`psMurx#2%# zwRp?MJF3$5Jvyv}(esCr|DewNxvp*L*ymX+zmqQCg053I@R zDrfQ@>06~g;KiUA-mC35F-L8ibpyN@CFA{e!IT~zZI4&(aRaQsRzBV(XYCCDFJ`%T z=k0e2;#Lh@uxmHAH$mnV~%w!@toKE zpfNpdQ(rF_37BPdm4kQR(&hSq7lUGW7yL?OBCV~;053+#c=fU?(S{M@(xr~5*l9zn zXYKLV!&sb)*X&iiveKK3=71L?Qh0lG3YG0NZ8}Z2HnZ?{GX16Kf7=gl_Y^d2OQr_z zy7h!NY@vn)s>)eOlb}uHtQK!sqMf?n^m)AL2xj?s3(vj8dzE285O2YgzEs-7)FBR7fx{6tGyjQ(z;^SK}D28`Oa29i7OO>mD7o%jnFCuEtxnbi6OC1$4 zyxuu^n_%){aW3A2)#oWDMVX`kUW`cLU22u)`ON6)XWiP&!h1=-R8c#i{vKFr*;xB5 z4c|qa z>psAXSuWl^lgG;4HWjV{ycm(fs|p_M*(wzfENRTcz18FO0{z7x>RZ>h42n9 zc`v{BwIO~n2WyJs?S0Uz3E;(`7~U?UZZVOcti`Q85bUh7yxy2hLb zZKaN=*lEL5za9+%FBa$G-96fzPQDn{1Mp%*3UB`Vh_em)Z5pCmn^}0ByZ2Xocd6MG zmO8ZMmHQgJze#w5R3$2lR;NP#A*;pv-=DrGKYSJgc(E=Y?}eZ#)c`LB1o5`p9!8z} z-5H-FjX6=gjks9PgM~t?R?&#h@78%sEMn%d{N)ZUaWicq6MM%NKiC zI7uB9F}yaWC4PVxi*xb19}Q5f$f!CO@M1&?Z%0!j*_tcOM*?0o#Wu)lGYjt>|Gvtw z?3iP))Z(ctax{3iZ6Lg13z8M9EXNP9_=hYDuanxjhs%Dzi*@;U9Xn2s2D}&$#LIlN zri{Zk{FT~Cq0@#&U7yJJE%7dZu3}AAS2>gSexu3(fER;ec#B)bGqp}P!5i&il#JI) zy;VL;_LXcu$b<8lNs!#Vt%s{D-U-Z`Mr*^=5BF55S9c`FJ;GG6sMb z1A=&We+i&APwIuo5_5#ft52Vv>OLFrVwTla4&GW1t2YI_7!$mI#cuhjt8n}3!-t|+2d%0KxUW`cLt($Yr^TMe=qhGeUFG1lax*;)crhr3_iBeM z=5`iy7Vu(}jJNv)XL@4DEPO^2Zh*C5{^T9m{l_H0i&-w-dc#}M4{{EU0K6EH!rOg) zuxDv<5Z;(*v@P2ptIaID1?CqOf8O`S`!>9uSmlKVZxIPERi{K%?WGzom65Yryhpn< zP>;5+^%o{DX8Cv*c3zJ^1HynHUXvL;sTxzNIl^Bj=2*w_e*m@LDw}g#k8WyRs|fI7 zmeo}b-l;Jcp8{SCis5Z8JH{x_TVw)WjFR!bPMRZk|5K*YZNYrJ+h3)60$wc6#rxVW zfet_Mx)tEXh!oyu(P6T?Z4cw`TyYbuHnZ@K$o5q>-KNNbr5-B{%hTWu3n!fOhJX2@ z8uIr|@jqm>czyDm)T^(=-37c@myb8;ZQv=GyciI~drfhKs(r>3pLB>hQM`J3#&mis z8GbPbv#hRi@E%&#xIN&-pcvl8zfLo8rsnud3XGERW(S{>5A2wW-xI_Quole6`~7Lt ze87uYF5dO;oavUy%OU|UMx^j2Sx%C5t5{+TGa{+-YL-D(n^}0Tp1rIb>+)d`0NmJj zV?zHGRFkKixDZjcQQ_QuwKZt0=&2hR-0LP&Hpx0KKX95 z9FDEZ$?dHMFGIp>nNX&xTE#f#AF^7!|Gm*3z3#+gz>9VHct_0hnF)9?Ac(hyo03{S zd;CeMofN`5_*`Y$C6W&P*SY6$_^g7$xJiDV`{I zXtTFOw*~VjZ^8gSd;%sG=i*JOG)rN%M(-Nn#fTK%mj@J{ealQ@H**L64b+3;#|7yci|p zomjk2Zs+KXzv;#e5GQZNMZ5kmc`?hyYv<@eFMaQK5Ab3{3h(jbXFCqHQ5opgW)|Mn z3+pMH{R|%k$Ch&FQl!EAgM?T8tX%c8Lq2}zg`Cym)nn?YUz)vo4|p-l$9tfA|5tz) z1A=%hRDRU7nb8BK7AS<*%E6G1?RnrHbQNogXffc$pcvk|Ww)8*hkLpMUW}6Q z&i!sjPgG4DsoR42leh5UPYb|{#kqK0!hX_gyr19$RWKrjxBrLAe&2(!s3-9cR zj|zvPagSlCHBLYLq`?~*L3qQK_w%Rf%=j7O{~@cz8+5;py3qSX9N@*ee7sHeUmgp1 zF(8Qd?&VzcGR}#qrkmsA~myF(`(&Ti7n<vR#!Qv4NVKu@e?)-isAKeI>Wfs z^vCZuV3dqEEiqGmWY?E-x-FPLd9Mr&!O4roxp)hn>(Qf3Rd}fkBT{(JhRbBPwnb&? z)@Bx7D(kkQb#ASRu+)>bqf0e-Z<6r(&(rfZvF~U54_Pfc=zjpU*Llm0Kg$cc7+rv_Vpbfl``90|VDe&64DafM zi_G(@>BTU4F-pek6`m(wnehIg)KSs=wes$S5$-s|oWd>f24#qs`Wxeagkgh4U9 zlkey9My#CRlA|;Z506phz6O7ME%sceY%EH)JE>oHt(aRn_nCe!R|0&T8?NHMLbg zU(;bQ;KeK-@7qRCvH>p!1o37!+()@gdU_j2gg3|VKMxVS(*?iC zPR?ra>M^y|1LNDj0KAyx<9%q7Zv%KSAc(ilu^rS3GvnS;3ly5XJN&BCvj&H`L07RR ztE(KmZGO%k0C+JdhBxbD0<-+A;TFJ)Q8HdDr{D7R2Xk8JwqQQqsR!Thfys--xp)tb zji(zhecl6Jj7Z^~@*zsLw%vDp&?s(#)n*pnW$7!G_Z$hYzsomO zf%Rm3tS>pM#p~>Eq3+hX0)I(?Sw7x3yZ^=mUJMB0JzcjOwRQ8tg>Wn}Cpvk@HrA)l zdF{r#9%Gi(RSw<(`7dq&UJQ!iJ+tN-)9~fi!+;l~WV~~acc4d|-+)gF#|^L+%*Q(| z;uqf5AG2J%-Hz8${G2g-65z#%6kea0aL?m|Rvm&Fftz5pnT2=aMyPKSZNXbh=ez%dzs2S)Y9l5vRb_1mrd1;s;d^jryD+_iWua=qlD^b(MoxZ8>Qs;KiUA-btSKm?kBoqW~{P$#`e_|CER2 zudl7!g86vg&v=mplNXC~@t(MDKwq+ZzZdXgL<(=ZZ-cZpX*!y=%QH>! z=F)GfYfZD4KB~hhvgUtQb&{fQeMAcX(%_BQM0msYU%azi<_`IXEZ}{Ae+51P6YKKv?x8Xw051jv@fH^8 zQ4Z%CKa$!>p~*Y=_Z_)&^^}9qRjetF_sOe8n*lEd#qjp6a*-J}d_y+i#V8qX!0lsl z+P~=;-4@KByqC|sssVVhI2Z4PiS6i>ebxGa7b8-58^7LuHp(+14)@y`70tOUFm5X5V3 zVn~(SEvzTCKq0(tDOvLWN7@R>9gJO6uW@^-byRb6>FGlHjty;ckmbzcT?>%t<;$ICPZ_FbH{3Qiu zxp=ScoXEW0mx*{WB8AsEqC-mEHGT#9m6^cn_@%94M^TTPaBUwseznx%y+Xs=bN(OK zZ!Jsl{v~==hxesZl{CA|K8P2ye7qS?AAAP97!btk^)FHGax(w4)B=U@`W`f4t1f$* z4OPWC#qlm^@%Rkj#h@78_4g9gA5zj60A7sJ@wQD$W=tO2=jyj$KHj`XD_TM4#mTvN zht|wfj2YS#AK!`*DZF=TgvtipEW)QJ;1EQa3A~lgu2RM`(DzsH$|doJVG!#Du3 zU_M^c$CXC{Ud(dwc7C{#NvQQb7q$%;k-~eyA?>VU=<*2t%1q$RzwM{UxO~SN@E*JF zQB{jKD1x@$1t>FyO_2Al}3-UF5Ga?q*0WP-xo_ zlV->|tbK*YJ>i^0RXLsa*qnWz0WSu{@V35iR&C~5qdDNkC>`(4*(R)Yi$8cX2M$2| zwemafhr53k0$$8=@gAtMjZJCyssQj}L<(=wxsI}76Z6kOkH8^_G81^s1|%qtY|Jf$ zYrAPhTum+BWEx(Jj|QrwY`Z&U$m;M$J}#Fwd65?$w1@NZ@eaAM7>_u`fFNGGop$oH z&~k63UZfCSU*F42Ksz&R2{vd(~cm7lUGWD=*!r9z7w!5jrnM z>3Bm2*|MH>ul|v`qGHH$& zdcsC!z_~lVuvDwTG4-@~ztZqV_BB-1-MSxtRZh?9@XA9?(n|LE;>qZk<>MW9_W5+c zivdBr0hPwdSC7AjU-e^76mMjm4@~y;Pn)2sm=(v{cIlGdfER;ect4a|uD-@j_XfNe zrQnLT-W3@o)mC$9!tylXd6-mndSVW6s&UdWaqtHT?3-y|)1MLQ$tyf`l(@3p92 z_$Vt32;v>{!b?8C&trV*3+6=e`g|*8j%82T4pqghINm$!+h+n^42t13&s?v5xN&}U zz>85jUNbut`}l3?Ua6}hhPO+Lv=h*IadIx+4zg@^Nt#7Bz>5(nye+@9k-cp*^Q?Yl zCh(paS*&O|%IhjDb;Zj1jkI`UXn1`)8>l=!sBqgr&;B3YLH~8$%31vZFJ}38@9&$q z3_33c1o1Z8v0C1L@ui(o3l!S(cC#+e9^R10LRE22alCyl-uec3F(`)jI~Ept=5 z0$z;L@eX)VgEgI~#yu|%K>W4x_q^AFGGe z59wEC0ZdM+%-w!S{X52}h;alDUZb<o2F38k9yzF< zkrdJt@M4sX_j73t_VguxQ>iN|)_G4SZt{W7i<5KlnjQGg-U{y89Pna93h%yUX0pD9 zC-GbOXOl>SM41V^FKRbZ-tp~m2$uS^n_n|6-W(dN$=?3*9Dn+ba}rhMykT?g5x)!Y zVo(h4q%INap=XM4&x=ty-pphhwq){)F#Q(H@4VLQdp`xdI5`*Zf}h@Ot?OSs053+Q z@a{|)CaYY{A_RH_JCHO;l$pR=!NE(}aZD3@ey~T;#}-<=B~-jB1J#nriFouaJ*&fO zm0+Hh+%>2+;KeK-?@2Z;D@atimoQt>GjmvEE z^Z~a3FGi&B-v8H8wjgWRbN$Lp;GOq!p;EJisR&DrG@a2(i+9^*${V(ZhYeMy8u!KL zu+g(RydKHr)13EQ9}9Rf%g6g7z2F<*Emw3&fl#-hkUC?7OD* zeW0qC7027>Z#R5=D+a~zer|G9ZRx#iEo>VwO2_Nou_0TmSk*Z*B89hIc)atKyf>ZnD>H$2aMBNj=5`c*&O0QsQCltE6EwX09gI|W zNB@2cWuj+wc(cYDr}_UL+6(YvmX9~=pE?}yVn7h@uTz8NHq+YR-9wlY#T&WZj2-Lh z_W`PkS#i7p`yO?N&Wk}Yyn*Kv)Z?ydN&qiL>3Cbr%3-SSpX4ufRmAqZ=UN5f(|~Yt zF5Z*{-ii~!vnm5#j7Z_Fe^2A=zqc12gN#EEWhU@?T&t#hcXfUyEY-Q&-S%3%w`q7i zHW;a{`ClAdhO7>+eNvHTO~rB-0WZ$W$J=u2fpLHr1A=%T&JL4TcySEhRboyQuk|Jq zcKNd3cw!D_iK=q84aK9DE(5$66vJ!s_Okk9>(O$+i%~k>)=y9UcVo`=?owAp4DS@@ zt#QzKadIx+Da|jk=1!J5fEOcDcti7dIM=MWBL{i}4ndTez}wAxpK@iLhxpTX`(N|z zwRrPscrCt^Q&rUTGKMnIvjpCMn!snBX8>Nz^6}OQ-Y^gFVn7h@$f14ZnR6!kNxev+ zH*7KGUNgPk)GC3h;+#ZPId~tR8?_klVo(gPO^Z17Kug;Qz>85j-om2__H(Z%L-kuQ zf7{UBr~PNZi<5Kl%I(dRjW))f1-uxM!nLjWqg|nZR4(c}{8UBbUKaSDY{G zq{X{x3uVtcGr(B&#auJ53|SrC{WFR+rXKxL058tV$6Kj#{R)5=1A=(7Tn5VfjSk0? z(J?35c`s%CW;$DXwt=c*RvfRh*SubU7lUGWYhFC1Zohb{A>hR*9dG_vC-!eMFMKD0 z0}u=5Ix-tHd73$$tQNF(QTcPFi#4qbmov=~rd~@8Ax(ilK+R+55JvyzJ=X@+~); z?3Y@gQ0H}SQI%aea_kDID$Xg6cYWmPEWnFFF}zbE zCB*@#cw7JIp8)cZ$deK*=&(yz<}-eY$>mG4(K8V}cY z!nIr{EnYPZZ$Xfu>Ynj=JQ9JP)#06au1Hg(#g%h_7qfi4f4_Zl0lXLx#Ov;OLar$7 zhCimo9C0oG_pe{~1I#@)E3t$7)t(1c#jH5qE=}5;0K6C!!`sIvPF?p*sS)7CC>?J< z+jOSer=?G%uBh0axASgibHIy}bMY=4mZw;5Jvy#2=q$zPf;`z-Y$g*xw=FXn8*sN)ZzsyHW6RnDIGRg|%((`5F(QSx&*A`C%_cdk z^(!-hcgCQl%8RvLREMRyK3J{L;w_}%^_ck2^<|9!{1pa0tHW!b^jD)WyMkwxVU~~A zW8Q^)z>5JvylnhPQF|!|K%4 z)$#x@M(KF7k2hjHI<>}cWpDuEUkx9x!}I(%(0MV-#d~GD2Yaa9NL#>*5h=XCiz8*N zJ{{eyUzrKKEs}aD|NWRW4X$m6oGva}yqmUC-mu+}6}vtTN_bs{tPZb%L6PQdrDZ>$ z^WwaGyc^p7N(8(Z5X8&u%9eM_lx>uHkwSR8Ju_j|)!x*Gs^XmDcn2)_SPnWb2F38+ zyKqpQYIOneVw8^e{EF&q&4~1q`Yo7`x6+>@Hh>o==i=RI^MxIe7kCQrVnhmW$Lviq zv)e!M-i8fdNrOb03A|_4yDDGwaqS074IO%3rNx^_!)p;;>>AV7Zg&~7I=uM<3N%(L zPv!z%oR^Qc^MF)0z>5Jvygk*^<-e=H=qmLh1@T%}W!Kqn#AhtwoJ3VQ+lK1N_oo0} z42t1R>6xTH+^cH=bY6_o@$Md3j{QE&wUd4e=Hu;U;&vGD;^bVss@O2LTKGgez>5(n zyrIL|%f=<86hV)`A&4>)cz1dHRdh5ih=rvNSkbYk7H=jEubo@5>!&IWoXU{Z;eELv zU(@G#bUna}^YZaJx0+N6crhS|Hz2s1d`@v%Q>hmzg!l9(Q#QQZvq?}@oRg?32e1Fl z=ShGUgJO7>zdo(5lel&r;Ke8%??dxf%%cql@J=KgfVyoc-TQbv;KeK#??+1$Hf}~p z2H?er6y76|+nvAL8sZZ$aR{Q!1l}K>>5B5@1F(CZ^~>n3#hXXNoBz1b_0T#`{DOm? z)#1&uEz|_{Tj~#ZG0Vq0x>4*)z>5Jvymimp%i9-heg$|jM_fz%wBg(40wyu6D!yUE zEKyYs-qg!IO93wi#qd^owL?A5c+CL7i%~k>nqN%VHm2YaUQLyaeYJRlw^8=I zVb%V)`ZsH04=(6g9bUWaLe0U6!OZ|KX8Cx(`wmJ0yciI~t8N@158l`lk1@a;aV-(= zH17gtaNrJnKp19;s&epVZC4xsyciV2`!(*EdPQyx{CXIpbi4;UTw?sPd*aE0H~_I= zKHic;VR*zTX1REM-}Gkpr>~0uycm(fn`Ks0X5?{kKm3EkA&4>)cq@MJRLU+H;$eAB z;)c6x@$RPKy;1VVb>5L7YXL7ktHawc5JvyeEg;miN2) zXSmdh6xudKZm-Pd?f-rSs)}QifE{bG zZ6`iW8V8`_Z5O;Q7CJ9xxp=3JvQiHH=zIn6Vnhn>r5hFGw;w$3reB!}yp3=6R9?>s zyAIcOPWF8dE#6cb-hA^CSEsw~cvl%ctHV3I@+VE+m(qKH7qfi4ahk@P0WSsw@rG?l zme0I85kCvW9C0nN^L`s#g^lgeatKrvv*LL7ET~!tcrhr3w{TgU+Rq}dJmAGB9q-*r z)mhKmVSS{osP?aw-+4Ek^x6V=adIwR$KjI{;f-x80A7qp;Vt}KUREPLzOjB~Ch&f5 zR7Yvu_0JDjs=-?2U@hK9G`u~({c~OLejmQsqi1z^XUgAeZgi><4tO!k$7`po*aYxm zKoIY|p^N0T)63(xFqjj?d#Toc-`m&k&;_cBS#iAOrZu_)crhr3_eGZ&b+h>u4g+3{ z((%S+XD~J!>RCx$Q8B!&woJt%PH}QBUc3HwZ0MCC!vQZwr0}+G5+zFrNcPpQ%mm){ z{?^LvokQ>(x}_aY4AtWODTOzoPVX;JCVCd|4ht!C1H72!6_`dzeY}=WG_cq|1;&`8S-lGA$7!85j-q5vw8QWV7 ze)^6B5Pz-w&RaTu1D=?JSuWlg?JX6Fx#3}e7b8-5-y|8!hN}$mLmeD~C^LaK`_OyE z%hi>J!L{AwGsjDdcf)qd8@9+{X&Z7g%kk#Q$Zm>nuRqfas@Z!9DytnEV zzX7}$5X3vddyu?I?iYMli885j-XN=E%#fDV@R6T50I^_x=XGebs2$+NEElh)Sp~(*QTy8iUW`cLUAn%oa^9(0+APo{_Ch*Qb(NMY9Fb03()mv^lN{jc36yCe1&Tj?0^eo^t*xD3tM#n54 z@1i=p@Wvbr2;x2Zu!sCg?d*n9FH)%UF1+-KxpZtkK35dyB&y26JJ7n#LBNYaF}$_C z_NeFk`y~KgjMDMmf6#<|TE5d5{T9r}`>E@UDS#Iz=iFmY_BA*gQW)hgpJYSeIteU%Zu3tWyk{Fos06#p!4Fqe7spz z>aoyyF(8Q7!Y)Jh%lRmN|BX4K5n<)EpM3~h0%nP-a`66l1mP*bi$O8G=hr5x z9lMUI26!<_$GhHF&Th!Nd|2wLh`nLEJ^Zi{;Kj+gcwL$fWZrk2+!F9&L<+CL4D}gn z=UcY`FAhPJnZVm_gOy_7mR1*Fsp`qq#%u8gMN;;>|9{&Mbz#81GGqbo=bcZU0A8Gz zkN0NPiN63Z1_beTn35q|pWkYv)Qc4AywkjIGxua)=0a6*PNJ$DyvHKF9|B$sis5bP zwOifx%O?D^0i$%hsZlN1>EBB5d@CG)_-o~N-g3@6UI1Rqa`EHH6a}% zHUeIpmyb90+PbZP7XyNLmmm8m>mgr=-(h2pxR%&?1KjU0#mDd2LRB##U6kc zgJO8ylo!;)s^tem=fx-;@A{8ln2{GI;IaNV0I^^`-ljX=o&>y@<>K`m5W-#$jvNno zF(QTc^7kYsRgEEc^eZ!gH}0mVBEId?)&THETEEF!yva1Yz8}h|?#=!Du?$%q-i9U# z8vE52MSvIQ6~LQ6KM?R@KoGA@@Fn@exQVBvUZhaxZGHYH^EhLw0aO*|6vsR1(6%tZ zi$O8GGq-M5?^;^}k9)!>9dAoNHM7vS?O6R5%*X3=@H}>2oScg{FTsS}wmi)M@M1&? zZ_~bKoTHxgP0_E+1m0>M{ggv$H)Ua|7baGms>OSshSy_lIn`k6H~5B)p4H) z#qbudI<1~)n_vx{7o&8%j>ncW0Z|w6?t2`7+IgS!-Z%(4FJ`%T$D}@I`}!Am2D})N z!rRkdEsLLTw@SY<6L@P($W->QO2<8Kg+jfqlF)3i09q#De*q*P*d}4B*8q7jLhzL5iG(3(f#uj7Z^K7#Hk3 z_vi`E5vO2~C^Lb#arza-B6jdDxVCR(&1Y%xuH8X-!w!R1O z(*_KR;jQnTs7^aO{|n&7C>?L8tpz*VXYv~T7R<-nx$3kAfEOp{;vE*9#3~kdOaQzX zk;3~nfG{?{#v{-G`tpJrm7Fi_k@)ptHb+p z!ETMw)l&ljFV4%y+v(8mRe%=*f_T4u-XQl{6H!j;MGE149s7=1_xSmZ`V@Z#gac4Juj^@KYul-YF)e)Zocq9Tn ztHYaRdq7iC{+9*d#VjB1kS$L5({~IA;*BluCvW#E`m59eh42PDl`>tQ6nuoL;+*1m z2X+hE3fl$@is3C@bxiI2Y2-b?i%~k>W;Y%(uLqxq)^EZ5&g*Bi;0oZy$+>u2CU#)g zHhu37ofjigc*n6;vid9M=~-q1Z=rv0rOS(kfw0sMtFz~8@#fI*TG*SY-kv^(?}g}D z9o~e?yER)a?;HfYnC0VjTlo#oD#L&vUfX$x?5_0WSu{@J>1$uTGrhvlsAUl#ch;e~)1|&P~I=RvduZd5dSaX%BcY%f-9qXslw+ z$hu7dFGi&BM*6$Ryw;z{(67t{-nNUEDd(@P*&D9ysY!_owRlTtczqk2sNz?(T~>yy z4sY_VXpLrE(Imi&^YZaNIgt_!+Xf5>;vKI}kylwZ%vS0}3gPuVSb<%YGZF8S#yQ3D zRv!4|2;jw_7~b<=kEnlnl*dO|VU&({wnGcH!S-YK^;&2v?H^&5N;milVU$R%35+oC9M*gQ5E zs{$LhF)Tw?hqs``Va?@A&G6m^oR^PxZiA~W051jv@lKO%m1k=%MM%9!A-t78Sh62u zRd`Dz&Pi02v*%4}QfL5pF(`(&*Yu-mlN#1B(0MUR$2g63A031Ie5Fie?1WJVo(h4@d0PmRlRq20K6Ebe-CG=y-M;hrHsHk}h%ys+$LAkV z+S^>hn`_4Joe-?Wdz*&0=QCr~C%ao!p-lAb|KVM5Ml)sZ{ceC4vwXa3hQ3e(UJMB0 z{qNnHyiWTIc;^x3MDco-lxN?s$ixS#V3w#V2k(@msIGt)gJO8=J0+_lmX|gGycnh9 zb+Sxg)T;i+q^^n>UW<2ETR`W<$+>uamepk|EOy=kofjigc%5&^WVRLjhXP(4f+#bA zx7w^*isVR}Ik41>So4)yy!kY|9#_h#`X=?n4`t|C9bS3p3C%f|xgP*8X8Cyg3}|N! zcrhS|*K=Kw{O95iuca0!v~8&AQ-gJ%(dr;n73UY#tE1-uFHX+In?Be|kyL2v26!9-Tk)t;M@)CvDIBAKo5UZs1!3dKU0zIsP*TyqM+Vo&BcU zLBNXvLA<#}j`9ytQ&vkYPzbO4%0lMog%aG1;haQOIe32#aJL4$7!$z?anV)tHryYhSw^=Sha50c%L$4b$IQvPid~L3~vW`ab7;& ztoje)0WSsw@rFe-lRt^=(k`#UeC^Z@CTSUIT!C#I}i4BcAPcf#fTK%`PPoIcJh7Y z0WS_gl$pRA@+&|Qd9ueISZZn0qV-z5Y8u{zcI8xK>iq0mhO7>+RogR~tRG*k058tV z$NMQH5+A670YSXeGQY`lCOpR<>0wTE&uezln2nFU(+;YNS)!^OyloQ};~O>%is3y~ zFHU{-So4Q~7o&8%Hu6yU$=SC|q^^qCp4a4FlVPxJz{$CI8z29v80WL(B;dt}6kb_S zb6JI34`%6CW&-c!zP`#a(_-=3ezu*lQHwX5hWCc7oNAFG7T*ievpT%V4UTIVlLxVY z7qfi4w#^52gU*WqLA=Sa?d3dsX|ud~Tnb4pqghINr6hr^Z9)#h@78 z-iZg)(diA}0$z;L@rK_|VZ66=9ID@f`JK1@iYE9#6`Y)lH@4Gu_S4hTQvfeUr0`xD z5G2cRxBsVKnF+iuSy@W!bF$g6RN2<-2rb@18eaR@aw?T92%l9#&+71|{W_>woHMa2 z;KeK-?*-%84FN9(1o4jSlP+Io8-ZUqVNMk9{iRl{+c6tFbOf{Fc(;9jRUhzTPz>*v zO=s2huiwX0A~8zG8?$0OQ~1EzOzMh?b>5ppTxvq+#mTvN!~H9Cdu=znA>hS`6yDYQ zw#uenyqpSnqYse=i82#-H(pzy{BGv@9+uiMB4mpe@1|XpH*9I+ja0*Xgw-!YR)^Pa zc&w(&fqf$ZFV4%y+i!PM1>nViAYMbG74kND|Lmk*q|lzXa!X6L<8@Wt=SM>4#V8$b=Z(co{|8rb&x->Pf35t^J8^o=HGmhhT)fG5 zf3xPXGJFmjMx^k5E)13}USBXmzcLeeod=9nMtk484A(X!u-A4i-b5PSa;YmS)_Ftj7WW0b zI5`(@my~eDmM_y4(0MT;g?GpSxy*QX5+09%Ll9*q@P<{aqICFPy#g%t{hm5eTD+Mw zyn(xoRMi9jS(hQJ!|Ustq>0{k!5Q%4ynMW^)rt5tAPflNT{&4MKjAd+iqwk~>byl3 zf0@*|&#MDooRg?3r}Kt7jGqR0F(`(2QROS@aU zMZIeQUYwkZcg(pX?1D9oiU2Q0r0`xC_ubjKN_RX}3x^=eOyIqfx-3WT&bF;KeK-?$;KiUAUU%0_^=6xarGOWsbi8qYyD`VkHNB?a zg86u#-*q_ycyV$rUV{z}$^w^J&VUyqQh2`xZIX@qFvb{q1P(!znZUa|aFw#Kzd;jN zYVE=Xd$f3iqbYk{yQmV^KE0B|%aGOKEogC6({IYpBY+p@<>QSSv(N$XVn7h@fsjk` z##?UOkb03qcv~|ySo@!wFGE#vPNJ$Dy!G7LT>`uq6vO*0?~GdMaXugLVw8?|*<*9| zqu~-f-wFpH_DOua_KpwI0WW5`c-!{5q^KzSy%g|bL<;Yi$Gc=H%je#`mF z-IaQ?aBWK+;`V9r?xx`_m{;QJQ|IZdGGujl(|(=QG^}N{8}Q=1e7u@&i}9973<%=w zP$Nff7dj8`n8zG(Epg9V6k46V-K}5=R28%0cvl_?XajgLD26wyZG!rV%k(>d7o&8% zo6fanFEbVKHaZ-DSTG-Nt1vU%^J12Zw>Tx0^}RpF8}MR83U3=`g1lzH3u`FzC>3dt zC^Lb#UXFpX>4N8Yl-J1$!w+ilrqb~Ge*WjW{NSUTfR~=t;mxu=uh}y$HV^P(mX9~1 zQoGmCc`+b}cUjOJ`Ru=uFQi_iQ0HA}QiZ*?W-mS<4Cf@O%IUl|rUm#>83x7hj_h|@ zy~w}QRKSZ-I$rPQ_H5chiy`_gn2$HV`}CL4d2wQx+9Jh0cpX zF}$jR)9NpmR_p`37^UMK*p^|hFuU;6cN~D)c{8u({06+3<>Jjhr(l9)E%pIkj7Z_l zpJpZNWtd)0zcLeeH=b#t2rJyu00`Ou` z4DZahht<|Hvy*@qqjbEg1%|9bU7>^2Rnh*n@;mRB(Uq+LFHX+IyV+rp!l>rVBY+np zQh49j4w1FUsD@7i!Xbz<6L@#u3s-*5HFyI{{eHtML5p|8Zps_B|Bv@u_Kb>U$O7J~ zBN~1Lyf`l(uV0nnUVs+^f_RN843{@QQt6@8ixld-!T&j!^t~q@_k?p2RpoSE+iGt3 zObQH&;jMS|wEB{v!yCYhQ99n7xm%ggbFVJyw_rZrdpUa@0549?#e2u{0aH@{M+o4> zh!oz`w^d{fCf>y3o^S}F%mm&=y+$kh-Yz)}OO4ISNYvtulfwJug!6zhWC3sGPHuQt z8P3bcyXB*=Kj6iHAYNuq4S8p~#70stQV6g6%2H-->Q4L_5Y9fI|>vCh%UX5u*sId>%g)EUfRCq{Vwh3U9>Zk9f}uJqvhee~9`Goforw zyj|Zq<0+9C5X5`eS@YkW&L{9A5zL8h8=jsz&MbaEu^&_wvqV)nc%99iRj_Tqpcvj; zJ7U#cM+J`uycnh9EzBrk?pTbu4tQ|@V!?d89mZOB1iYB#;#Iz^z!WE0&jP#{k-}@( zAi&Wg+jWtCWhU@eefr-YP8}Eg81&7&{F7R|Z)kWunwY3&%)IRaWuj+wczeD~(xhyf zlLmM(%g5{En~t|cVn7h@=Ei$ulg;1Z=|`9&t|jhy1Kf`?{kq(I301|cI9`wK`|zpn z7!<>6_VI{%tjm=Mz>85j-hVS&v374}HvGcoFHX+Io2>f6I-13o0$z+r z;Z=-koOlZuT{b^ zjnC{e*m*I_#~bQ-Bm}k%7!bs}>Tv#lj}-5YKfuJCC|>)dbmo1yb3LdkX2tPVwX&}P zofm^*c)czjRcnk}*a2RQ((y9yo-$M3?z{tdaR6e${LX99E<6(OVwQ_{X2le_{|N6E zfEOcDcrSV_b)Hb)1|K4bLl9*q@cz^EQ5^1e9S_TEt{j`9#T!M%8)~AmtF;%uoug-U zc(ZI1G_OXK;wh1s<>R$T-+CGFVn7h@xhXmF2W!ihhii#B;#y+oo#t)DUT~?j7w}@1 zs48dMVDK+00Ptc^46ohX5nZKqJ;Khg(-m0NVGNTv2f9O|c0&f)yPo=rjL_GB-)A-prE#71r-r+k;RK|UO z;deRotPZb-V}d4UtSf%QhFLz|+IL2`2fP>%#JlwFHJOXOeI>w)IpSI(-VZjnn40cy z7D81qD~@;Or_cnzi$O8G6T2T&|IELJPXodz9j|*)HTGmw8a|T(2Ot*A$Lq47?gYS# zSuWmxKkBl9s}A8odl-?zTep9qQ}^8itn@20fj4j7Aw~181^9H+ZIPqZTDxW)4kSpuNTE*~3=BRq z0i7NXf~w-2;&>yTzl#C97!aPNpp9}RbY6_o@v0&$+3Q=%_0n&_e7qkUsIDB4*Bp09SJzff)8hR~!<#kT zMCB5{_z0AVp4H)P7;-=p)vf`4REAkT-mGPFb^%@t2;wbVyG;J8!e{&@1#?6r!p>_D z^qc83tT}EQFe{GN!ftOZz>7gKydO;C)qQ$RcLKZ^rQ_{4rxSbYUb{@Gt0MM>txaX$ zWq=na=i)V(Zm4i=KNvr4z=#yyDNa>o=RJDiLzi#}qRa%|i*-9IS7twnhox$c-npd3 zyLK<-4O`?d6V=3vy(X3+tHT@CZJ)+`h|_TByf`l(Z|ynP2LWCT2;#NuyGlOf{JB!8 z7b(Z2OKsz{DsWudA#Fn{3nv ze9@4ljA6OOeVwR70TWo$mz>5JvybXQ~ zmUruU=r6p;7b(023gPW${fmidx_Ths#jH5qp3AD*0A37=;eAnWr@B$wOMRg8Vw8^8 zJ+2=6Z+)f7`Yo7`S8=!8QNW9nbMdYi{(>3Rqr!c_ixDZjBWu~pii2x?(67t{-k|}% z74iEPEP|!ZQ2e>3#hXsUn{dcfwaR=4e$GqJ>hM}*9oE=wEf@=UG0VrBbGURg;KhI- z-q>&h#@XdZAE^Zj;dQ@Up0)h5ycbjz=M=|#=DArM;KiUAUdOZh)ThsH8wYsrxRV!z zj<;ubWA>a|$2PEF9Dv$+pT0Ub3-Dr=i`VgfYlX?i?B{?NBT{&Cqx;I-W>1nqnQ;iB z%mm)2eQcHQCRf4k*}`Me4K3ar8s5lHrm9P_ir!ErdRB+mJ}E`>q_5v}z>8Tv-eU*X ze*(N15X4($V}E%|gSB{o4CaVyiF;mOUvu{JosD=75oU?1a<&ckTxO01yciV2o7M8P zx?iI4M8JztI^MQJwlg<+SHe3^Z~$V#{LbsMw$&rRi&-w-leHJJCf!@z0=yWJ!rNfU zGw0E9{qT#-^rRYwz*$KLz+?HoO;!<+W& zyynt{)SiGBvwXZoTb`Z;yciI~Yx3&6{8m!N1*ruJb>60{tFkUVE|ow_z&VMka`0vy zkH%*YV^9q5v)jkj7b05s1H2feKdcX zP$qg-hc~iLil)WIaRz`FvwXakL4RKWUJMB0-RiSTKH%bnzEUqz2(QmK3%2FJJNU2! zoRg?32k**jBPT%T#h@78;=*wCO%vAvfES~5yqiq_Fi(8jsq|YgA1^cV=4Zf*lXLMp z9+|Aje^h-obY6@|;q796Toy5FBkp;dZz2s6WhU@0ZnQ<&ton~hu+)~fCq2;OJwd}8 z_RvgqrgoDhWytFAru{mlDaxPc3wUu}K3@Om1see`1_be{XS&NLTx(D$^&*Av25czD z_P91L4>~W-NmP}CH#q!265z$47+$|V+te#_2IDU&FiOXpJ-RxZdN~!pQp5qM+lIS0 z2TcULnC0SaxqO~t^niI20WU_R@YcBd!8vs1f(kyf3araYr(&K@I z4v(~WZ`1G&KU!Y(DB@))xS(fsc(eAM)$I29o&b0;%g0;K%;G!X#eg7QRe4AG{9Kcn zQZG^nulvfM%#I+79H=VJNmP}C_fP5j`+ygNVt6ap-L8(ax1R!?7o&8%|57Tk8&^3k z&~L%~&fEM_trEbClXLNI%528AD0vqKcrhY{H+_A5nbRDTp8A!U!27~;m*U-~EPPB^ zwfK`yw0QGrcxQGsSGkX!g^#kLXLWex7U`PaUY}M1Ud;0GmhPGL9`Is75buw}Z{?G+ z|E-5>i8-PX{STn-(2>_ujM+=QA~aA{%!=dnTofJVwejeg*?Z9_>r319D>H$2vT-YA z$h0*zV5!q9c73MByJ|mW&zsfGLUmm;20Jf3tHYZXkf!l&Q($p3YmwsSP zzEDBDzs45J9}nM!n|jQN;*ES)cyDBGP|Bmi-C(IbUL1X)#k*e$Z|#szoyw2}yygF>@ZJWTmyb7J{i-%}UJMB0 z{d8iyyjXs1yVQ#m+BP)3T7i9C-WboD$2p0ra<&cj8DCxjUJQ!i?R6+&kgLU;O~c!8b0yWL8q@L4QF>N~*CY9grt_Vt zQvfe!`FICehu~A+F(8Qdj%=X3MVo-HfERPbwM4w0G9xy|rN>~XDrSkQa`0aJ>gNi0 zF(`)D#xGetyyGr>lodwlc!OdlGp|-$@YQd@e7x}&9&87^I5`*ZAfqa*Y)nKsz>5(n zyf0o?kS*zAJWanc6L^i5tWw@`9nt}oIy5l#ofdB)4X>npL#QgwDULU-f5~RR zi$O8G3%f+A-&SqC3py`G>3E;)He;QBZo|)yZ~)@3m5(>*fd@W&7_(fwk>_Jrx6~u} zObU!h;Z4mQDy!)6uoIN|^cvD2QDy?~;YR_=!%wEMaBZ#5wfmsOyXgSs4O_Br6;-X6 zuUIB}R)^OhC{uHAx|bt#Ud;0Gc3ipF2k>G*5bvbpqvR%QOg~C3PzdjRWjXdw^D}td z6V6FgmD725wpdaQ@M2I5@6T@+)Qw(^!Si`BO2_N=x<1n|$_+nW!2zgv`%d#}2AvnP zT)Z>8*|1KovJB|F7?Hy3G~Yvpen z3V$?u4|s8MF5Y)1>#!r_vg?2sBT{%>yN;0=cI}48Amb23nF+jhD@>Jbj~;b^r7ri& z{-(v7N5ebZzPidKbCX3GvO2tSi+dWy(r>2#FV4%yyVq-ASHOz_LA>1+RptGv-+n6f zB856{fct00!MYd^6u>!&s&eqY4evb_@M2I5@7{C!)izZ#Rzc^*C>^i=<#O!ts-KMY zTQDE5!xu;Fyf`@*Z>4t28Jn8V<$xC>Qg}byd+0pa`A-t!jeqyeNC?-HvaZYi(jJi_+bY2XK;k_~} zLS3nS)DFOlQ99l+pVlx(eonxzj&J~CpTx(z!n5)l*fwC6i}(2;GuHfZEmOdY5h=Wp zJI~9^`#-&@UzrKKS$;E=uKil|glikOII~ELHhhrj4m6Znpb*}~!jFvay3CqTRh&~C?>(ENE`S$h_=y8h@wzu0@(=K0mW%hG)gIQZsR8~B2qRK>4;0K# z$y6T1V~}wOqRa%|Ehon)9=%#!6RxeVyjO`9?;{#s`G;C6rd=`Km^03Umet`6w0fus zA8;rJIxlAVcxQL^#bf<3Ac)tl)foBKIia|z#~g7j@eP~VuTo}NGtXs!7qdiFIopPr zTkkvryciV2+o(vb-uY)_UBHV`I^N{oTbbqKJk8;X;sC^g`JLB){RvCJi&-w-7hh%U zv;$ouq4Q!y3UA*hxy~JrLD+p@h-aj2ESp$fFRy=xpU-`u3CSRdXYk%_i1NSc3jWO_!$n) zDUNr6(YKC(7lWdBW3Q@Lhd)~Ycri-HtMLnG!n+2})o;Okyyp@w;zI;+axUIeBPuHY zwOi~8crhY{w?Tyfr%^u*<^WzCf+#bAcPE>q*w%efA}rPD+HJ!i^T*06K^qQH-mv+0 zuB|G4RRfQTqGxq@?S^M)yatxX^La7L$D1>`{Tz71h54yB+WQOKO2aczxem zu)iLKH;1a?oJ3VQomZLKR}OeFD2CVj>s7VFC+-E{#V8%`qtbm$-I>+5>bGD%-rS4P z_&^n$oQt*B*URd0IWv9(UX0T58tgVFK&&8rMmk2 zn``mDq2W!dVXg8Ej?F7WR);rm(`8N5i^_)3d2wDoUV~qE{{UVL2;!a8EKok-Xovbz zFH)%U8W`MWn*XYT_w(YM;&`J1TjRYAhl0tfis3EU8>zn6WDuUui%~k>X`lPBxkl^X z!-8=DDqauSoaulUvs}E!2VxXaPj;CBUW`cLEjRqIY-wJ~1;C3#5M?Itj$S`ek!CP& z6D&35^E*o|-k=!Do;Pi39aY545QpH0d6G+JIR;-hu@^dIDYy2;vPa zQOozwe-t3KKq0(7-ySnPZg5UU$2p0ra<&ccQ~r*E&Wk}Yya{_JsaF{8#PfMEO2<3! zk|XQ(Dxt1^3+8uT$4^IZ0A8G&i#KNHcy>=qSpt&i$O8Ge^cYsH~zTd zp(7ZjhNp zD6^3}X^<#0fp`41;mSE5>h}hKhYqi=s>Pd3#e2W1s&ra4{Ir3d)#0`OQ8BICtIz!b zFJ}38vx5V&0WSsw@s95pAYb)2cdXO`g*tChXbIEs!lIo}Rh*NkDhF@;I-@Uu7lUGW z-`PZ{tJrCZV9$$DI^NF9+q28e-0^c>9Ds_q-`j9J)*rK6yq~Om6y~|R76M+3Na2+i zZkNe_^|+{CnF+knyDBK3$~#qnYa94sh?N%aeHz|`ebrR=F1N;C*wC{&ylKBI(}Ewq z>J4}?%fTBI=TgfyVk_XqfFR!UzP;q8&+PGA7|apZ5<9O!(0!&xqR&XEDrUv;Mm2Lg z4tOyrhWEh1P3k@8lW^OBQ99n+f10teKhGOVT~X~{E5GyZFm8_r?cwBHyuWU*Vf*yS zj03zFk-|IgYOd3|TuU{S`Ntp9AW>!lZ?;qs6=SFy#%~ z|L?pX-y1G2Ll*GXPqM5CcyV4n-U(YLP6WId5X7sgdqC!zk%oU^m?N$wcHY+KQ<-ML zL+~^V%o0`Q;4Mk$QxEWBPz;@qTp+b$;nCO9i|bk-|G_e7)4(_Qi?NBX9_!%mm(b_QCA-=2!8{#L$J8>S^)D z(D2&j)lnT?xe`yzr)PC|3u4NrdHJ*+0(ddY$18jPtqb7AfFRx;@domf3#w0mzc9=Z z*AnsWS$~*$`LgCjs48ZOs&eq2C|*At@M2I5@9UwF>fPy)8=>=Jl#bWVP{mqhyvF-^ zaR6e$e7uAA{=p+oG0Vkk9{qzETI7LGeaDCtUiWWRQ@+i!tFK>~3A~4H^;Wp7y0;Rp z?QX}N4YYXEX?T;b)m1eJ%x_zUtPbzXKW1quy?5Xdr#LSk?=O#vzX2}>1o7r{wU+00 z={8mBMG9>j_N@QHgw~lf1FDL1isMaczrQ8m#h@78gLUqy|9p;g1iTofjCD=3G$T6!2m| z5bx)g{_?@sr$3Zhpb%aI10y!uZ(lCp#W{(paysww%&qePF9yZ%T8=!WZa?Fk1>nUf z9q)U$ax8N#^PPSR=Hor}^A>(RjFWTmn!LKmHcQ;t7w}?43h&16xz6tohi=xd%mm)* zGhQjqUh(#arG`ze(nO25gof8HwU)|lek*)v5gJO8M_d2Fd?812t z8%F7PKb+aY_#3y~EOkZ2K5ei!f3XERFHX+I>-oiqT~y6y7~sW-6y6>?JIW&39dy;N z%mm)mTW%;K6LavBq|W;mHPhnVc7*bVEo@6&Rk-DK{1pa0tHaxKk3rgs%v*R@8D{x- zcQ1~e2Y4|ch_{hdb@_n3_3&hL%!%SPFvw^8pB&GEs$y0gZ=&maJk}qBVtDhS&#OP> z^nMJT7o&8%b9b1qzideA_~c_kk_m$tyW%94goXr;w_TMBQ<^j7#qBs~jw%eQNn1b8va$Lp~2W(;&* z3<%;qU(iOLz1{^+M#r2e-lkW-FzNj+b_TqdC92BV^A7If^b+u5Pz>*cmlxHi0-WCh zUX0T5?k{=s-*1=ht^&L`0I^_x=Y7%SPFKK-SuS3m)Nf3+$M0tXUW`cL{kq>>*0ou6 zJnjjHAj(YOE$6mL@uZKRB`kIAab;UA-h3L~$RcZ1u3=yNhK-)p;q^#1POIj%G8yn< zmV@`dH*5*!?;iqQ3<%bg5rYJoy;*orKkF{fTe;M47JPNJ$Dyvc)a1OZ+Q zis7~Oy{2yXa_V`&i%~k>H*1G8!&7%{(QmWsY4(^jz>5Jvyyn-!?f&4Tvh|iVcvsopQ77%Sc=yxrT6J%z%8D3?KM$j4b$CN! z4bpP#KQ;%vnC0U=?wQpe@M1s^@34&z{_zfG*%g5{Ky?H(0#eg8*QR|n>mqnk6k$RCro!8#pkbORFMhsLH z=On7i>Ab<+oB9A=42t3HReqDYsNfQQ!-i2h-X<-KST^wltKWk8c&)99Rs&v~oQt>T zpD4z}pyx%vixDZjyB{x?_3P(?_x$4!M41V^D}rw*LLX}IyfMp#2OYI|vuSt}t~XG9 zeq?(G$~0{)Evv(8SKlbD!HMThpz~sukM~MRNfW?}0YSX21`c8-uJSuA^&*AvPOE3j zcK)0?4DjNdL{&L>ZK^N+2zW6lhPTn&1oi9akJF*^Vw8?Irfm=AYvX75dvF|p+If|; zPyYtInC0TF7x9$sZ@g(Z;Khg(UN47yne+Nv_)7{Lf+#bAciP%rN*`8M2d-^mrvc7d zyoEHpJ^R|Is>WxxC_`3T#KJKzA|#eg8*l}@MRyPS_+mU@vw zcwe{r%%rmp_(W%%lc*{OZ_9=5h z=l!y{v=QLN$+>vl>YQVjxyRZ9UW`cL-RjUu7WVxlmbqGY(jZZ00&iyf#>%SS7U4}- zKRqoNE#6IWls9Y^-VIfc)~ybLGSRdDhj&JShH+nc2Jm8*k9X?4ODzE}1_bdI*|(K% zx2f|_>O~6S4R(6W%>2?n0y;0wNmP}CccWK+XTXa=F}!y5qtz9L*nI%J7^UO=oMXYZ zIrFnXzXkL0o=b^~1iUyo7jM4Ba`wEtZDqiV5h=VE;-)0YSXs7ZT)0 z3$ON2dbc&13suEA#qpNPjvoZP7!85j-dVNxFeQ$4 zKI^w&KHk^1xgLNQC+FhzIJ#Kz!rOZw;Khg(-s2a8WCN3euj^N40NE3!2s)uB*T%!=dPRo~?_;KiUA-ea15>Y8_6-vGQArQ?-# zY|QwzDvujM9DrCbAMadcav(ooNdFb9Cjn%#h@78weGvs%g*d= z26!<_$2;%00o(nc;Ww!(s{L2P$9tr8r(J+I`y8o(i`TGOZMK`imLq@{BT{&$PrvMZ zI{CH_lo^L0%1q#$T0ULTGk8~dSn7)V&ONnwgX1ZC-moVPRK7K*H!VX}hc|FjktVtN z5Ih+j=jG$=5%ts(@M1s^@5r$8^4pGg@#uHViQ@J7X2updH}r+7VwR{X2XE4$D|kyJ z2F36;P#sd|$6v)mM=(mq8=SP0IXHJ#bE&H$hF5h`xfAf>9wo76vxgoAycm(f zJLp@Otjn5?pP|ej-jD`~G81@Luku!oie^e+sRozxdTa6SmcrXQkXc`bEa0uS*lZkh zUYwVYcZE#00q|l#5UL-?{B-?P*uzlRpsEF74g0%bY2XK z;jP&yO1*fgO+)Cs7^UNVXkNms?|$`))Kw9~8#dgpGvLL^xp=d0d}Ffy<>mlhj7Z__ z+q;|N5R2-A^eZ!gckqUE#l#jtjGu$9$XdtSR8d zh!oz$-qx~_aUNauD>H$2?$Z^Dp2bdh2z-YRi`=z%AJOnyTyLxz);Gx%T+p*RylKA* zHG7I{y8&Lz^6}1SQxkuHi2*^pGoQVbKi@aJw$zIh!h3&dIktUlF@8ybbBg1Qz4yot z@M2I5uPl78+GowH9O%58{*V`hj`#Dc5GLVmV0TzB4nW0g8+yGR;KeK#@2+mcmFc&) z)B?O1k-~e~XP2z)4wrnui$f4)Ch!)Gic&ToP#OtK&2jnVp~d@?hBu3~RlTma3_p~i zXLWcjh8AmrZdZ>0yqM+VJv$&a1UfGU1o5u^>mv6aaDI=}0)_DQs`iJu*+`B*z{EL; zs&cjs!%aKx0K6C!!`p0jw7S^RU_0Q&C>?L@`992sl*Z5XTQI-#S}xg#=QiNvT)d~2 zE>l>K510&iF(QRG-Q}aRiQK^n@Zu0enF+j~5?d?ZIN!hnF~is;gSB`!Bv9V4SqyBV z`mom+k9(qLb$Ig!{MM8v{l=fZW0sG1^L4|KfENRTcozjMm1noAFZm*c@Vc)wV<%K% zte~nmCs9=n-YSlEc<2ZQ#qd^}dPTibnKK{oVw8^8&DoGKy3lYo;Kc!`o!4yO8#Q!Z z%yRMC?z_*<=xcoo@M1&?@0&rrWV_U>M(9^&0`Hi9U6tih8#ace9y(aTQ;RoF3a^{X z?tW#+0^T}SQ>>u#;=FvkcQ@qXL34+C|#I^h%!2kQ4_uC(4&ifVk zXhzJ6#V|SpBnC8L~RO1_q^?lCgXD174h$k9Uze7QdvxfFRzK%wF=P%Q@%HVNMjUXNe(u z;N68{%yk36o zIsjgroQrp&cPG}&X+Q3HF(QR`d!t3N_E{4d{mM+>edc>#G3)MOCs=CzWg#Q9c;C?Q z=3i{8ir?srzhR?ib$BDUmuhY`AB*=kV3v=!wp*t)ux-GAAl~0k)8#X=1Mt%Z%!%S% zc&ReGqRFN5P*u!|PAj*libdUW`cL-5ESe7QLz^e%gRT5M?ItZfV9U;|Iwe0bY|; zuA{VggN{=6yu%}!srq)#$6G+?Ssh-BT83%uH|9-+&Wl+--oY{N&jVfz2;!|(rv|%t ze8rwp3l!S(o^E5xwivs{2=L;ZL{&MR_u0c_{G1nqVt5zKn5~Xj(6c_^#V8%`!enFi zuX;ziehcQ~wP}^q2JqtKT)aDaUS=x}aaaU+F(QT6p!A%q%Y-vS^eZ!g_s~9H<%bOO zDzMZsewW8+@kY_`-f(E4iksvAqYPOc-W!>}HGeZA{Q)n|%f~zVVRSO!#eg8*)i=k> z<;BhM7);C&jR^O=3svRVkMDYVLRB#?pvC5h=W9jfcuczsvZfUzrKK!QbC0 z-tDo#zth5Hj^nj>lWBMhT$`&j@4w=G-t?>vZMuv23@_zS}vaV-&Vz-@E(shOiSR28%0c#W5jN`Y+y2F38+I2oc|V!GHF@M4sX z*ZPwM`|Q?VJdhX%AQsHW`!J&#e%gRpF5b8G#waHEt5yMCj7Z`AdZ3GZQ5~nIP-gE4 z(jZZ00`H~ErpjuQUbcm6>*juMf)?+6D&E~qRIJUA;bq9`@b=tOF73w8MHYY;=jG!~ z=(-zkM#q34-b(%3Gwlo4?38+uLfeMQElt_2xqI3|RdG(Ds+?`Z^Cxw}0WSu{@K&t1 zNj>bsO>e-9Q99o4V-7P}(JgVGgac6V=9W(w2%Q(RT)f@OpH<}e$K3_0R{~v!7MF}B9R>+CgyG8@P!FO-!~A;s_aeLpXk=jU-d<8hw;fZOA79`|$Y-Z|%a#>_^57o&8%+LAbS zz!~es#w}Rbd83-&!fy}bp_|5Sp(kaIBQ)N7qSiTVpfPZusW9q zcrhS~_uI-!?D$6^-f|l$iuXiqZg%*k2GDtNPNJ$jyzMt$#aEnSPztZb$IaR@OWaEU zFGlHj`?vncp5OKIzHti{;yn~~Xf1SJoScu>&*TDU{o7*~;Khg>UdzmmO!BM7%Zw{C zfp^>EG*$aFHQv@}zUKQ3J>D1^-dUlJnvGxT41_Y#vj)5o+ii5tt1Ny4Ud#&duA1kL zKT=>o6z|MWo0)N!Ug3AxFh~3s{U1QXj}$4Ys$4+bH+c0Nv(k7=D&3g{ofm^rczthe z*K!seCjefI%HUnLg?;sc!vjGafLO2)FE{Y=Jiv=tK3?Z5{kg`i%6$X87?H#K{`Eb@ z_}L#<0A3t|C^La~SW#D1rIh1%b4~uJxwG|nuha0lC>%BC?Fx4TUV7Gm*U8dGcic^j zPY+{Oh}X1Ty(H+o7!buf=+RYH_qZp%m;!UezC^rzy4Z51UCs=Ls$!O?DzEd-{S@62 z@M2I3?|z@PT8GkMcuOQk>3HAYGU0xjHphQ8H~_I=Azn7)Cf=BXSw7y+y$&kNdA1!1 zcrhY}H|TMgVpChicH_!S;N8=1j%sZsrxF0T&em+69&aWMuSszY&4L>)_!I^`YryN> zz(%*!?RW-sUd#&dhL`%N2D}&$#ml8EWd=K4xFEMcvBQS0kE}Sikcmg3syL@K-t^9+ z@D-;Rl)^hixkLM^ZN)I?ycnh9^?u)gc(YfRx&xgTC+FkUU3|k%%WOLx z@M1&`@4{V6660;7A(X&qgHq~z>8Tv-i$|$ zxNk1S0{|~ZlpiOZ0e8%i$e9Y@!vEiJk?#z0!J_0ba}s@h*PSAFnoGKooDih30I}deJB4Hd5@c zA!S7cF73&EKd36sNmP}G_W@^{1b8thh1cs+h_=|KQGLLRQ99mtCqJ;2GzmM6Td)wX z<=e#dfEOp{nrsh;_klaR! z;oYh7rfmG=aj}7gCyphl6X=|@AJqCC&O2>PpAeB9s-ma!`3l`$_ zncu-4@Z#iryj9&?xh?Tm8R)zik;7YZvytMj?}kc%7l$CqOyJFkKB9Ds-DC+%ZMUHR zNQ0d)w*Cx&D|Bcrh!)`__L~YdCDcfGFN`mD8E2nyq1S z3lzhfvcinB&iJ(ys)}5(%yiXMq6?;-f-7v1q1m2j| zF{+$4*>_>zy6)H#pvN0c!|P&EQ?qBwW4r}~o;Be0K47C8rrok1@M2bocgL0lE5M5Z zQM^Ajw(QHg!|*3W%n|$Ye*g_XQv6CR&COZatqW8Yv(k8d-cBwCycm?i>ukASn^T0WU`6@DBBgR@_{1 zX`OLpCh#8Fv_KVorE5i4>cS>d*Xr?VX?S(}9X07;A61Zj=0?jJ@P4XLLFeT#?jYdB ztPpSIIz3hbUJQuh4d}Crc{lD?sN6=1b>0t|w%ii$4fw7yoKqUFm8~7#Rfa(+yp3bG zX={%23EB8e`Ui0%$pgvU?JXy$41%$UYwkdxB21j+}#U)c+86tIlK?1Usv?F z==c}#;t)ic3A`GI399^4rg5;;ad)e2(Bpkh!y7THhUU;c=OzD;HQ-(SvAmACnt`u- z!g+;wpG~<^4e(+>6z^8ojZ99B``CFgC)s(=eKzBc4AkC%s$!O?D(|r2th!1xbY2Wf z;k9eBLHjy+&0@fdQ954Fqmk^~;Jm4Fdqt}Awo{c`1$c3CK3>mmWt6+UifTaT#fThU zuV&xef*w}Hce~&aM41V^ztg6wwuO(u*BWHkhzi!@{Yk?c@9v;+Z(a^v(6a`-S)D5D zEPra+L+8b;5O2Y38*jji0a3hmZ-y|t_n4M}eTg|qyva!)*j@o6m4FwsL{)isYgM`a z67XVB3h#!M{@NI>0I&06l#bV-cO9;#Pa!@Vg98u?7Ixms`?AIZUd;0G{@wqeg$}^?HsGAn zcqc6heF1neD22D(=s@j!-9G##1xD$39dB84QI(4Dy`MM$74I^O>Dho6vwXZZ(=@7C ze@^#+&WjN_yz>&06=x?;z}NcY5JZ^?yvjkTs(9{4E!elFM=oyBi+4kc^u%yh#cPTe`6J1KaL+XuFM49tm#`+%GM=EVW}3?7liBaCeiQ)53Qu> z)qDb8LZxR7cwL^`=`wFR^a8w?72@rFqlGiz#egW@APXIH!lD8Ggort!5#iN_D`S7L zKcAT4M+7k|jkivG{j1PQTF0WU`Bcr*9!U}pvPzAd*$rH*<1oHm~V zyf`@@uX%)%a^ke*h!-Prcz+!URh+1=js?6p1W{%J?`>wAYF5yFyp5yB!&VV`yg4+y zpH|yyCLBBv3}vEc4S4N+>~+p*cFzGXW`%fld1+q&F9t;M{+Mup*&A$ARc<52I`5US z<+<<+Hnh7lTrGU(O2GUb4P?2Jm8(jyFVim0cc_JIc5P3p=kz z%Arw!7boZA{qm$QH}U3?-_Ut6B8RtCUXsG1b+4z!m6^c%$~;K*=23J%SnBw^gOPf? z{--I&yzv`tHDxc`*4|)XvUd#&dwrR4cCg8<@DBjHWiQE;>zL9bZ z6vO+Wb_Fi=NT<$FRh&~A@1sSL_}&H#O5uIif4jD&fBreZi%~k>v-cC(&hGv08Mj~| zUY%QWd}9ty&d0kwrGm0VTY3@T#fTi<3l|)i$w?K)8CPZk@6N2Hs*|zx%ED6DZLP6O zk9Ri}?`&($j^eT=|ByA{JyyDg&Le;1E5M8M3h`czUs4+IVn7t{(uEJ022(qoklRQx zyyvEyaGwKGPeWC4PHDWo2UfTQofm^rcxMd_);60mtuNrkC>?K~tPWgo-Fi2TTd)vs z%m0)m(0OrkK3@MmrIbMfH+chIjL6~j8(yN=TGDx!ab+g(hKyoV_Z_bk!cyOVUcX0= z_Yw`S)1k5&-%)qs{~>F@Yoc`0HFO^Q6!7A_LcCMUJG}7gCyvv?$)UI=mc?)nxh7Z9&qroTq2hY3RHdk;7|O&{lD#!c@Hf35OucOyKnivrzrnz4Ztz zbwI4?K|S7l8s1NDEj3oon&N-R8t{6>JL!&>A9xAy;=Dq3A0(|NlRj z{BkaSlL7}I7A(Zueb}Bvz>8Tv-txDsxKIY-Qr4(aiRoS~es&C0UWd|Lhm-$zK#8t{6*tD`GwSiTwH#jFr-diy2!0WStb z@wQ_Mn4nDqZoyv|=7@cXoj2mC4Oeuv-%zM3W~K2q-SVpv;KiU6-gQk6YfD>RuK{>5 zO2-@C(~4UY(;naHiUSY}7UC_gJz@vo#VjB1P2WPU$KxkW053*l@xC~uD5(^(*tjwi zc)weWRRy(6n+W^1)N8LJdb~$yc&%rY((Jz)@ZUdV4R}4XYU`R_^}%CaoL7kV+0)@C z051ka@x}%fG6Bzrd&q61*fH{-te2MYJe9f=i^PtPv^Y8WPAj?7?H!85jUXzUr*kND#buwwj@tk)PR_?0?7Ul9YxM;Dh#*Gf@Lv5A zsOV9)CVmYFhak#K;Pv|UMs@t*t2VII8zcLl(BpkW!y9p}SpB{7y_|o@{vX~!PCAF3 z8L5C5=N01Jx2M`*z>5J*tE#x**4DaB@<+=Cgn>U2ci*piH<>75vX4pKy zi$N*8%}?yp_8fHrzdejmI^K}Tv+RLoTe=vxU?JXR9hwdTyf`@@@7}ah$}96+e?sTQ zh#cNspHC>Js8*yHS7rk5yb5hpH}1X09~x4Bnw-|-U4E8w%=;;*Sewp)tLcGn2pL_+p7!bufGkrL-m~B}D_9fbS7rjQBet)Ox5YW~K3#FH>V9 z;KiU6-a$!cw4VFy?!YlGM(KFJP2I;{9(ACB+#c2cs}bVOm}Juh@Z#iryq*KAbN&A6 z-UHq))@unsa(KfIgt*Onn(!UUj6)D*Ch%qs4OiAtyut2S=R(m%J>C==UQesPYP%Kc z@lYmu)_^y9W*yz$>}wYRFJ^^!3$_I$16~Y>;?3@qr)c4whc8saoFv{WW8br#=WTR@ zs$!O?DzEeQ^hB`}FHX+K z+wqk(d!t(ArGOVBa(H{4Ue{@Lr>l6vhC>i#Ch%75XREy7k=O&4YBzS;6+PZO8s6c% zeySUmpE~p(vIe}v%h%S8I8gNg;Kg}`c=u{Tb^=}uh~n+~`VeDUrcRXHMv5Kt#&xjb z!d<`Z1iUyWQB@w^hodqs16~YD;ayyIpSJSf2`+#aqjbFf;kViI2bXciEm+ujOIb_| z0K7OkAFpMvead^spSJ_N7?H#Kx$b_&&t30s8&_rm?^?$$Do>YI_=<|V^D?x0yz9?V zPS`wG6sd34t&W$<=vf2aV6$4fNfYKh0=$?N;@y3BNF?CJfGA$)hl82l({`l8zQmkl z=e?2sjXl2l$Tz4eW~K46i&}00ycm?iyUqQ8c4gf$v49t&bi9Kj3t6k?rSTvi2Ot(K z#QRo}+XL`omXG(%0(Vut{Zm>4UW~}$jqhip7#JQj+PE?kc$z z+eop_8?pU4yMK3OU#Ke1DUG*m^hWHu;Z0VXXs&cu}Ud#&d?y(uX1@K}(6tC^LvCRD%?%A*} zF-J5ayxQ<}fEibKupeH4#H=*l8Ex1i=)4$|!h5{y8EtoqBD~swQ99m~`{UTPd&=UC zIXD2ZU?E;lOVcpGi&;M2W4)_z5f!SR0=yWJ!`t9mFU7mblkjOP9D*n_fp^~RkIEli zCi%d=9dy0z9X;Mm8eXq0CK}iE)$#SH^sE7I`hO0(F>_Ci1H70O;yvq->k4==Ac}WN z+5XJ&a>|o(3l!_TrRV)-73LL7pe5j(L{)jmyq80&H~?M@O5r_HbCcrhY}*LL&}MYYz0>KRvN0`GEN zW7W0Ni;uxlTlBqjSC6-thSw$KuR8v#E#8qv&l>Q4>RU}0s*Ah^crh!)+q3Ia{COAy zqIkXEdN3Qt>^?2GKry`k@BO@Mn{2xZRmC}_@dk|>U;}tDD1|rZ#z}3z&%IXyUX0T5 zW@?+UNqwp;HEzK|yq%|y+YWd)k0CYi@z%MxU)jZMl?~vI8h9cy8xdDf-bgn!5y@S2!Z)x8?n+63_8yh6MS z6B{wmc`+c0x9058%$b8x`{g!L3~$P{&+MP4dnQ0taZaMDyw2N`i?Rc}7?i@BXns^1 z+%g!yNr6#1UfnxOZflva=Ef~ph&TRV)lGmGC+Fks*ye~bVU?{J;Khg>UWd5$iqhjU zTN+np0`Ki>XOwjZlvL=G?d{M-ri`n3cvmzu}1pz>7gCycIl7 zX_cw(*FxvTC>?M0`~>#rl2p7gr$dHdkLv$gg?Mx3FT|@2nC0W0HTHqh-p-^F;Khg> z-aR|FDn4#-dIV+0A&4>)cunuNRxNw}8&BA-h3t5&$NNAI@7%TP`T|~h7Vz#Fc^%(X zhFKxr6>rSq051ka@tUOkV0Ii|i*EzOoFv{hZHn1yjjX;vRWVCcmDhRK@0x-y9l@X! zUemk-+QXafE&{w5rQ>ZrZZ&&hObfgR6bB#{EW|r&lDZyrUd;0G{wxXS*o$G2fEOcj zc;|c=sc0YfXq$0mCh$IOKUKAGTGmwnSaX$EnjY^b8eZn5xu$Vw*Yf|6HQ-Gy=b&3> z>wg(KFU~8(dv#bl{COAyqIh2{uEM;i?uD;=!W^+LvGX=%Gudj9#ZgdI%u3@ev#QZ3 z=)4$|!n>^0MQy~$Yu^AbM(KDvygtbGQdj6Mw^yV(?_C>*pMV!9=i_bpJe8esSaTlm zVnhya_4&?j1Hv!+8&_rmZ!IT3rE812_zTOD z-1FIvf8+G50dM*^2i?u?RW*PYvqHSU49^;g<$ICKW^VnhyaOoeTVGu^l2L)th5QDy>frTprusx{K_ zyAqk1Gc)ygpVRPqb}dma|LV3F@Y1seyvaQ(=}vCkhIf@=R){w!w(29mivdx*9k*^{ znhp-MliNtK&iiX^J{vH=cNyTtIf<(B@aDy|JqLI(D1~?H`QuuLty^~hUX0T5mb>o6 z{*C;IzlY-hRJ_4c^6LU#%<}P;pHW#EaPRz9z>5(%ym?hi+%AuPfiIxPA&4>)c*9?< zQ#I~wH3;_YzLng6db~ercnf_?)K?G1&HIO}0q?9Om2_?TSpI;{i}MQcTGq>52Y4|c ziZ|`FKeKR}>pr=S6vO*A`rS+WvFV0C+m4|oH=>vTLF9xOX){efQ{bJ*Wzpz%^qG5v4KsjMsJ@v2Jw&&aH|ByA{jUQP_S7+^rB z72>@Zx^5}p#egW@Ybr~&%=7#Nxs4RV`(JD&Zc_J)^Ps9YCs9=%UN`p{#{e$|rSO*D za9TUat}WhGhEY1+1LYpGHa6}2ja#trupz8-tM<@&adJN1nT5@{OChVGpz~rx4zFt| zOQzqedDo3AGl6$u(oogMi*1y!)CIdY=jidq(eNHiFILx_e*{kr=vf0^&plOj121ki z2fUaS;ypiTKp5b~fGA$SWsR7L^|a;W7AS_-`&};Eb7?F-J&bco7f@g{lCWZN%X)zr8J3-Nv}U(ylq;^ch1ZfWB=@4+WO173{C;a#aI zc8d#f!zU?l2%^jc-a8L>DnIURf;Z;4UaI&}k2i^iH`?T<`uM{9|#V;|1R`()gLg?Jw%Fe3pkPR_?WNil(2 z;~#tl@M1&`uV?H@#p|j)@Y5eS1W{%JuUVTjsw2-k_JXB4j@$TIk2i;kH}04E-4y>t z|ByA{b&0H?i%5Pk7dkJ_E5!SJ*31;Zivdx*lRJ%I&P^GKUyQ+=B;L56e_8JY=U;#q zvqV*Sc&99Md<1wgD24ay?jzcEUAo0V=fx-;Z(@80u31XcfpU9A|F1@f_v%K=V!(@& z^YKRcSt~QlkKP5m7?H#4HgL8g{B~EoF$aer%1q$R-!V#c(ou5-mipDgJx`C<|03m> z*S@5lz5RD*MZk+eDZGQ`L~Fl1e^3VSVw8?I`rL1p`|Y?wZjVag ztzFz4e__MP`FKZ0m?#g_{o?_6F(QZe_IGzh#G2wE3Y=i*B4@zs45TdWe1ODfER;Oc#otX(LT>Aa~AMol#X}#pRMd{ z|4e)g2nQhk)d)LpfO0Ng=fx}^Z?|K0xffoZZvihx zQM~3i$Fl0yEj{HnQVg&6fofdg!!r0y3Y?RuDi80AO%qE4-gB{JRi*IWbGfCp9d79l zcrhx2_h%Kwnpl^IuwWd3iZ}aIb1OJ(z$_mx^QE=2Rh*NkDi7}upAoTu7lTrGmtWbg z?U~|o2=HQ*jyE{glk4hH1-~YZ15oiE{nL68;KeK-uX6Bqu1fHszknAba(H)JSTokn zJ{OEDGlBQxD0kKA!Pb7TZ!hoKQl!V5Ps1DS`$Ii>NngDAj-EB(9Ug403ti;a7Vu(L zh&Q1115fC@7!bu9{xywJ2ASZ^=$Iq+<^KR0t~OM0vgPU?s)UcVVpbaOJ@0WSun z@csz*(Pn;*I1P9)O2_MK*OAjIZSm?m4nQnec-WxbF&QtFVU~|~N9+e~pU>=PfEOcj zc;_9P#H2Xiz#f4^5M?ItwtVBFnm_t2KIK0y)3!v9H{=rKge`t&kve6Kw->;tXAO9x z^UCPnRqN>icrh!)yYEHjAi#?OQM|1(w=f$AFZe3Akz$?qSGUsKpQ($ipe5j(L{)j6 zw_XZ&67XVB3U69mxVG=Zt9Wk%M(KDHUc|B9-`4*%ZoxvlGrrrcfX<7P^YLC9tK?4S zY^()%F(QX|ohnuFr{+-nCIt>bl$pS*b^NQeywDwgJ)QaG{9irZBQ(5TPfFAeUtGdZ zG}E&Nyjd5@=$tEW!$;pSE5v(pWFbBVgaJ{!a}Ibj8Rmg8urD!3G$QQ0gB9kS@9oqo zfETkwRe5+{_iq>vcrhr2cYo$d?dA{N-azNYC>`(hHQ(4JFH-P02?rn+EW{f>=IB1a zi&;Ki`vaZ03sGP2QW-|%@Ge<8UQuKp*4wx;6L>Ao9#noj)fs;Y?~=2`Y=zZRmEH2& zG`v}_i`BhXKI;Q6=vf2a_?_0e(Kjj$g3gOsA>KhTUQ?j+Vn7tH>m+M-LVitrKQHEp zeTjHCMVoVBn~O(4RWU1#H*h%95b$D93h$SKNNwxCnKc0~M(KEew6DUwb+E_ZJ#heH z!9u(R_dXm2yqM+Vo!Ij%*L3!yqtJOVB8PXGLwRPds&9Ma%1q#`S&3Cy&e%2!0M0$i zSnBbOT=5c;1BERp|OXmVpbaO^;r>p0WSun@LEhgq_y!|+XnDrl#chvs9M~J-5x9D z_Ne|iNr*S&VRw928BWf}yVS{v3;%uB6!2n14)6L>c8bW~CZ&ukGlBQW_eAB6{blec z-rNdTO6&11zf3vijnJ5Cs+PNnZ&IRX4S2JPEOdddY;FTy%nI>NO{~2K@M1s|@8^db zm`)@2<85=8lf-)?y&T8HzncbC#jG@5|A&8u0A37A;VqbPRGWXUVLsr+C>`(Nem~e| z?-ywSFAhK~Scq3Q&FdRYQa@A@l7=^{v#I9#gCIP*qGt_wb?r=br4~fB2fUaS;{6zsx&ZKEKooDm z(O!&JmyO3Zm?QQjcHUpsAKBVvZJnU1n3cxcVermkz>7gCyeoPf(_Y#$YdPS>C>^hM zT^H8m=_WUd;0G9@25j4e#zb0A7s9;cedhhJuZlg&)qwA&4>) zc#|r6s~n;};}gIWz1El4<4vLA4fZkBEYn5fvyDk(X;}l_SE zECak4l)`({=d9NK%w9LZi%~k>GM2~L;#c4CI0*+J7A)+%8!TtH0=$^z;~moD4cERz zwHEMVL=JDSTA$r^PqcV!T$u^HOM_yRPE8yUul=Nv74>-YXm}&Onrb#ST2lvH(6a`- zt3Uoq_`3PwSip-}AztsfBijI842a^b_1>8&e}uz3j~4n07AV$v+q6ky%Y{#B3{}Of zG~V6U85j-nw;fvd=!U_?syXK*j4hs9^=bi&;M2yT7}r zd<#aG1H2fK!)vceQ*5{uiEq`yA&4>)cpJLcRhczzI{^T0I-X&#$GiRt<%BJInyJR$ zcf){x$Qtk##(Ykg5jt}%;Kg}`csJcKjRCwE5XC#zZ4Oh%Hs+|@MvCE$7-GV8+;{#m z;KezKs`5JT+U`pqKH%jR4*UZR*0924gCvvF(8V!N!AgjX}^2DDUJ8i5Lf)_I|iljIuGBkow7HnEOcIs((z`-__H(mUk^5J!9u(x?WSh|UYwkd zH+1e|&cwXl1;C3DIlSXia}}=Pjc)*69D*n_fpfaDLFU~8(Th=Fn1H2dz#TzoWD%(7@<4?Jb6vKNXyezl8 z%vXFfI?hQ{mDhP!z6pB_ofm^rczX;C)^=yx;CmY|O2^y0=PUL@?x^F&Em(-xw#w4? zfEOp{*ksyddchxhYhL=LZZX)mTg`O*jQ;t)ic3A~j<->FJ$bJoLBU)2Hp~j~wrKTk1K`DgDBe!fA2Vug7CtJ1IpPoy zPuL==*>K&fyjTEL#Vk=(9^SJa4_yH-2Bq-UwhGeT`5UweIxj})cn3B#=N81Cs3^Bb z^?$8Gytm!5@l#efIUlcP;}d1GrM45G^I}8}Z+yiv%=)Z{_$ezKf+#bA_hsjEDwqDz z`0Hsx;RGi=-eMYF`+FtoyVr*eYfi&-Jw8ndSi1H2dz#e26! zdv>_TaZ|aC6zjZudYN+5&X>kV-*HZ&syw`9J`P+7crhr2Hz9kKwtc@3IJv z_{b&<{ZL@sf`xehJ3M$LbY7gCkJq!gyK3_H(|rIhM&$4|YP?=iZ+Id;q>V!mWhU@G zGPQ8G95tpYEH&_=V_iMoZC5ELZ1G_xnqfZPGyfrLz*`tolHfErdI;dfd4+iIziI9b zcrhS~xBU5L%xu%UedRV%46j?v3pTZD@3PQ&aZaMDJiIO1mf(#!7?i@BZMj!_&$G}M z@M4sX*TJ^~H+;gn_Qow(i1+olR42fTlk@S8_aChsXcpoLcrhY}_eT|1Me&S_4-R?G_VUY%Ej zkG^9-6z};i`NeEleL%w-ecDtrr#tVMm!37?oyFuQG^!ih0y-~dg?N*L ztE_^~ivdx*nO`Qc+rM@?Ah$p-y zIVkgOjxyE>))T8MUE_%G5Xn2o>n`#EXD#7c#^sE7|-?}pti%$!m)rCqjbE>-)cs;tcR_#sl*a3KBa|buo;|8Tv-mUIy zm7^=qm;!h)B8T_A!%>A--<=%b#UY3?6L`<452>EM%)=j`wBMau=5J)85jUW-f1+0;%6_l#Sxu=D!PPn-&PadJN1 zZS`BKcFui{Uwy}j9Nrf<)QWiIMtRDEylu9!`|O-rN^tK;(cST zS(p$t>>siQyiS&%6Z|ut6hY_3d4+h_Z75m{crhS~x8;*SCUmC;FMDE+Xhi=5Xm|j# z{1kJp-ICQhs48ZOs`BtI*;y?O@M2I3Z)KhV6O;mulUso9+|pzt5E2E55h9};%t)vN}1ab6+b%?|CS0$vP=;{7vkC}YF?m0h4% z=Z#rq!Uc5u6aiJmIi>M-&8db@4`WaYZ<&L~we3@*c0uRGC>?LFT`O4E2CItX_KFnV zE{At*1iUyoA8*^-Gi6FRPNbF z@z&+9EfpR0c(+`moUqyFT4)ZQZ;rQs(6a`-_RU`>EOdX@9PnaRh_~j&ulE2i21N0) zeKMG&p8dbTzQi1{FY&M;&ex6`fAjiCs48Zq@m{eSl?`|?D1~>%_I=uWSF>(I=fx-; zZ~g!k*JgxKh}Wvm#4UgqC+FjJUcX+MRVnQc;Khg>-VHljGWBK#-!iVu1YZ9t znX1+{v+<;Bhq9bPk2j8nH`vxv)5mQQ9!}D;2E3kGuM#{*H?#-5m=)qZb?XW~fQbQ7 zyj`3VnJMjmoQHjhIZ3=J*Q~kpLF;NjRWU1#cSK?D9)K5vQg~08@6+~rmi-9uVw8@z zf1_9I$#Rifj9ah}@7U{e>i}MyoR8O~(gg0&KJ)c}7b9|bGn+PGo>vaYG_K49-d66V zRDZ7);w9}a)t|6>yh${?!+)4-N}mt73T2{a4R}pVo+lh#8&d#yF)PG7>_nP5bY2XI z;!Qv7&semx!6zv&Cy94(u{HPXPGM=NDrTkeZrb(N7Vu(F3h(9qG1}7o!Yu(WM(KF3 zZ8qa{i)P`I6gU8}U?JXB&+B~zyqM+VZBqRb=N>jX8}MR84sV+OB}HbzsmaEbnZSFa z!$oC&(=(j`V5rjyl^$;n4R7HSGmZ1@3N`;BYrtC=la+AiY_p?)7v~k?-QlpKKH$ZG zDBfCIs3EaIr?TZ;Gfv6v6{!=p*I&2bi}rAGKHk8n`>LF2Yw_E|7?H!9H@*vV^+DbezNVd;aLu7DS_ zLcHs&vQq&s21N0i=cO`dHlN0CQeaLJ@7Dol-2UgKXFydkOH`G2!nU~1&#izLgHm`+ zYDZ{mmdY3jcri-H`&v_u)2xqbB)3M&jKhD^Jofjf?<^N{&EpQgoCK#s$y0e@BX+J_z^)2O5trk zK3eOv@mV>*i%~jW->F$_c)c4_IDN@f8(zW)-^X@m`|gwLfXD$#voIL!tDn0dKH-X2Qbmjqrmi zm=)q((Co@az>5JTKkN)yo0i73vQg{`O z4{HysuTcx|Vw8^8Zq|42d{Fd~Py z{E-HVeNJr-7*}QjZ>`z6O1m&_D*T-WK2Gee$NPka*QK0=X7ZXYc(O;&8t}Rdf1Qw= zS=SmmFJ^^!WBXM74R|piiZ`U#n>oF>BEInxbHu*HW8OBW^4Xm&Hsa62n3cw>oay5N zcrhr2cU}8XZS29$`vEUT>3FT(+_=pyEAUbo4nQneh_`PgCKm8wmX9~HU~i$N*8O#=67j~^V5H|AiJj@QAu6}Q(j8IO~204m)f>}*K>{{ z81UkpL{)isPmW*y7CJ8mrSK{ahid0!K70$E7o&8%_A#&6O{$a|#w}RbdA}{{vJCLz zsgen0q^kO_X%%Ptabrj%nI@Lsq1zY@M1s|uT!~ROi-CQ4Pb$oBN`EQ zUgxe~*-m5UXFydkD~)$&&rP|27lTrGU%y_XE&c2E1Hg+>I^I^hJ-Cy9Q;!+9U?JYe z+r!QPUYwkdcl+@Wu3hVq4*@Sm{$!y!9C4%1q!L(2Z4DjW58Hu0|Oz2I%qL zrs0k5^Gm(Myh|@A6FqCdJB!In;F8@h0A9=r@y2bKdT zU!($FoScvM$*>S^{k3<_fEOcjc>7h@sHl1NdI6Mq?MKoeQDy?~J+JPnF*O@@fu;U* z3LC7)`-X`N^34_O0V6O-=={=Yc= z-!UiIdE4jdA&;+w_suC-BsjW4e;XRe7x6p<*+AXoEigOjL6}2zxh*9Z)x-9 z#+8}CTXH(2Vacb!M-@kY|{MwtFkAAaA(0KO693KosxN$_tpNQ;k>2ZKT*?LyD@14ejHARmC}_@pf4EeH`G$pcLMb*(S;{?FGlHjYoDpe^-{+VHEzK|ydA?f&YiedF=kEC zGQf*N5M?ItZtwg~Ic<;2c3A4)ig!lq@y65e4*yZ04jbZO@()=9Uh6^m38mcHT!hYx z^9u1=tsYnmcrhS~mz~Zq%g-*wZ*^f#vhybQxX(Uc*}N)L6|+QDd7XFjux48TF9xOX zh6N4PK6EJa9Pnb4j`v1OD>nC0WO-WkgkXl^|Kycm(g zYpOox7SuG`49YyV9%+y$GlBQo$SJCV22=2LPw!sz7^laZLc{ABl&f}m61oTQ(z6D< z$vp}aP7PU~2zW6o#5?|N&u4%a1EP5EJRQYwo!{-2+eop_>mK!$)wKU(169R2iK_DO zx^}xY4De!53h#C=U+vf1FIod$jMDMWw%x~8WWVDb+Bg6e??g+@PQZ&hc2Si(kZYxs4RV>yz=CUF2J^7x3bo zL{)is^B!(G3V1Ong}3_95!y)s4Hp4kjMDM;I#r(Yot|%F+=7Lj*Nl7l2JqtKe7x@t z^i(xz7*YoCVnhyaJ=&#e`1(T3O5<(hc4;o)#h?`4H$9eX2RAuZ8t`J2j<-{j7i?n9W2Iq_;sC^g zg?Rf6XoQcxW0sHC_GxFXorhH*;Khg>-g8z%742?nRe%?VAj(YO&B;Ea%4_lXH7s>m z-w{*wcw=aIvo3s6&vJUb^B=MXyw>3sy4Hic;Eg#ruMlrPRlnVU7XzYr_e>9DPJGK% z$Ze!p=j{_<%}q#G-hry(oJ3W5o%hY^eR}~f2Bq-!f4^26ee()FNr6#1-kAaO*^zd= z@KaVe02Obuin>?Oc`?h!`{UXm<)Gai@x$2|k;Cg^T8jBvz55sA%1q$>eZWF>_D4A0 zbanQ=osS;xbsFCEvbpNO`enX>3wqXoS9hkA?sv(|j?j5AE5tk4ZXO;sU_caab~9I| z-&J;?+(wGw?OO3Zdw=YW-%wSYQyT9I!D8H~@GtE5z%N-6aP)F9t;MR<_#6 zT-7+8l-o!#yz9Q0aFr8X@zabrr!?NE4F4y97lTrGZ#G(?UE~~tH=|>ej(6(ej@*i@ z2jh%eun=zmXXOZZadJN12Q3{rzg~)VfEOcjc)jv>C?4L>^#{B-1W{%J@A>WjDOZ%t z#7B9yeKeh;$6HLp`>E?^b!o>+E>I?V)_^y8y@jrRUhrzbi&-IFlY;U1ic<`T;x*@X zGmo13)R)^xF}x;PGj7%O^5vnbI44n6-eJSGanphTF9xOXKJyLI_FTyvgwBgmI^Mul zJK4Ya``a3~U?JY5GlK&FFHX+KYjW91Iq2G+7l0Qda(I^yeWmcPGWor6WhU^ROk1Iv z@T*i1EY)-Tnt6J>+ip@$*gUuAs@*#r9sUnl1Kwi+7P_RLGhPB-oL7iTK&kh{m40tgpg?G7ajCM!C)nR}a zqjbExGtM#b@8{ub{c!+d!9u*ZJI~7jyqM+VE%J!uR#@#?2zW6fhc|ee8T0a8DST8A zhak#K;AQ)|x*z&4_9+1D{d2Id9`9)y-eZG4t1Ik|cl(E|0k6GJS>2|GuklhD&MU-w zHvjNtz>5JnN@SZ3$gs7?% z-fIIcX=~5w-v#hul#X}W4iDDFxg0)~hyxG{7UDg;b}4?!3bTB?_mVEC^3|Kx0A7s9 z;q6-Gwqos%utrd39D*n_fp?wvF4f$9XHx*+noVu}^mrf8@cLc)q%Np@5ubmfXAO8i zJuIucl=~L1HegnWHz;QB7r=`FQM}K*+p>4tEXJP!F-Po6#QQb18fSH{`EIBxW{Ilu z@D^-aUjgu9Pzvw+SzEPL+gJDucri-H>pQXoTQqUvLb*MvKTZ_nsQI2`rnCGc$ zwOQ@}Wuj*dc$q|7-HJ1j_=;1^3i0|{j|l?27!bw#u+9qR&aAtv+(wGw{W`#e^K9@s z8mfwOO5<(Rw!b6b#h?`4DJ|o)2OCy83wSX~$Gb14Dref=XM}MJ7UG?DInD#{;^ch1 zJ#Uv*&Tr(M0eCSYhj(kKP{pE|b@8wPhak#K;QiItMm73bgNCrw@R`?F>hVU?@Or1^ zsb7>z#$R6PSp(ib&B*2SVqN=>ZhGv_7CjnjzO5uHd)K%;JVL=_hi%~k>&J#bg5s8W|a(h(ju%T1a z6gR+&lk@TRda#R|ou{+{ycm(gJMH*L#jOXuR~lDl0&m%xtyCc<5gJ(P@PTty>+x!7 zcwNeUS1Vn|W9Ox34S02DD(K3Yt~vyGF)PH|vDs~V=)4#Z#k*obdFI-hE7@`j6zjY` z8AsV0bK+}3RdG&fyox?H_#_1erSK+xj?m8kc)J(i#V8$b+rsy3=6Q#v#w}Rbc|&^4 z>IQgmaz5U~Bp20OSM5x|ixD}ze`Z=LHl?qAYh0O0yc27xPMkZBH`hegYZ<7=`<#Y1 zxO%?&XSr%|P$qiTfY-jcovugK0B699Ss~uWZTk-eyciJ0+o^7Urs9xm*W@-*3~$Z; z_t+J;9^&U)aZYKx#cf-}Lg&Sx6yBRxPia4teL5HLVw8?|i|<1=r)77%nF9wP{?!Qa zPH5C{65z!wA8%;=RAtDN<8FW#BXW4tn(kEe=+grqz{DYlG81^~53Q7gCy!}=8wBzmwS&Qg^Ify+Mz6%WcXDTl%ms>Q5!j@kE}UHQ)_4tEjX3+zDT_hgl)sFq?At^DqWP z@wzm=$V>`S;`s~aB=Ne%l;U~}?1?`QW0t5Y4{yrc>j{7tgHm{#G)d6jZ|~k5@M2U3 zZ#fUv=8)rbxjia%%sbh4st@4B$@zHgCg*U=vsdE@8%E^tzOb-iIt5=!gTn?Kf+#bA z*T%`zz0drF4Y1Vey?+Ml@y5~cuKu2@-ecD==^wHNyiTht>J}caod%s3=M~~zV_A7R zbY2XI;tlB0mYLf~i4W;vP7?1g>o076+StxeRm>7q<>CG7c)Tm%#h?`4gO1a+uiqSa z1$Z$^$9uLG9B~|9 zw1-0wWhU@;t+GQke7GAv4WU`!y-ANZiH6rZH&-2-ZQlvXM9&)Vu5MCQ_n-lXAI`?C z5O39i)|CJ+21M~L7~7p$p7XYy+(wEW^ESPb#(s@F-~o7XPNJ$jylX3Mw+6fzl)}4G z9jM)3)hZV7Vw8^8*43SB+^FjV;}$GDY`EI{Xc@qZlk@Qo_WZ#<9Z(+c=f#K|-hCIM z6pOb!jyJB%1m2=MiOSzsen-Pny%HL2)#J^f;dOD$RiFJ)7Y`@tSp(j}7)RX+izO$a z^I}$rSL@@m3GiY-9PiF_W_0m@R&omz!yDsa!lg7BizjS2r!?ODT{{*5UJOd%E&nxC zyRO~i5r7w?bi9+^m~l4)j;}Rt!9u*D_3C^9yf`@@Z_W-A)sOW{FG1(Uh#cP6%^Nav zXSjX`yf_3=W&&??t+}d3%~s;er4_BegzNG8-=Q7zUi_f`<34RBl!=}-;Ptbwt1JDd z^;y7+Ss~tOF-uwiUJQuh9To1yggLygF1L|lc=y=;$JTxujUN%jIf<(BI&TfvJ7oYb z2Bq*8#ztwU1?7(hycnh9ZQAuIn;+z!Z`^`~c+)CO4g|b7IUn!XEga}Lcu(%CH5VfEcz4tA4qx_O-7q9H5XwZ)8t`Tn z)z|s{ZaW|FVpfPZmf4pHcrhS~_te00?5B|60J)76!&_yP1@~ugt$|QgoRg?34{wrL zxmSP}gHm{-(za`p_9}h?UX0T5{_)t%#s-eT-%N1;;vip$_xkGjbpbDC`FP{kL?~aj zEa?n*F(QYz<*6}DBRda#KQ9hJl$pTmc{fLuI{WMl*te&=xF|i|OEkO@=d;y={)W8$ zhpYjw?o2b?-^*pw0WZ!g#QQlk@(;K=D95rr;KiU6-iyQLYe!Vy+6wSul#X{-a98eK&72717A(a3dV14sfEOp{<2~nl zUAZo9aWLS;h#cOc1!_h0`TOu0HXMQ|Gl6%0^I57s@!c-LQU{#4uuG5k2@S8#IY;fg zbye~|WDR(&(;MoRpDMlwcyV4K-hiIfj{;r{h~ll&Y$@Y6+4hy(MvCEewld)yW?$9P5TJI#F)NMNvFz=?fER;OcwZK8)P|olNdUYUrQ?mu3}h~bz8xU9NA-WLLcFit zF5xRqadJLhpMZQ-om0mL0bY#A;eGx1kfMM7H&f%vOyHfo#lihZPQguB>c&4s(R#cg ziIfwzHf=try}qoi@DEu7-Zpb;>pZX6lmfgsuMn@}ZKem{#egW@^d?HCiromc+(wFZ zUbmPuw(ZgCm7uCPr!?MYU5|PLUJOd%^|%8@C1`l+{ZWhU@08mUz6o3cL)mTGqA_(471 zBQ(4w%ipUl)9T`HIrOXnZ(*bAx&gk&@FRkl72?gv>-`w;Vn7t{&d^TGf<4#g%Pmk0 z?=S1iY~0*SVNg|^QyQ;F0|y=8#h?`4s&=cjS=VN)2D})hYjm)W z+yce$`efW=Km2mQw?yKc(s-{}Kf~+17?i?0c+WiT*%y;40$z;L@&5dCn|16t>x6L& z7UB(DSb%TL!O8h}9da5f+ojE44tOylhj;o%f5iyDUwBamhak#K;2paIE z?2S`L^myOU@Y?@*uU>t@7H^59XAO8iRdCR`-f!jtcrh!)`!c3OW5A06QM@kwMldHg zMs$aLi8-PX;W2NOS7uy+U6~co5->|tm3PASH+IWu=)4$|!aGlKQ@hvxHhxeAqjbD2 zCp>0<9}mGBb8rA+!9u*ROhfU**_h?yjV@o7`&vBVIN-&I9A1ZEn-u5g@60x?%mm&w zZ&oUo{`8&*`_`*+qvLwK%kNT-dHqs8t4#wYsQw{qz&kv+ite>jfgj+-d4+fr-f@0_ z7XzYrP1l}fthe9BD@T|k_9fzNy3~TxHd%}ZW0;l3+r8;t3&4v(DZD{$7qxHfKd*t# zi%~k>%%b^h+^3%XYVX-F&cA{co*NuU{ew{Rfm>85j-qVNMu}k(mErdOa0}u-qcHWmie&VGv%<}Q>YvQW%`WjXm@M1&` z@8un96_+mfPB*U11m4CIOjPRc8}ZvQ=aPI+>+#0Z@OnI%u3^}IPi)) z;KiU6-uwy|wL60<;J1e{O2=Cq@SCmEVY(&Y#Q}%~3-RuVdaQsGHq7$zZm!#eOQ?Ot z0q|l(4sVR*DMhQRvDJ(#GlBP%Z?b4T_Vo(b2xWFyinHfjlL+8aP9q-tm4xG!0{jPF*Me4BOkc$UiD#OY7cyBEKp_*l9 zvl{SXL=JCn^PP&c3)b5JFAhPJnZWC%JgVBcY^6Ue)wAHrc|G1d8s7AaAJz3fw8Gat z(X$4;eknC{-Bz@Z2fUaS;@!0B)JedL0a3g)R@7u~<|squ7ASVL!MSTPd(-2;`A}7y zlc*~1u%XkW9=tc^Kvkvimc6%JJ3(_O1@PjWbiBH*u3U169p2=M0}y|$!p?gv^pO%e zFJ}38OSjGDer0di1$Z$chqp^tD00iPzvy3L=JC9b5}+3mFFhLm6^c%d*vY2^y!{>XIQ}eD_8V*V`zB2 z*L+YXP5O=}d-Ux8;l1yu+pL}%gLq+HA>N%wJ+2{M2#Dfs)5VTiJ?F|a+?S9e8WA2g zY^pzp-8y3)UVy{}O5^=+=pcOb9fMMM%~e&kD_6F<3Y{0DbiB1scjPRX<@nPP4nQne zh__secX*u_vwXZ853f|cI}y_p@j`v&@H*8?b-PeD+8y!25JZ^?yz>`rQN8tSUIP2} zV!-rkdc4==@FvW0!FyilS-`s_{MrP-i&-IFwy4)Oz>5J?7r0bb1V@vd+6kv;MB%rWS^7?H!@4O-UpWt1p{6TO5sf(7N?!8?K}n!8!$@8 z8(r-!`*ijGTgEL|*m=8;udxvD;^ch1W5cU(+0S;42D})N!@F{4k-{-ys*7=DCh?9f zQjVQ|46otm_Zxplk9S)#<%Dhc{jcgLH|y1cGSRaJyb;x^>H03)ngE>_vqHR`+I9O0 zofiY5cmuYSWlLiA_m|s9F}%s;9JrD~{}8Au&MA#|n%T)ufER;OczblvYM)Gdi@&g8 zl#ciClt^~M*tR~#Em(+m=+gg>vOAB9>3#nP9$AvLM3Su8iuP*IDi}`Tup_=f2Lf%RMt^F~=J) zadIx++Fe&F0>4bT2Y4|eh4)LZPI5=NYMg#$Ch%I0U!B`LYEJoE*R*(#(eUQH z`t9<**_y6p$m;MKDC=rGEqd$+yf`l(?=rJt!vQY_1o1AI>nOkbeFI*YgE``VQQY%x zw0_60t$e&+ zRjqK(i<5Klu4bjcfTNi5sUd;0GmNYps3-Dq<5O1jK8u`>V=J+cN z=0x#2waRDw{c5{FRWVCcm9uS78En`Ocrhr3*Q48Uwrl_RZh#k~biA*7nldjwI2r<8 z9DrCbAMgI#1HQnvq1`@G0~fDZrQu5UMzKBM#fTK%m!|){dwAL|YbY}gL6n)m+jXX& zs^8vr_(q?d&rNP?@qVV^Z7uujqMQ_nH!0AwI=uN4%r!qJU&JToV3v>9dgH|7fENRT zcy|x1D$foq`UmF{bHusC&KtKjopGu7btP04vqV)nc)O06+Ys<#Pz>+i7YXdHr?2q& zycnh9?HbQAx0?^Xr{9A4cz+Det_^r`axUIZ0UZ>r-`WKLUW`cL?bmy@?88v+1pUfP z;2rHSL3!fmM8uo_^T}N;-jz3Ld)~ximml^ute{NvtPbxw=Q^6z-NsIa&Wl+-US&1Q z9)K4Ef_O~^hRd%PUS1`2kV1Rj9IO?}xKHet@Rpo#eC+FhL@eES_S(Akim&S+`-t&Wx%Kp7p;oZYS z4WAMQi82#-J6`out?=Em7?zs6ecyd8-gp|`knJTdSxr4Alp(9bn-*iH$&;VNi_vjj zK3=&`a4o=#0YSWXZ1>9d?NH#m2QVkvc^6&GW$uLzp8@5kJ#)FE zE#SqV7~U;*YuMdK3lJ|x>3F?16*7It^tqtlg86tWe9gq4hjDT)UghmW%7y6%wg6s? zNa0;H>9TClxDY4(%1q#$RQgr9|6?`$J8g5~z!NRrr!>4XrG$P#dR-Ut)nY=9d8B`Us;&>Nl z{Kx>j7!<{ObR`>ja`9ob6KStvK#De*Fd$+0i3APQG<>Jlnv`v}R z>dZL6ixDZj``R1H0-Sw9^(!-hci5ecO6w}y@50~dq;V~tYw;G)@V35C;?gKB5r285 zXLWd^hSkzI_#CVScrnYz+s(PzTEL3|LA;Z%eU^W%)FfJJfkK_v_s2KpmExcbs)}=p z<88IZA`|dpPz-Nj@DX;6(g@%Bj!`<^uao{UC!(+7Un>qk#rq=55U(o3EEn(mBQ2B> z9-+SgFGi&BZu$ONX5B~KSidq8cwa9Yq-tYtkqGCuf7hayTD%drC?D87`j@!eAJq~s ziKJ(Bcnu7yYj!xMTm`(C<>Sqo{Q#esg8@Oj?z5)I<7>Qem0F+>-YAQ7=1A1$FHlvS zQyg!by?5~*HVlg4b!tADy%tm30y-~7>3A#ssiDX#Uk9J2fdf$S<}Q&tL+8aT7w?Wc zdzF`RhT(hIFd~I_z3EEX=RO;vq0CuI(jZZ00&ffDa#cXrQMcjTT2x8N)#6R2;dRI> za>@U+3Cl#!>hQMSQA1OAn(auyi&+7@p7(Y@=f!{^-lDUWAsk=kx#h@784mXCg&s(L`0K6Eb<2_PGrT7^)>W_X4=5HGuN7NVt zcyV$r-t24Dl$Rb=z5|^XBT{&G_NpU05i@>-eq|=`u6^mH@>+2LFGhE7(C@7l?{ym9 zb&rc&dSw@dLz(DV9o|M2YicHR+dmZWVwR8h$(WE9fENRTcptrvk~>WwhQEJfj%Y-< z=dC&EGxKB1V;`t0X2tPV|8da;@M2I5@A6F>*#UK{ZU(#W~>Fg7?Hy3=^yPhzMk85z>7l=WhU@8n%!PiSj));mTEfF z{gW1Na293HyRN)}x?^&kre(fV6!dvs>HD>ST)@D#uoRg?3XWOvwk3|UJ#h@78oKI6&|EjL5053-Ac-d)pm}Y&u zVN1aQsGT=$j{&{`6SG{rCkCb}*!y+yL3V_UR8!sI^Nge zF--1}FZiQ94nW1bB`-Gvwhfr&;@$6(t2n>vN+NV#j7Z^?&8{u;cM8VW-Qf^KnF+iN zwwkKuMCWyabKCg!_3v7|r)hYN-xa&qY;&JihO7>+pI;qK)66Tl=f!#Xctd{<9SV3c zAc%L=;tBG&fg_Ej4pIp3i7#iFbx&^g0lYXTQB@9Jo6>q!051l`@ZNj7l=Thmitk~= zC>`(ou0_nddWY=vTQGmyFgo)fz6}T`=i(joMWu*a*YFzP#fTJMmq~82NpBy!=~rd~ zue(RQ>QdN@$FS5k&35H!@jj&C&5tZ{*;TJ#SsAiAydDL0G|x87m;~DfoR^RHwCW{3 zbOZx}c*p-f!yLAaIU{wDLU^-PCz(tq!=_MGoKqaHJh$9Fz>7gKyp^i+<2TIh)HV20T^xYgdE$52%S2s1&2;wc@)ssAY}@ph=~tem`MUj*RAh!kGyVJ~H} z!Wm=qD>H$2X?8p3K@S-Gw!w4Po&qi2^|vV>*aCu!T$KLn&qA5#SsmVW=WA#dCx5`s zi&;KiPxBv}051jv@s_*tPJZN8VXo9c3gOLomCGDRGr_CMa87Z&!L<+Bw z!(Un37NgDqUL1lbGl6$))$1yok>i)bxlO9nu1JeFiH6s}?ypOwDs?xPA*;h1kX=(_ zJoM`*=)5>DAMdoF&?$fy1A=&`_OHtHEq~#p)Ikd2H3&M+jJ9)H1Xaa3iK=osZ}@n# zgMb%Ei?kW7^UO2OH7hmC-zOyZ^8V|o3rm=Ds*0)oQwBB#dC_EBhP$- z&WjN#yyXWZ$_)R-2IyC20`Jj*4^*|L*&T(Y9{TgPM2q(d4R4f1k&E$pr@dv!>hR87 zTvHQrL}U50H4Q|0`xitsU5TF)NOD zYGgtsz>7gKyz`Wy?4vQ44*_0`((!tIG*kFz_WCGwRm}^YNaSr(FlU zI5`(@?1Gz$SJAdbfEOcDc&|Bm%i~KA&DO8X1YV<4cU3VO{4rR}K zqhpCn;J^j;WytFAde=13q&im`0(fy=KHhU7a|Qxl3<%;K9Xw8+Sm8pp)Ikd2%{~{; zl)Djzk2u9S#qqA6=7CQ}$DkPAiA&tsN}tMo1-uxgnkGwF9rnh+Ioe^j~+aTzp!CWblZ^e z>KL=dy%~OogIS`goX-2E+ScRHc`+!4w_>LS?6ziB__!yG((z8qh+q;`okmEV6|rqY zar%exfEOp{;ypgOwW37U24CNb5h=WRUfX3w9R|7sUL1lbGlBP4!b@d8%TboF)T$jl zjI?;uXm~@q|8wcQbq78MjGoou4QX3TV>0hcedxTH<>Phi_A>?WVn7h@Z~IU=V>dcp zYJozX_hW24Q)~8hIaC$rB&y26Tj52U62OZ=F}$INRII8f$rw5>M(KD@oUu|Ak7ugu zw_twfy=Pju4e;XRT)ZCp+?8!!RWU1$*G=&opWA>zF}zORli4(r<@m%LjMDLbG_I`Je{9bt z{T9r}d&jRd4e;XRT)ftuS|~!dG{LXRFd~Jw!c8QB_Xo9lNyP0d!sris3bSw23{vATJF%FGlHj4PK|q z_cb}#UFxieZ5xg)df*9oadIx+#-oNSY)TtkhR%x-DZE~dw#u4o%tz~2W&-cW?roi& znW~jxsS8@V*3#k)zf1YRX3)6Q(hZ6mZm*{TUW`cLo#w>IcUJt4cMszbM41V^ zhqlJ6dIopK|N0$$Yt+`_-Alup<6q*kAboc+;H77EcwKXAdbaC3OHV2F37p8nl8{Tg6%d zUX0T5{>iDW@VoDaSC!!aRJ`6JzApm2nC0RP4IinP(Rq4#z>5(nyxaOul25s+NYt;) z1l}=otyR6px4`GnMTdsf(c-;8!<(-xaasL0Z8x}}XLWevzgN>lcD~aJIxlAVcwd?| zoCe(tz@Ql3&dEdBN#%MT z1H2fe<9+Eljj8^z2i~-Y15oicf7}2;%kZ*-d_6-{6)~2PuTNmuWQPcz9V9v;>@!s4A!Pvg3b`fX<6SF}!B; zyx65F?WY4?jMDKw-Sv@Ka(>Tf{T9sMHZ)i=E)4ME;%=j>Yrofjigc>DXx zWQQ78Kc-)q3A|M`PnBO@W;TMQwjU5%UyHYxhWEzU0+;Z(Pl%VE)!{WZudQ)iunhOS znC0X3SU&~t9>#zm-iqb-$vdP^*(0?;A-uT46Os57XyNLyGOo|m!>quADl2p{4e_dyQl8jhW;z|GrhWh#Jh(vOH`H9 zd4nQrmxs=aK{33_bW_%`-~v8q52JLvG5tC#8l|ntkvc2dzg9lpOOw9L0lYXl7w>|R zhm?1_jM)sG7b8-5WN2gjkS1>(eUQK zFLo(xYVfuUSsmWiPpfK7rYz_IcyV4n-lvIAe*#_%2;v=YpCu3ez~aw}Qijb)fTNl#Vy3T~$TsmsjpmXGIL}1H0ol z0WVI@#XDgYqe|!(bP(`jL<+Cdy3eu+MjrS=6&!*nGl6&bAeriKmELV&sg_-DHr3+I zqTzMOD{vV&GXQ^`qi1z^XUdH=aX-iX0=$^z zdzYVOYE(VU0$!Yxs4537n^(OjJ1o8OQs}%GrQ@B!{$?f`IPB1G z!F;^?c1_t1cyV$rUS-Qc$|ASFUjZ*hr0`a`I!@Nkr@jG{dH6)qAW>!l@56|lDoc;< z{b8vIYmTRe%=*f_OU* zxhda}R)9YPVvcA;xaW;qyOxQl+NdW~6|+QDIh}XO<8vLL^I}j8@6bn8*h$02mI7Xk z((zh;@2se9Xc#MXR>ZaqPX{kp33zdGF5df!FlBaj9=>}RBT{(Zysj<3@~NYPeq|=` z=3Tj_DoG8%|5dMToX|##H=c$!-r$dm-GNr~p-l9w4sZVZDw^xcHKPG9X8Cx(8iwJX z7XyNL4{og_FKQ>p{~j<{om6^bM zB`;d_)n(@$Sn3Mz&bC^-EDdjd*8-QqUe-U#kk#RB-Jpsl{p_=CfEVZG<8^xY<}`F( z3<%;4tFcsGqsH9|QU@utZK(U=E;Gz_`eLXm&MA)f{;}Ch0WSu{@Rp3*&D#3iF$269 zrQ@Al`x?{WWp+3H7R=u^lus#)1iUyo7w_mZZI!($^4KUiwFF_rAJc%Rbnnq4Y%@s#z&S6R`sI=qKgRM1p^J`o?Zhgm+};LZl$ z051jv@iwfuTmEyvts7Dc6vCT*ZWmKNrGf=i73UPkyYA-vYJeAmVt8v^3T8Kkr zy|!tevb?3q6t=CD5H{w3!1DhFB>hiQ>e1|e*b$Ihz8EPv03^oM3I4>V>@ZSu4 ztUm?>@pf$+Ag@|-CqwEWh49YFN@dnpJfwuG;+*1myAQ69Z+*w07+$l58(H_|_3;B6 zM(KF>*LeBgJDT%d^;<9>@4zYB@v;6mIT!EB6n7@HmyI*v#fTJMH_Jn^i$_k6*RRY3 z-p0&YrN*Fsb69Fyhdo`ic#~;(TU-BgNvU4fxC~hx-UquYXwr{O#b=e_ynMXN$5>Q^ z&Wiy-ypz{h$s_-)#1G$?6aBzeb5b#sNzi#QD2BJ0y$$Qzv8n@f zUX0T5R*RM^P9?WUmO3lizg9lpKb03)LFdKExp?6LrOyE@|IjZWMS~>uh+I^0PqZaRV8eW6>25O(+B7AN$J*&g(kyc)F%s2A|bY9Hz z@!me&r#j%pfFR!Pwo91>4hsC*6LX??hc5cUocLU|F5ty1QB}@YW!q|7wgS8u6vMkS zvMcM{c^=}$C>^h5RS(7S5y$X%PaJ?)Fdy%js~s4?i&-vS^?OgHcYan3;5{8e0+Pa; zmcB>c({WrXlo^L0%1q!LGU%^z@_^Gl0q>TSCUPy__cXlnum9m)`LJslvO2up{fsqN zU%Wj7cyV4n-lqk3LI5uY1o4_)w3qLHJGhn9K?-dfHpZti-y3(X0#(I1iK=q&nraqw z0lXL#!#i(tD4Y9a*f{9C7^UM~bbk}ml?}p2e&YaCyruH+&43rPT)bh6U6r@C8{osG zF(QRGd{skP#pWSx^eZ!gx9|HO%E=Z>FT%O?8j`Ef;thU4+4BZmDW~2y=VD$NvO2ss z!mDXU*Dgo|yf`l(uggl41%MX=f_OUxw30uV^RSB4K?>nrbTNhT@L4$&s)}=p$$eF!h3thBK;Q3@4R`JeOm!uoScid;KnXxr2)-8}k_OVo(fk=Dq1`)X6t1VcURFI^MnapD=Ta$KWq)H~4YXV-3NZ~Dgv(BmQ>G~h_D>H$&-A$SD*!IaE;oQc5tkGMG z_ZJOs)Q9rw)bdIA3mZMF!@I70Jx%_e(tpr-G0Vq$vFc}h#3=>@@s2Z|BCj}k1YV4e zIpSR6wxRNz6y{#$qIOVK%!=bZb9&Nzz>7gKyqhnrVf~_CzW}@#rQ_|J+L=jZEniEW zQL$~q?+#V)t1_INi?@NJv7+t$W4i$_Mx^j|^BN(mGiTH?{mM+>-Ll?Bm7zZM0G2xH z{GGm9yz3uQKCl@yFjV_3D7;jLtPZb7nz^RVz6y9J185j-j^N`%%2yA zzw}!$f7`G!om~st2ArIWx3*7?a`VP8yoU`VQg{QRtz|8aZmXnUnF+jMMe!=j^H#%P zsUsgQ?x)3@M8g|WxuW{Q)z^c|kk#Q0$gZnd+%2R9bY7g7kGI41oOgg11A=&W4}UFd zEB{eL>L7*iKIy!fdD^e-N~kK%DUSC@*F6IOF9yZ%{=4DB9_e+uHQ>c49q;~|JDJp5 z6@KftU_RafA4W9hOjfFw=~AHBSb3ab7;&>%POQ0$vOV z;=OeFnS9)!NXdf~!s~E!3-kTCBYstea}rhM?0G9Z@X-KX42t2s{G&6w?o~Rz4G5!j zybmj{VAA$5Bc;xY*tX%zIWN5R9Vh4FH4W4#(>!P3Z9o{2!rP@voa|m|#RBLNI0R8< z0&h9nG}VIdNk*{Lfs5x2(&Bwh!~39RMfJO5pFfl#tHWzH&0Mo8e$XSpi}UjFF6(&u z3gE?nAYSY0Rpd@~nJ=UcQV4IhY9@1Xw*mgbhI0~C<={PH)F}t>Vo(fkq2DleeVDro zbY6_o@kSiXU`7p1UZdZF`JLD9%(W2cyf`@*@5Y`Nl#O%EpF!uvh!oyQO9GwbN)0{+ z8HXUsOyJ#8ud-@K&jbHpsS|CiJ+*j)9#QtZW*HULZ%$NcSB9((uYo~*&60_YP(uyfVJN6$65J^WDSba+^yYQU@u7H{(?V6YhR78Cn9)NmP}Ccm0tKwE!;$#qjP< zo6N3D|L<}q1MR=)<;y=*!6+TC(qg^LZje7dkN^iDKB4mQnphbA1H72!;w^QGP^hnN zz>Co_B8B&sRdd;j9E&OXm6^ahW3R3Az2k>*+wi#M^=xd<>T%BA$2@-UJMB09WlL?{MXi)`celegxA?>9n;D$9=|HXImPiV ztIk>jUJQ!im7DZsz3!Rdd)P2a$2;nDHO0VV5qtGpFduK$)|C$cFHX+IJC(ViC~9(f zB6MDiNa3yAG0Mq&OeVgE4Tm7gOyE6J&swD!aoPr!TFzyWw-#?24e!k6mDS&Dp5phs z^sEl==K&U)`iwhn8!*eqd*;C148V&4LA-NEl$WPhZ;Y3|VUB1-_*L1H&OwZ^^CrCY z9kWDLIh{BA>{mJ9#h@78j?-+}CSF(YofH_Q<9*d&FY~tFH@v4C2Ot*A$2;}cv88|) zvs}E}E}T&Gt^A@F;Khg(UV{_Aoo*Hsu7S=wW)NwRC^La~<%`*>%3Eyl`h?)#Uq)#0 zX4CMdEi_cu|K>0O;M24Jhu5T@rp1U8{?K_b%f}m^*(Me6Vn7gY!pz32DZC-(<}$0_!$#>>W&$ts`mJ*0hh6whQrI=0 zQChs;X?Pvpl~;H8*VzinM9=E*8YmlUYF+z@H(+9xkJt9gXMezp0YSWPJS)jZj7;*B zI!K{ygP)%x({Ret0Z>((Qyg!0aKvQ5i$O8G^S9SyNA^qG4trjV((z96Gf?!n-EyCP z3+8v;w#UEXZ9q6V7w@L%DAl{6UGW|^j7Z_lxN_O)?KDleeq|=`w*DHbs#ktV3M{qR zrR!s~c*7r4KCnfpN?p9acDw-D<@agX|HEt0QZpk~;Q*Z%vwXZ8uix1TcrhS|cUk|9 z@(1hIOqV)HA-ugdu4k^*Jlh_sigSwNy%f2~3-Dr44DY$>Gg$Wo&-;KEqY`)rHCLp* zG{Glv-~hybHGI73Srzs}=fx}+@3)ot$||+u?m*|oh!oyoW87pD#@xj#PjLvM%mm(A zqa0OPs@?ci*^)=A{Iq!Y((t-k7^pvN+Zhcm=vf`!0JD}F|4a6D0WW6xctdQzm;hc3 z2;yxQzk)ehKjyB~K?>pZ^DD1V+uZO1yf`OORnE5I_NtgKfER;ec(450$Bw+7fIkmo zl#aL9qXl#1)NE`=H~s}#V8%` zf$eP+6JI{YUuAFrD&BE#B3A%j%yRL{qGOd_<03x;UW`cL_0|lQh4!woQNJ=1czfnI zQ`Ig#?*ix6VnMYjTD&i5c)bG+)Ek#nEiFS0$vP?;f?q6XKPw|Er)FbM(KF_ z&;P|ZPHNakzXkKR4ZqiHnFe@qaxUK51+$fT(Zi+zUW`cLbr~KiEBHMs67b>>M41V^ zHQ%06y>Z((29{d6?S^Suyu~!U9{)WVy5Jvyld+v%1_j{vqV)nc;BCKb^*K? z6vO*DeL7pN$&G%17o&8%L%UvOjvdTAuHSuqr)4W{GEMwRp2=cwJ8xx$I+&szI6P zSsmWA=MI{+*+Fyw60yi&-w- zkz1Q8TuVa}0WU_R@SZ(lD&ONe>9>AmCh%&eEK_yr_XHm(<6XTdK#OsvIVJ zL8qBeRm_UxjY_VN2-^k>is6mPjbYclxI6^#Vw8^e{pIG2mzU{h{T9r}+r+c*BjCl! zxp;5%c%g_h|GWb5VnhmW@z=+)(eE{(`jwf$JEzrp)sA-6w!>0Ky_~W{i#MK%cX*MD z%kqtgm!8$(^_Xv`Sry~>1n^>(kC!d6ItQH>1A=%%+Vy5!KDv&VTA)zp_4C`zJU)29 z5~_-GisMa4tcDMl#-JG9#eaITmp2c>i_tMk$7@itzthcMzwr@4H~{h2%E#;0t>Z($ zi&-w-E%)~-9eypZ19&kag}1)Vcc+25=6aTyz-zaApDL%o2Cq+WDtR2F#mmz0<~SF* zD0e3G0vGhG4sU$2o#yt7ZUulBvwXZ)te2DnyciI~8#=D7yt3>`jMPC2;l1cNi)oxa zvl#H=oZ@)L-nqFOIxhyr@Ls6bgKgc~r!sV2jMDM$^18`<3oG29--7vg^KYMQ19)+A zF5c=3swuM^o23I@j7Z_#;UDb8B>A1yugnDAArW#_=G(b{VX4FS4_>at`;>;)+q~H2 zNgvK-1N5v8Z^(i6njwmz&VU!Qe7sFZc{u`J3<%;)?vg4msPqmWAcHxg5#hGMYS3Qh z`;wz2P*u!|;~lf|B0gvjgJO8?4)kPaPamcMycnh9eV5Z&(Q-;le3}LhKrEP#*MDQ@ znSd9wT)d$VZY#cwOFaX4F(QR`-l3tgz|Q~hRaQ6zQDy?~t&&NqZflR!1iS}htwObU z3ut%`c^13ujoXPgVA8WXyvCk(n#iPH;{h*b`FO_+xiAFqVn7h@jEx)QrB;sEc`-+v zOT_EcDvvp8*1av@#Vk=(&bJNceN!@_^I}j8@6I=I?82;fcs(yh>3FyAYNqJidiNix zGphZshL1O@u(t!?#mTvN6}7r69%#bwg(?`4!fPI$C);RajJFEn5JZ^?ywB&gRQ+3< z=LJhGx8UPSE#8P{ln-piTT5I{jWG@>Lso}3>XEHx)TeM8z>D+p@qQiD@E+jBfFRyG z)qR*w<2OhyP-xq5Vk*lt|Gi}s;KezKs&eoSbsjzh@M2I5Z}Ups*^;ZbFGJ_WC>?M0 zbVJ2U*Z0_tZ~)@3m5Z%EV7qeWv0j1TP2Tj;;89FaUr10J!bxXFo`$JRx%1q$R zdvsfM;p~&<0C2<6b*r^_lcn$$UanZD3|YY2bp6KDfEVZGIhcU~?8|iL30`Ou$5bwH# z1X)053%tb{bHusCZG)fRa^`k_e>1>~S)!_(&b!ECJYI~BK{33`dktd^K3Bw-2x63u z*SYvOb0x6)UHEIo0f+_jJMXOaoA9{}nC0R<-_~B4b)hs0@M1&?Z>#B1PUqa3V2{8d zh%ys+7xzA`Z07zI?~*ZkvS+;(?|T~F83D}+S<38Af5PgwU_Rc5zlw&#wgD&S;#C~ARqb)#mjZY(B89if!YEl? zqi{Ru5jX@|+5hMx^i# z4qYuD{^|E!z>7l=WhU@;c#x%BUbWYJIJZq^)!w4T8%x96s8f0MlMAa6@9gEYtPXGf z-p-oVclHbeyqM+Vb;+M_6!2m|5br&QQs(oTJwdQQ%n|1jw+#+QW0(bsWkFC?%o0`Q z;B7bJL^r^TK{33y7yUWwTrI!?@M4sX_fI*6Vw#CpRs9ys@4P-;XU+q>I5`(@PWx2l zkR!WF053+Q@S5Z;k*_|HS_{g2CxmoFl$pT0CSk9tZSY3?&^0+QD^iR1G!1W5rlI?*FD?O{j+eq!8>DaF^z6}Voe7sD*jM0D>1A=&C_MMh@f0K&e=V4A1uXFTLreprR zzfe`o5>@5kZ83ND0lj_hplJ8W{mzjMDMiJo&`Tef|j_NQ?sz3+Cf}Q~gpc zz>8Tf-Xk8J6;I=Xo&#QtNa0<*ai^2Isl_q<%1q#my*x@a=+B(*@OL`vqTtF9rnhPAF%})HyR4e+I-HaW1j* zPJ8m3**W!3HK;0P#qq}Xw$BE<_E*WOisAM8dysuvxEp_@z$hK>>y3tr>RT`1{optN zv0y&ls+-H&t_HmHtPXG5h;Ewg{r2YoUd;0GHg6e+Pe#XpAl`|OR?C;A z+ZIY4q|l!CNoq5u#uxk3P*t3hs4A!PKHIYuUm}P>F}xklS+GA&J#mK4i%~jWw$Wqx z$+LO*h*KPZig#$;ff;}ovs}DPU@Fu6wJ$yyy_zivND6PAgrO(z#b3wod2tA$%mm&J zcdM$}nATVe=XPFr`&cdB^)DzN*d9zaR1fw^axOzwhu3vfH_hKqDaL>o=jG!yI@-?( zIxhwU@s4QtNUkxSutMq}h49*B9AhfnbZP>4aZaMD9K6GfhK_^Ii$O8GCYnQR{`wO9 zg$<*0yy1ar#rlX*ZS`9)zw>q-m)jBW;^bVsbM{S8Jblx$5_DdSNa6jy^|P$e&{%v7 zG7dqMnZVoPrGd&N;ek0Ub?>FWyR>+dr0@<%y7RLPS-@Mm7gKymhX|vMmGD&jQ}*7tSXEUd;0GCN8-*1@K}( z5O3@UWBJtCv+;>Jm=ne8)GD4?{bW%ZR28#CRXKQ#@4u@Fcrhr3*J^kSoBDcwBH+a+ z9j~{HW&C$$;|-WN0I^^`-h*rMHUeJEa`CphID+Z+aL94MixDZjm$s$L#x?zeFA>Bc zh%ys+Q(1FmhozZ#C&i6j+xKemzLvs!xNre>UV0Yrj+`*N4dBHr2d_a=ck?rT_)ZE8 z2;!|WGemA%|C!`L3T+#HY(C87E9TAQTui$O8GVZH&Z?Tqrv053-A zc(3lMps04yAMxSC>sM_%yRKQEqSh3`EX1#z>5(nyl*BN$-RS`(XV$(0MT+h&OBNL)nkeyBSgkDTKFqW<1mD&+nShd2vpnsvNx5lXFJ_UJQ!iwYZ(i zUhigV3wSX~$E)1s&Fml5wVZwn=6BwL2S0s${Zr0}lpTTeDH z_WE-D%1q!LcrryX;loW_>fTY|2eo*2Na0QR$Z&R7)GXkAk!Xew+QWJIc(7gK zyu}%b>^OB%A>hR*9dG2EWsKQ~RQ$~p2Ot*A$9p1hb9=yxSuWm7(|5{8CKcd2DKH|1 z*KKH;Y~|+ucx?j?L6n)m`{kRd(tg(jIh@-S{?(GTc++TjXKt>ccH1@GuMAloUW1@6 znk5gTH$&&edHHxpCJ(X#yciI~TWf)x{MOQKyQL0NsPoqKO zL)v!Iyvc~k1H72!r3b``*j0YSWXR`-?HZt^uw>L7*iT4mp0%CB34uc^T~#qru2 zHxCEA7!Cpw04m<`%^$7-yqM+UP02hauk&DI z6TpiRDZDC^U|ENL`)2`O9D*n_f%m%2TGgk-eg1H6mz`aFT#NTR4R6}AT59!qH+=Un zJ*&fOpmfk|i2n8+@M4ya_xGS$7XdE@1o6In`9*%>T+=GBz&E#e3lzdTZTMEkt%Jh> zs48ZOs&YE-{MG{;051l`@V?nFhuz(#o&(^;C>`&X%c;z#Iu#D+w_yIZp>@}*v49sR z=i=SJ-bUGXyL4SHDj9g-;0}i%n^+U_q;Vf z#xj=geilJhF)NPu`hcH7fER;ecw4DfvJHJZb_To{rQ`KTVVTPHOovOI742UuA8*M1 z#b*I8PR_-@4F8(O5->jii*D28`!)$#1Q%{S8lFGlHjceVV(e7<|K zi+&5{ciwT2ZhwW&i<5KlzG;0?VI3GX2=HP=3h!p88M5bfTjA?laR{Q!1m1wr!79h? zhw<^X#d9LgYVp3L;SKmzQynp+U=x&yp4H*a`P)qsd~$mN;KeK-Z(_~Gcn=!}1o1BM zRWqC9fp{kc=0rQMpWhKCsMXi=fETkwRXKQHEEuvA@M2I5ui{Y{Yx3gNT)>M_I^IQh zjxqM5>dlfmD`K7ZQ^LQ;fEOp{;w|?hSh;4?{0D#+BT{&WO?e}$8aWD|B-%8H{Ud;0GdS0D<96B!s1o5uE z8^sJssM%F&fkK_Pm+5L|)10>!fEVW^s>;Fpcg|9LVh#qy@GdPG!7k{R#{yoA((#UT zRVwAn35;KeK#@1?9{MR)rb_c82k(DB4;Oc6`w#G9 zKoIZU>2>8Ey}aH?9i$N66H{ZD>ORZ%LsfB3al9M$B-ugd#h@78Yqi#~J>J9?0bY#K z@m`pp&dh%NwUvGg=HvamXs#9D#mTvNhacae9Cf(V4mvMJr0{-esFBt1*;r1$G81^y zGTtf~pXg#(s)u35Wi8%gG`y|no2d;(vLhLzI=%lf{I1xXv;kHD*!J> z>3Dw~-OSX#;P6-KtcYzJu9z*J19)+AE?)bqlbG;tc42@QBT{&84Gfh{F>UGtcyS1# z%mm(7-M1-6w4Q-K{V)IC^{N(c77efbP91fhw19z7CVEzf*TJEiCazi|OX$3q<>3AA z+J?BBbJ_u33<%=w)cK)&KnFHi>L7(WZ_STcj8D*Hyf6pnB&y2UHpKnCj6YIfPz-P8 zuV{8*^}p=^FGlHj+io^f#IuX>DJwVt@z=`lyvdt>?*zP<<>Iw1e_Zi<{WCe>#fTK% zxaSV?lZE^6C4x8vQDy>fjjL|T$vsUf!nyUHc;dPi?`Im`Lzd?1n1ioE%aHv)yhl50 ziZ;@wQ&FMMXu=rDfUfB`|g>E}b`hbr6-mO4lwyuLrCGn3;cctTZiPNJ$D zyw~gPt_^rGD2BK3PdS^|&ZIfu#V8%`-2G>nq{Roa^;dV{UdgFw0Prbcs;tBt5e!qWtAbT z!|O5MQPb7?D_)F_^K$V1_kpd!t3`vM^I|{{@BL4!H$&-B?pqSH%xGxm;Q+*6E5Gw@sCK>y z;KeK#udVM=rqHN`7vRN+6kgSd*0KV}y4WLd2%^jcUiPX+=^S?z|4x7GS@A%N_bCmp zYefrndDjP{!3905!>K zp1GQ_kKBrQF-ugHvu*e}%)2Y##h@78(k*@1kJSqr0$z;L@!r3FhbjEj+gIwWh;`mM z0|zYxyf`@*@3h(PltlqwCIMcINa1aYY1i=E1`LYf9lywk^*O$CEa1f`9q+5-T@|S=zjo@k zV1DPlSLX{}+klgE@rFOHs|>1lVmjc(h!ox@&+f{8tS?#zW%jWm4H9K0@ZPPmM`h&~ zjoq{G*xaXDyb-S{AJ{yq)mQJb%*CIU=~*3KzZRV}iG@q?dS1+O@c#Ez*}?X;?f_m4 z2;%iT+?^S_b)_+!OU#LO-omh>%#~je_$n*R5>@5k%`f+5E_7ZDis9`OIgC9&@xdg( zi%~k>r1n)6rn5HSCLaeN7R<-{%OG+DbY9GI@fOy9qnuT|{TtxLh!kE=|6X$T@9H0b z7l$CqOyI4TcS+UBUX9OJiFa1N(Be&|;*GRWH~aK>BDkPub$CM#bkPJfY`+IOFJ?J- z|NFpZ|F$vic`+b}cm0vOvKk}G<1;ugN1RLCHvI1qr@relpFveIOH`GEcT27JxNX3o z7~Y%r{aAOlcYVN%Q99oEl1ygFrFrk9&WhN!;mi!#BfyK3bMcnudnn?R6Ndp_j7Z@% z{`A2qomMGeJs@X?k3>%OZ2P`ufx%< zntM(o@$O;F^6|zjZ5jfd7XyNLcRnkSr;I(0x4vUe6mM?ZY^LbaSx3N&S)!^OydRf* z^MTHbK{34NzVv4UG*?UkFGlHjBizq2xwijC0$v<|STMiyp1u2Q3E;&n7jKJ|LzNfP z=HPqSFd~Jw&m#l*vAOS)pv>3pNrOb03B1ns>8jbAYvLoDCaLeg*5Z9n!)xYPUtRDy z#T3d!&+707L^x?Ony2_c=fx}^Z!Z%A3&4v3LA}yO;X~l-%pCGgi#PZU zWzYLRyv-D@Zviho3wXzQ_G}AyG0Vq0tjF|pz>5Jvyy~#k@*Ngu@fSAC5$6)|4qddF zsl97Z0#p^V;&@9NPAvhv7!<=>A#*0%>R>)T86Bf^yasctGE2iJ#!H}R}FmxWuj+wc-Ng*YTArza6$S+H)*04J?rV7k|9ilkDBj$* z^BE)Szj&c3X2tPNf7|Ih;KiUA-syQW+5Yw&4@2k0C>?LoJ!giQcfYpOSrNnAVa*XQ zz>AY}@ea(bsaP7b@EPF6h!oz*1HELs+|P^vyf_3=W&*G4*hJ-rr)%wCsW&c;{;b7& znua&(cYSqN_qNx{kk#Qeo2Jl=^G!VhcyV4n-W8+lyrJ`AKoIY~ujQE@v7YWy2PyPb zS#rTw=3dSgd_FJENmP}yZCHAF#u>niK{34kfA_J6Ue)gicri-H8#J{xlR0n*{z!oX z5Pz-wZG-*A(JcWlX1RFVXEjhXDgW&S;Khg(Uf+SwWDh2sm5JvygSe4 z$$R`+-UskvjyRXNZJ0LvAYxUNaFB;xM|LUuo_CB6phO7?njlL?)$VJmtfEVZG82S`V9669D*n_fp`46 zhN{V}2AqJU4w^pwmlp5(x0DZTQB@kK7aZs_xeQqyUhj1(&90NhUjZ-9%g6g{^q#HI zc`+b}caplgeDjADcz-_TL_2TuUMrZ4+7q(@FJ_6VayswV*H!S6NDPYM^==x?Iv)s_ z0C+J<$2S3va=9nq#eg8*{=ZH!i(g#4B(*@H&YOMiEfdIi`vYE_lc*{OZ|j0ueW3GVPz-O| zHEY?iVQUOwI`i%a_f zUJMB09nk5NJSDI$KGq*|L?gmI?};y$n25YJXJ#aKS4o`}v2Pn%hK)}Iykp*w8n}4-uQ<+BT)gfB;Khg(-h<&?<&7Tu z;$_n~1W{%JZ`&d7l^v>F#VZE?oOxcP#rv9uxAo~p>c=B;jzF2{Ssh*jR;B59nE3{s z7qfi4isO^p0$vOV;=TG|gzR$dU~j2|6zaUm1y|%_a+|h*mVk2-RpoTveDxeT;KiUA z-j1DY*^u8ahXY=W((z6@^PSoLxd87h!~uxER(|JwdSyf);KeK#@8y1#6jyh+*aBXR zNZ~zn&)n%&?2CLT^YELbL88nAUXwo?mEjj3ZiaIko4K!4i#O;UWzYM$&{CbQ{A^f; ztPbyu>rR@Zb(-D=yf`l(@9Ezc4gg*Z2;%MaeIc`?YrtWtgA~GR!z^QBUY}4vRdG(D zsvNxjJ#2OZUJQ!i{qlVr`zOP5C*Z{>9q)w851AtkE8|-eaR4gbm|Eed054{_cpF{q z#RO0Djsd(Fk-}^BrIozxE$0FHm6^cXb8CH7wI{#vr~mr>N0nP%<&mmZ&<-iQ^RwO> zfD3vS@XiRScMR}imXFu#hIc67#eg8*gr?(|KDMv%)_2Si=MuLK4oB}Zfev3TLsc;= zj`vp7rI&yggJO8c?Ayd9*jvT{UX0T5zC7$8?`9ReRO+mVZ5w=oLNfs`PR_;K*J^-r znc8|P;Khg(-jgYI^5aT*L;cE3;GMtQ)Oq>3v%g`fjt^fOYVoGg@V0*4P`xy0T-`Ec zb$H{Gois7_AMuGfI4>XX9jml)fENRTc<0_3A%AMKD@f`fg*xxW2P~8ODPt&973UPk zYh7p448V&)F}&vj_p&?c%;*GoF-pf9{3DDRFz?23{T9sMHthV_0>3K5$+>uAU2PP{ zYtO@|%_XY4` zmZ&Oc+t6dXvLWEbpcvjRs}tGlJ4^84(io-VH83tr*F@f)CUsWCI`7N-xABE4I5`(@ zyva62t6i&yL+8ba6y7%uZnEDmUSH6!%mm&6C5&pzl-p`pYOk~RjI?;a)9^-BZ=@c7 zz8LSqpl5Y>bN+VHj7=-N33xHf$NQpA^KXC`1A=({6E4g5Hn5#3wLqcHo2@#<+^+w) z22>U26vvy|>D?E=i$O8Gx&6+uCugp03Y{0Dbi6ZqM=|F6cHk>NaRB14mEU>aRvD2G z+Xl>X@wW9}rAXVBFdpz?L<+C_skyT2SB~jfW&-a*lk>_3Rqb)#`fdNJs#?6^?k9q+FzzD$+= zyAq_%idg5Zz%IbYJ>leBys4v`D*~*h~4`Y;$ z*Zq7K#h!MR@daZz0P)w#@4PYh)akHoz$_PUFQczYLyMm#fEOcDcr(XUkp-T*jIVFS zA&4>)cu4oy1 zHYIH`bY6_o@%FIJV~hgt9@B5Ze7r}Nb$AbWadIwRd0?#a^fWUT@M1&??}XA9vXH&; zVNm8#vq*zPnF+kB`mIp)aI!;yD+hI{r^Orjf%1XPA)G0VaG->vV7uioP8TQMMr_sED1vL0uLr%N5A5MJLOu1u81t36Z|=On7i!8^5P z+vk86gJO7FpJ~A|ZfEg@Dj22XJ#w#xBG_;_zC;iQpmtvGWy`MvUd(dw`rP+WHh28B z81Q053a?F4gj2t;`}iN+=dq+gqRa$duHS z2f&MybMbzRGf+ltcdrY0F(QTcSxBf;xp6y2>Q`n0ujTAJs+sR>X24R%oxE?Q#hXRN zTVkc2njGL!hO7>+=67pNaYCz&fEVZG<8}Izd>`;)KoD=*tPtjdMT(`=K?-%=y~}4Y zo9}nu2UW#6#qrwwEHnYU7!<=Bf2H_ryTp6=xF?L#@hTeIDk__;!EFN$K>W4xw+)AK zP1gZl%yRK6&mC2mCKg=;ycm(f``5`$p4@)vODOZzOwu4xW&&@O6c1Ik2{Aq4+@2k| zqp=q6XDVKw2I_iVhi;c4tHT=*(OeTf>go)@i}UjFZpi!I2k>G*5bwO@6_}L!2cJqE zq!8ZKhZit=YpnNxs^XkPRXLq^te<){;KiUA-c>7|+3X&nrO&D;ok{j7Z_#G4rh~ZN$VX`jwf$JG3NEY3KbIZ}Ix+ zZredRB+mBdw+8jnPjJz>8Tv-Xj+GE&*N)2;zM_b{BKB zk?C5%i#g(4;MwIy?9xNOG81?+&ks|rXxIMwPjfBacpBdL{#NRww-$IC5Iw8IYrM6E=0r}UKj6hIA8)mPkNN^$3<%=&Z`g`? z=5~2HoJ-7!;;lUAGBecrCEiJaS#i8gdl}+O1TiRv*U@n;yZFzUA%GX7bi9uv-ZJw# zZz|Dm!F;^U3$Eb@Hk_P`cYtA2#m&Ak_$n)mNa5Yw{=RJ6FEhMJ8;2muOyF&k9Iono z*--;a4am1@rNztA@S6EIRBvv15W6-#tHYc2yoqLC^9lG18)o@<%YCrIcMoGg5byd` z^_Y%}jq6D*P-xqbG5Qmeo%YxPS^~~VRF$)BXgAI-6SfT)6vMmh@fP;ws1*wUFGlHj ztA&hVJp8}l5B@j+@z=`7JH%un{=$Y?F5c8B28zWyX5qCB7?Hy3^{AQLylyjmZUYWM zl$pTm)6h>ft>65caBkPSzi*?(`;>+^ZEi#Lv{xO6l_9Ic>*v=@b8&IlCFs03FCTC3 zJx)o`c`+b}*Yd0@v)#BHe$R_J;#}gkq4J!k%=inh(f}`JiK=q&K6h<03GiZ23~!Si zYuW!t*`3G56!m`quS7(JkZh%FEmX2ZGk0dvP$b!RNn|fdwk)B9qEtk7vPB6YTMbv) z${HeD_9Y}+vi+Xtnb&K6=X2M||DW@{=X>8BXJ+p5EpF&Sz>85~ysI(|Wp;mD{Kd`+ z-?t402Umx|wgHPX@mdz<%0|2U;lrgdB8K<+LK~_1m#|~nwVA*hIN++Bc3X~Lcm23> zro9?(g%Dony)BeRgSUo4n}o9(ypac5(~tU9wg9}CW#hf#d42}q#Q-PXjm}S~R+~Gv z5<5t)mG|?yc&hj2fg7Q#Sd$;`C7lH{;Kd*x-d4wIsk$GtbqBl{6~_C0hpTL#qkezw zCd^)Wn-s_b0WTJ3;!V@1`}4d4unyz=#;$*G4-fmtD;8b1@D))E@Ot37b-aYr@Y3?aNa5f;kKcAfFJ9O0}6Z>*jj9brD90pP_f8*dGt`q6+F z1Dtq0FK0^=YP;eGHq7yE8}==mO>GT7hR^54EYVd4-rKKF-UPfD8TXUXw+U)bVEb=D^B}5iz{}VX2aEX}`6w zM&J-cn+d#E8`n}y8ub7lMf^F!r?VPwz7SrI;TB52330gc3THKVlg-=HO=J7vofMd5 z;~mxJOk2Q<0ZzOpb#_Q=uiAna=3tIEm$>I`^yC=T@b;v=IE zhSxoOzvS)PdSTkNnZVoe?IwkExiP+PB<=XSu4=q*gz$bZvQRqZf1C(^Fyn7h4Y`ke_J4^+<7~sTPU9p?;GLzsPrkEqnCF0$;ER2dO3d)79VwN9o z9#&qAh~ahh_$TrHP})zsHWPS{9>1(Gcz%C90K9VUOm{Wjh*F_FZ+%N;(8UzIEh-As|DKz%(C$&`kZnBycpobJJD*dbaZN{hu8$U_Pn0)U8pm+qjy19u_iy> zsQfqu;Kd*x-jU1x=12qnMgv}q3gfL=UP1Z&`{k|OgxPp+J=%W;@M3W$-iuy|G96XR zHh>o+Vt9QI9+X&hoK{!6HWPR^q}5Y=Y0zO7Om)@XHBvR+?Sgm%n=8j!zHeWJtOl>m z!}hep-_c=!7wfX|daN+L1b8vPiTCY~Z4w7vrw(EV$%S{=0wd~bwhg`w2y61=RV{5< z2k>H$53k>nf}FWI)C0haQDMB_Gh515c36o&JK+F=D{t9Ly}N)HvrN1(m-ooabrNR) zUW|z0bxu9(YTJ3HDd5E+h&B^=Q;+UZ*gt5t2hOeMm0EH&-ZMgYNA+r<^onZ!u?krY z-gE1T3kMLyJ8V!ZBfyJUCf)-L z8pxllI)JZl#fTW*js<0sHA5Sv0A3t|XfuI#TlYJPE+2d2!Xz(R@219EB!oBlrG>J~ zmBqP$S2(M|YmsY9`~8e9gq0VwY`jM{Ew=-_7~sZRd{t`JxfNa#i8p-uOyN%9S3ILY{TPW3d zzY5_U^}MNaXOc;A6|x$qup6uQ9!*fzXcN&*tY8<;vnGWT|P4QMkCLA05`yRrP7 zVtBnkYnbZ6(6_zRc;h|@d|*qDZK7QHWfk71DxB5ez31PNZatt?JHU%sHr_VMMu!0} z1~~CX*^Q;_cbmG2O^|Eb;OyLws$cKpKIkgeB)ZDLyI|v&e87uAKD+_G4OMr8Lm~k$ zMuqWuHI1j*S63EkH(@qjWBdrFLxc=zX0%JL=11nslBcb-u|=JuFVAA zf_in_rd8xzg{d~ZoYq^7_n;8odlt=<3z~Pp3)zLU8oXhH9BG#YEs6mzX4!bh>)dq) zycpobE6+2gp8f9jPi%r*ct1CEp^S|Z@rgNDlOL~_*%%7&VvrB7^69ypka@fD+Xjq^ z;B8o6mRzG@x^@$0;~iMTx(x7QaVFlZ2QCWdDY<@t7b9YL7cc1|In`xBZ@`N~5N#&# zcKCQru~#$c%ihddRGa%-8w+%i9BdDCRfq0=QW{IvcR$lwergnfAgM4^frdz2V9?Zg( z7o);>Up1*Nd-NvohS*u*+crGdYx@lFVsR$kq%AFEh5E@;0WU_x@Gf$Qkql2R*#>xV z2%^md-u*A56z}`g$4i$x_J7t-jrWBZ-Y%;R44_TIS-`vP;+_eB7qe`&i?{ip2+HronXAxM%<|*y_uI!9@M4e;@8gURRk^3ta@g}? zR2XkWwyEs*o}{_jO_;rH__?<7Dd5H8OuSFGE~l#RY?lFeF(QUnVbxgD?U!vI?b=M> z{i$dmKYIFD2~2gyxm$zOcsC2-)k$ojjJ@wsQH87qud}lwP464w4S2CG8*kmBiU`1q z0ZzQjyO~HYxuxOL05Qjpw{SRBZMCx#bQQDwc;o&!d<480SHC!R9XfYpRgd;2mY+NO#fkt`2yyE*tL%-S2Y1 zivdo&-j{AkBlbLr5<5t)4{SaLq0|ujqj>i))+D;h*fv~h(c1y=VvrB-%YeQr!#|dN z053*`@y?htl4=?37Ovfd*(>jmqmuW47mG9To-w0k6BG&VfEOcTc*oayE4jGhup6uq zI0VsV0`I2qOA6Q@g?g75>ne7TTzHF*&!rZ;3c}l3u_n<~2HtsN`ZWW*805oi5oxR% zHDvdAz>85~ykC2iQ9lMgEYNPkY`pE>_Y4QTSe%L1^uTG^q`XpmCj~~t@Y?9;OFvyt zc@21R2%^md-lwah6fJMMzJ;mQJZ3jqjkin)FFm-P@~F=w$0}qsc%`cx=u?NcJOR8| zmyP%PR>K;A7XzGl-6FiC<_2!9#SW4SZ}Y+p)JL<5?a)=MNpzKg*Y>Y3UW|@GKD;NN zc2u1@zAXpvVpJG!X~lAC#J{CGwVN;-Z;OyhH^7Uucdvb&eb%}7CS3^d)~^Na{+)Ci!<>anw}z?tEhJc@M1&^ufb0v z$=a-fnSd9EAlgjeZJd{=80|T)BTO|{+G(5`?><4i^Xe*hcfNGG3Rw-_27%6Wx3(X* z!pe(v*?7BsbQ}tJF~EuU{NKh@qZcc$iyb7_${T$smhvd-eHprnHHoe=R^CM;XMF>_ z805qIcS$2vm)y&`fES~}cwac2pe6=OaFdS%5Pz-gmDk_$<~6{JStj103-siJY8I6O zUW|z0H5(f*=~}}8KNsT=M4Jh`30)p3l7{cYztbT;SH`RHUJ$~YyrZr%KBf6~a3P%4 z;EjCmL_au@&>8SzmW_8L?X?c@Vt^CxcITzkb7d3!+7olcx%?l%fM7rWS(AeT8@jez zNtJ!8{0ew6OLUci_wTQM?ExD{blaB)s6K3Om zTX*n2z>8TXUMt7evRmHAO#m-O#PDYHJs>%2`V!w;gF_H)Ch%S!zErVvdSMR$D3=FM zRO5XrgqJ>CSE(~e2VX8JoYmkh$akdU=Pcd=crnYy>%UX+5%6Mw6K_!WR#bY;$_-)@ z=67lV9w>y3_5nOr_=4|p*ujQ7-cJ=w&#m2I_~ zFdMJ=>4SJNIu>W*9kV}HzAZW!FU-M+7~aJ6c2di)%?@hUW&&^T)b@(q`6jzzsz=&e zPf_FjEreI6u%5CY-(pM^vj30Qt0SG-_e?tA#ky>~wF*gkPmOt)9*P~#zaK{UW^LkHGQrl zJ2Jkui*^%c8fNl`o&!w*FGj@hI(fNECN(*S+XfthXfuJ=qUU6V z+lbUVFjb43=0R$_nL>C6bTU%5zyIQR6|x$ysUEF=+XV1pR2c6i zo2^vBkML*OO_+^0@mJa^z>CG1cvEhf%6I=vJ_~p;B8E4`vXgW}&GGnw4Tm7wOyHfC zzEbh*NFd&ycqAisrW)@JA-to)>L?G_w7_RR2xm2TODa3kix>DV0KAxG=h*g;gs+Uc9&Tw;#+{PI75nh$K*&(2dV6Yk?9yD>|2m4SEA*R!1fF9!MWu65s} z@~qjO0=yU%#(V6Nj%;hgTd~?rn2q=D&PDeCFBWIw_3COXvr3De4R|pkhWEynO3C#$ z^-sYXfkO~&Ch$(IQ%y0ho!MZR>h==5S!%qcLU`#NwUqDvjh$D8tOjq2qYLf$>4!Do z#ky>~rPaD!1H2gE#QR3K4z<3;s+M90$+hzOevY7?UzpM#x{5W4t}^giMrStwycp!e z`(R#MRqWXAO#v@Ph4FUU-d;9qe=g(2+3Yi_o-iA4Mw{h`7mG9T*30-K^X_*z9q?jA z4DXD9P|4M-9$U0)Gl6%v?s`RH*XC(0<$>RQ*H$5`!CO+< zovtu_I|=Y&T{d3tHTj4a1DtrXV>?K5>vhCSA~DCi@(x=tit4y07O&^UEI-}`X8rK0 zG7R$JeSX?R^*HZAA>hTRFkY+HX0k)uuiz#h2OuWQ#@o*Fs5h*7UxlYpdSi2R7lX2Cv5s3Ek((&hvm5vuwO0rVPhtm0^Gr@8r-w(trs6n_?5>+BQ75 zlTkixr>z0JSd-`~18=`sYcc>Y2Kn%oM^@y_>b-Re;Kisg-c#+`%04d|k6)GH0K{J_ z8}Hc-$0h+@%rf!zu32C9{+hEV;Khg-Ub~cy61%m{gP_efHKgGMQXech4304sH42@ekd4R2xm2T!xCL->hRAPz>8TnUZW0=l(6z*fD>Mw(#tC%Ia%D`*b>cncmi$OlTx4*4ZIV#=p`Mekv#@l3+ zzRc&r%m!j-g>TRMedbvYz>CG1cw%DGi*Jcv0>qNzf z^0#==)#{+Ka5dfvF}!xs7mT4z!dbwZY`YaNiNq`$@8#(wKL9TVxbfaGq*m7~>?U@Q zTr01$^F(Uwjn*fjt5}mCZ%%M>_A^AKp#h`>1ZEnkT`^i&0^`HE(^C?z@#&PrC`T zSKj!^5AYW@EY8IHwc2`WM70{;fEOcTcwaciORkk9fe&mYdB)0%whe|sn}o9(ydHkt>Gsp7l)%c1SvKBxFOE3?UJP*J^|7BWZI>G2 zAa;;kcyot(Q28#a@ZG~$lOJ#3ka2$iF9!MW)*I}js%v=}S6++?;~n#96%`copC6cY z)c?Mw=PPUB0K|VaY`hs^&0S#S#VixAL7gKq)Apl(173`X;dKe!Bau@V-veG8f@m{= z_xRi$a;Ilc>cdp6Gkuq<@n#6&9d)3#@q7VYbFvBG#Vi}IW$!H` z051kO@g7^HqL#K;W-c~CF1*gp`c%=z_L2aQVvrAS#mZ_bZ@b2E zu<~M581Lgt(bVG~TP|ofVK&|^y`JNRIar*D*I{ObEFf(dzIzxWVtA{W*6%*+i7UQ1 z8;2m;OyHe1%uJzbb#*>WH7U5=N;TemA-n|*YAOv(58{J`gtHpF&LN%Y8}UP3054|Q zc*ovJ#TRE|fD^AWHh_8=Z&fHZK`y*L26HLd&l&XqFV-Zw%D@}(eQ`P9#ULNvpjj7l zq7&cXd)P24j8}h;LgpUr+FZK{v+@4;eEtWlyjYxxx7C9(`L2n|Kv;P(B8Jzle~e_< zo7*PP=3h%mgG8GNyupjEC;~^m$D2mHZMR0N@xBqlD?MLb`KqEdzV%%=tHDcu>qfsn znmiToVwR29bnOm&N+bq2@h-mBg?f5o`*%2(m?Qod#Sd&g25YFewK4c@17?Y?GVrD* znq>lB4D#W%^J}D%j`aToD=$Wc@t*4Zg$jF8f0A|+X5)2xdj2Zl#o|o7_4XW)pAC8U z3-Dq@3~!f`o061%%RK-u4nee;z&o`@oWda_FAb)8d40V#YP=C&1ophK-ulWWH_lci ztHImgV^=z$qnW_1iTm(#=9%RP1bgX1AdIg0f-5+@ixkMQ2=-`%fx%A z^K`|7iWq$82u8&4ZZ~T$&1s7gXycb=%tLEr><5guC6~>!vwuJKf>4{gB z;Q+*h*?2pd8YBQ-%rfy#$(f*7@!1)_D#M5vUN`wi$q)UHGqr0ofp?VRl%nR@KltvL z27k@htML{I;dS0r>7I1UJPTY1XEk`GSETgQ$)R5XFJ{?zcdTo$5Ab4u6R)$R7Im_8 z0^UrEIpSO*UXynRsGckLE`qLNmLG4*iqlO1F9!MWwwV;AdRP(L5Vj2%6~;SoNJm+} zCbDR;v!ed5hK-k+7mDwsz~W52^)HT*f3>ZFdtQu);az?5pk$5Tz2DlknZTQ`x-S3y zFC4#ZXzBEDgBtHwA-u`mD&2n#Zh?DV;j9KP-C03Tc)B$Jq5hcU~<`=I6unQ1%Ya@aOtL=3M*MO(>2m!0@SW|V?7NVJ*2 zE6?kp=-sswZtrW)8@ox3H}0#z2R3QyPxplSqwyhq!dVSo55J!Dsr+%>0WW6RcpsXy zc>s7Zz=`+yD?jO!T_56MA;KJSE^+16(OE~CwyL-bcri!r z5AQsqHY$aKCw^eVs4(8&r!A?-Ibrw2&I;eQ;aS{xAHa*nnRuVLbe2E(?cWseVnht@ zj?%xb=bF{QOCoUyqRj-}TU+WYQe{8zv#Im$soT|fFA3o-J@?an-RC6ST?uD3c;*rv*~|*jp{c4wCDuvcQoWsSBlxKSEcrCec*} z-t4r7xaY+nAKv+k`m4qa_QjuvF)EBV*`|PM(>M@sFTeqazgG6PVd%A;-2pFVnRw40 zpR1UY6ler^F(QU{m3NrLzHh3Zc5No`o~W}=F@J8}UO2aVdcN7M#vA@kV9)zsya_#$ zmsKGPcrThBE&#k(myP%H%aT`s7XzGlmsH;%trHrAucpTwaW4M{P;(F4g51rNN-n{7 zEMb-(?}c2qld$q)kPq)^*JY~p(NXx~Y>W!yt;lI4TVxecQ|zqpt-RSY@~i+a7H8tk z_Rgc)SS_9hcrhY|*JPNr#CNj8M!<_h5N#)hqQ_&ek+epNO&f5|>I-pxXIOK0jT zQzULDp-sYB4c>dZlyri9t>u6hvuwPIE(1;hUJP*J9Xqm@G<1Qqk=Q|Ut-L#o7gI}9 ztK*Bau_n<~#>#uT$B_Ae7lV9wqf)1MbPd<^aKMXMHr|aj?)U;;3~=IINUx=;>6Ax`O^^$3 zBi{p*?$9ClF&JwSU1i{Pv3J`EcrnO_x8gs~=dD+J+GfCuQDMB6!$YaRJ42>xH(@s3 z4!fNh?_mQCOuSvz$mL!p*YR;rc)VhGE8m}yY$*3$4l6GXLA05`>p5|NV#Grg{vK0Y zIXz8{w@?i4B+q_xp-sYBz$-Vohd)wamW}sm{rOJ;F9taA9)I~vx@fBsziq%A@3!Hm zVGNZyt8+K#DrSkUGVs>59N8Q2VvrAS`j)Y(##8Fw0=yU%##`Z&D|N3|y+Z7)@NFC3 zWDQ7zl^2UM@fJMSm9Obxh>tkMh#20x!M`OT9i@t1+3_sOKXFx3|$8f2*P zmI>i)aHN`YU%RaQDr7ZyrG|azu%PbFu<~MEHs1Ko=4${i1~~E7yX7yPKBENpyqM#~ zyRTX_)w#qGALW8se!RBri||2v805q2J}pqyr!c-8@M2ULuW{Q7N>#TbUeAjI5EEvv zyi&WV`1)4NGVzY-vQ4J9-hMRfc`+h}_xq|^Qj58(8v@>5Q%QqFn+d$pG5h86`9b); z#FTmOj;Qg*d>8n@<}q1c*`e>tLx5K}tHJB++=rI^8nqkn)>uW>W#j!PZ;Y>R#Q-PX z=nYLNWz%B3r3-V!xx^1_&kx+E9LFzGL02(Lbd|C4nx{N?0xK^D`S2zL9#Q$0xBCEi zF)ECA&H5N>VlB^aa8_^tV!~{^OY>9{VCBUu6K|K0cd`lD#w!6YM#S(&ENd#=o3#fY zgN#EEZ6@$Gnq4CA@i77KHO*gf=9n7qJ|Vo$GJR!Kk0YO;O~P3X-dH^^n%?teFyO^3 z8}HS;mR7LxVt^CxHrpwbtlhNsVh72!=k@(8r%W0&Jp*{LCec*}-m43aJp#NK5CgAYR8_=N>?(jBAQHCH33Dx&8IJSC$&@1u?u`T@K<`Wx`p&`(?w=bAT7K zY`pFBb~FaO7~sS^Tz|DR=JxeGu?ceFU66Z`I@86dAK=BBL{}MjoyP1g1-uyK!<*7# zxhf|iTL~*KMuqW8JfBf*W%YMyH(~b58{X-37r=|fnRwS4d{4ls~+kinnycW5~ zRsQ>KZUej+6~-I)T0xzw-7!hK3A6EzXmdFX@M3W$-pHqE^4hcMJ%AS@VtB_ktt&lz z>1CF7Z6@#@wq7BBVH=OXuvJeRd{&M3w-8=hSzY;Z@xyJ_&qOX z*?6h0<{5w&1DtpR6OKwJet-2)>>#=D7Ai(l8J#R~+kiFs@wWMOw<)Z=805n{`>loQ z!ok}I0WU^{@$O0fM}@rU-dMW{v+-I7yuoi9us9R1VXxitbjh>EfEOcTcqa{5C7E^Z z??}KqpgoKVM*uHI#PGUAT1l+K15aUH#lY8pE-aU+2 ze!TGu@7)2s805n{Il);aeLbiIR$hz>U4%*K23o8M%>i^Z9E(_AOW zCQUy$1Mp%*4DYgS4JBsoQ%(Y29D-;wfj4L;rTE)*TRKd&{o~cSYP>gu@EV%^XWLNw zO6w|QHF!%ZJ?XMA>-~Ti>$35B>(%ZHcrn08Tn-etXY@hOoQ;KV!Pr=|2>Y-F+6L2}{UVLX#cXutY8bQNpz<30U2 z^)KN4HG%9ZAKrlHJyk#dtsf0|F)EBVbICg@ppETjm@p1N{8z)qn`+X(AK=9-6K_c( zMRm!rvID#r5yRUkIp)-{oj3BJ%{T9U+c=f7n`T#301~~C{-uy?R?9vn8w}m<4T;iVh#PmVb4%b3m z=qhH3t}<5M;hwT-fER;&c=w)jQ)Q_gX~?KcBn%(C$|_S*ah@M3@yZ+e)eH2Tr_3^xLQoIcagM4`R^dF=e`lhuf;Kisg-t$kNQg&-+w$g6GY`pjK zV(_anEY8I1GJmk#b>`TYfEOcTcqLtKx*iL2&Ve@5S4o3Jn+d#=FLsh&=zIG#Om+C? zjn~z9RYG_NSk_ir9@x0Q3Rw-_l#JeVEz@lLwgKz1@!lGc*$ePufD>=iCsEYxM@qb< z3v;}9<6B*&2Jel*>_KkH}R*y2exD*Bc-3|F+~-!8oZYUA2fP^I z#QUqkJL%QtnRq`U=7@9oKY*IsfQq}sQGXtM9sqbTOLUciH=yOr0KkhuKD?_Y{L7g< zVO(8Uc`+)CS7(>xO#4@RyNjI_zLmG+^v%Vv@?vo&-tA}Z$#ahx;0>4<5ySiLTa@&% zSD(|`wVA-{c+*FDFKNYZnCc%Brw3}h8A5ndBu2_G^JmH`WHoqGX4unppN`xBc(E=U z@7g!cJpnHUIPqGBq)_9k^&TR2kX$Qo_P7(&^&vxX&x!;D&NOq6Xe8e)krpuo+E{>Vojo}jFq?fkTzWbF9!MW z*4eyV<>}Ny5Ab4C7;mE+H>vTeAEnw&n2p!bHEk&1#o|o7uUlryl?KOq0A7rU;kD_u zNqSXT9p93RLlA8y@Lt#*rWoGZxgkuol|1T+8t)q+yrrH-O6UGI_=HK}tOjpZi}v)r zq={_-FJ{?z?LrN<0A37m;%#_kH1%c9KTojRujvYS zG02Dai%pQ~$2HTPfES~}cu)Uuk}2f}Y_yv&8?S2q7HhzZ#hG|dG#{wAY5Es`q`-(6 z-lPN{>6V;XJ7A5#A&52;c#kaCS5)6V-2kTQlRN&I8gE3Uz@B$NV`HT%qHIJJvKqY3 zM?26C;V%OLFV~pV+ zLt*8`h!|d%%{8Q_vTj%dUL1mGGl92qZh_*J?}=ELY94+6g&Oa6A-vM_#>(rfmN``+ ztHE24Z%3c*cr6U@VqG@gyPG3#0A37m;@wucmiqTE5P#~&9PbA<-~=g6}pO9 zqN@zNh69(40lXOG!+ZSj7*)@Z{fz-HMuqX}t@%Jz7WVKFJ1gqHRyN+gR^tu*%x1u;e87tlF}!xvNy)L##dz5?4nee;z&pZqg`(AcPk)$d*M+@btMQ%@!fUbC zSh>6X-D*|HYVb-|+0qxr2Dk!VtjosxDY||U;KcwZ-o9OaNCrI9{UCObTr2Mm&Z3vY+Wpy75crhY|_fGCL*F=}0C9p;uSWOxv+Dzabd-jbyKIztHIJfuh zF1%IaEfT_eZ?B26noZQ!Dr5<~HuSO!E9(JXtjor0*1{qU@M3@yZ_vFq)FKPL*J20B zg}3E>4eFGhv&ro4Ya&AmUVk9HGg zi(jd`h0`IQZ9Tgsyj<~%y zIX|ydjrXe%UXR@-%DHE1;{9*JSqho1#i%e| z%G*hHBsZ-@y9u-LZi(tM16E!v&cwUv)JD1CwwPyt7b9YL?`)JvmL2|k1@Ph!M4Jh` z`sN0T*5;2#!BnjV5Bj9W8~01#16%rQ6Qy_0O?Z=na8`rY`KUFW==8fQ;KeK(Z^`6| z?ExRMf0e0(9+G&R!v(b z0$z*?<9)o)LuS_F$r9!tGrd`{ZD98Tn zUi;3E@$O*^aN<2?<|qBx&%09WAi3}c1k9k^9b6_tSFtA1RmRF&T%+Mnz>7gXyyHr& zRfl3iCIViJ3gfM@*i~lIB^m!e!~uwX5*u&941v4?+fM*Jc8*?v3*bs}9Ef;M|t=w*8^T`$7mWz0gP*Q?uFVDr7Zylkc~rho;&L z0lZk3jW^gK6Yr$J04LrtH)m7N>RiAtvN1=TOWgAseEUHyv!2%;x{6tTykR5VYXM#i z^5NC3y++l4oX!fsi&0^`b)xIYqK@l3ik%hpUn?7LOysN4fESB1@t&1N$e#7M6##fK zB8K-*f~mB3vwfA?wVA*hGJCD!_w^ntV5;5?_x)7k4gW2$=S|i%QXU-Ogcq_4XEk_Z z-CELp+DP%S{+MOsEzm11fNcW?IPuOakD!)Boy095=6Lb$F#bnbpMPNpUBxUv-lB@` z_*j1o^5LEI{E+I)R0ngwi&0^`BLa_8-4>z`9d`&{fP5 zU1e+=HuUUs4_00b^5JcG=e+8EaCpAVzuFVAAlb^g4gTm{M1c0w^Tm4hx%@V@ve8N~s zMY&j1A*;b#+P?*zYEp@J4`W?6-te%CZ(!xc04LrSvP0DJ&Qo#Ei#g(4;xENCURtJ#ofW>7_jqVj3s`xv zI1{gB=y=82yk@xaVnhsY&vs`d0cAa&XxC-}@3ka};!r#DWSHujFHdwMYTZ}V4KEbJ zTQJ^OIq*UmKC4VPtHJB++??L%Ei;9c7qe`e(;9q_{nx{5XV@s^F=p9Xj_$cJ}tzPDn|(Mz-F{aiO}h!RSKb35 zGw}_WSe%Ksjzy|GEf*2LXyL3?tSrqLQquqqrc=M7L zuY;8ri!<>SXFAJ|wA$YR@M1&^@ARgtCAxJi@sda!f@m{=*D>Iye1m~A-Zb)NBV9v{ zH|CGP2euTC`pU(hpFM&$31>BUW0y9ebASBBd)P3`#=Br&iYMU304Lt+cji%B+b-H8 zc92|n<5L>SW_52p2Jm7{qN|KO@5RIew*W5&`S7|pY*2k%Ipr~|yciY6yJvqxS;*!Q z_`X^kfY>Lo@#-ay{s4F}%fx#;!(6sh)_Wk}#fTW*jnX61k?kH>YS(50Z`|uk@`SH50?^zCbG02B^85~ym#ld zkfkQr&k{Q;e0yHsg6q2gFBWIwUDIu=Le{z%-v)#cF}#yzjF;LxZL(IoHWPRk{;sR| zILbd9rrIE1r;Zx$1tGj)aSfD4O{aaVLRN#94sA$(IQgj!Y#XpH8*ji$JAc570ZzPD zI@hI7j7Lbt4w7r-^@%!8{j~4X3c89l`SA|2Y}g&}VvrB-3CUX3wLK+m0WU^{@z$xF zL_O2{TuZwNvsd1yd)KA{UM$YUyZ(3<c$I_Z8naGDP=+u^R7FA-pNu8z^t(9k7Bn31>BUBM;Q4E&TW22fUbN;|*=)Up;iY`b0B0{aw{xgUQ#IZVe+53UHRw`L*|hxk$|__vcr9{G=@(h%9)K6?vhhyx zC|n76F~Es8J2sr!FWrgHaK#*PE^*JBQE`Ae_T|BO=qhIU@%lVHgl_}FARpe2m-eZS zc-n^pUW^Lkji_ZQvpw#(O6;ug?Rg*e_HF}su{aa&sT%#{5_9S|;Khg--d8n~B*PE& z!Vhduyh(#Zn+d!wBTE%`6!-CEpGgtHjnsHEh49*JFj1D-40eGwRVE5$HF!(rH>PX2 zOloIYvpY|Xd{*GU+XpC#hOG{8QX@nceddp zPBF-b_do!piXLID19&kijQ7l52U(M_MTOc;n7wV7aBl`)n1jWccsquhD|R;AGav9` zL=3N6(Nl?{LohxD8HXU+OyCWAxL7fEVbcXL)#IVf%++{r2;sHpZ=xI$JPQ{!;Vgl- z5j`YPRs?u4%f?$faW3BajsZ@*7LWc>R7mDfu?ceFE%4e))!k{*9PnaIqN@zNUCfT( zhHV1|`S9u$*H^tM>x5sGVN@9J>&ZQ2i^i3V&~CzPyl$_o@50K9#hG~5n>UwtUY3t< zz{H3cUgNK{WK_}A@!GYSz^m8)mZEggu6UU0@% zys;5&(S6rmz>8Tn-eNubZLsoUfD`Z3olU5AZdSfx6Xe2cpM8dsw)h?lUB#OGcyCRz zehhdq$cNV@d2jOghuu6EDocA&52;cn>#@P~_PB>IqYQoEOnTjd#UAfj#fNk@b~P<40|* zLRN#h13XZ_SQfEVks@n)@jhI?KNaN^C5_NO+N3@{NpNG`m^#|x;}ZThwbyjYXy zDr4on*7NT=z>7gXyvD9uRE4b{-vzuF6~-Gkwm+rsyA@xkf&&nnd^X;d-{>=d7qd*f zKm8ZW8gE#L&nm-+7+&4jTGHk3?#s1nGlBQXXHUhuArpVVxi$D&VX4NOB7`@fhN<%M z(k`};U9107AgjS^5!sM#zrUap;KeK(@1sXU>|y1_04Lta*Ll*6YI*orAIuTw5(5H?gDebi$OlTdlJJ{V?Vja0A7p=m8ZYleHid!L=5j4lXa4AGve@jUL1mGGl4hOt5}hD_}W7_ zw=*+i+o|zZ2;t3|Qb$>%r2E7wWHorR#+cJHi;VUGUaZT;>oEUgCE *G}%&rzqZ z*3c6>NG`ng)GbQ!{^lWA60j!GRmRG@GD?CEm&PC;-X*Q>s0QphXA5{SDvbA)Za10z z^Z`?~n=pIj-R<#vC9J$yoQZc%olElD)4SaUyciL~o89rL85~yct8Cq*f7^@c~{q0I|tu)tqAa9mWelL%rdv+ zug5C@FGj@h22GMmAI?3Hrd^u}yf=+%yLsEj>B70ae#5?l8gGUm-b2R9V-e%=!9v1W z4c^jv_2|1Xky(HjvuwN}-F|fgycpob>s;4Z*4pFhA+ZT^;q{5yN@b2U!rNN0CO_VC z^LzMJ83y_A#$LXoQkAb* zWo#QH#txaV=fxl&UfGbDs!3blTL4~+3gdN|e380snS5Tm3A6Dkjt#WB6MhNfsa1&+rTxw|* zvKqXRQ%&d*z5c!jyjYiww_C_;{COAyoOlQBjgY!ESb~3@m?Qod#jnafH}s*xkNIzb zu40xSuWf40V8Dw(KD$FrY&ZZhVK(0UqZzjWFJ_r| zOvfukzp$CVCIN}zeKKg7q-Dhce0?hpLA05`D_=BDkv}vGA5rluJh`(PZ^ROT zJ#WBP6D8ef#%91PoYmmHXI+n;WwvY%;KeK(@2dlr_-z9QIPuy<>Qj^3B;dCVm?O?5 z;w{LJr~Y(4u@&%Qmgp*DZAPhPWZ5@|l^3JJc!U2L$egD4!D~Qq z0Aj)%cpD9H1iYAK;&u0LE|)KHKMyM}M#S)5=r%)AQu{W3se?lhZ6@%Jop(r)^l8>9 z02t&s*hP(ZyAa-)4eKh0<*mkV8-%kOyvg^C>6KzCpJN@ZNm=ZrEY| zZa$t?V2!{bh&B^=w+_;E z>w0U-S(xgj`wp&Zyk~^)dh|C^Rvy@@Uxlm&?|_Q`{76wNxF_Jnx@^3DM^||PUJP*J zU9szw^t?p?{ydC1Vj;qn*T-NAWj@gpU*C#ZqN@zNg>LKi0A398;T<|?tm@0pXYqg+ zqr!L_#MPELCoI1#c2?AXt!%t?9lEUoyjYxx_wfcl+09z+!GISdVtB`750kw3n?V6y z9D-;wfw%d;x{A~_Yw>P~^E-Y^)p(19@D>cKqb$kD!~0Z)vl_e}E$h?6@9)DsFJ{?z z*L?QETi-FjiT6`xM~W(~TN}|+ffERPbxx|(C^ST(S|De;ip{tnX$4d=rT^Ckf z4D#Xq-gdoes%`IefES~}c!N7Q$-Zp5k9Shw0K|mZc>5;hO#{4`W#WDPDNepdubUE9 zUW|z0U6%h;VlZzBzP=TQAlgje-8td2+;PWvyjI(=?6I2~Z`@LW4{YC443(4Dbv6VS z!dVU8d%GIb5o;xr054|Qc&D3G$LBU+fD`Z4c^9b@P1ZaUJ4ntw@0x?uCRg8Fz>77B zt}<5MOWTU9051ml@ZL*Xqv~F;KNj#}R2XjxokV#(PsgiOZ~#HP+3P+B0A9>8@z%NI zBL6enXFA};h#20WW{spvYmRHAU7HEKPeQES*7w+X3C?ZGzY$6`-h)DT@AWcJ_9>j% zqY7CK-kH({^!|4l_%^}HD5!)vsCx@z^O5qL=?MuqWuxm~92kD5@f-GteA zH|zJD3V5+N6L0OhTV*3Aw=e^|7!kwUrYKnw-8OU@tPwZ_(Pjc~qNIt!r*h*Cm};}d zzj~|jz7WED?~AT-?PDFf3Rw-_27&eH%b~HxfEVks@pgTj77TbXz=`)*Jr}BYdn#UZ zj5%JspBsiy58_t8g|1?j=qdy6f{*2cVdcdjAKs7c`>LiT)=Gz!7o);>k8~d;OY`iC z4;{e)hzYatj%hwC8}MS5iTA5>nA~&w-AjNMBVu@UjMqpuZ@#3bU7HEKo8K-~oE%!w z5dfMki|?z(8@^0n&r9F=>)x*IZETZpR)be3+>~Bmmv;g1VwR0}w3`dQlL7;rc&D~_ zF3lZxKUHjkT-%1`gVs_#wm%&OUB#OGcz4!leg^PjkPmOgig4BHoYkuVFGhv&*6-pa z%lxL=qTPhqct2Oa;tP1OI1}%_ux|3=!Rzte!x$06JH%|gBqp#gJ~0P}Algjey|HYG z;_jn79hmBwmJNN>csC2-z1LJnnUuR6zatjTYVf9CtVa*|9*5fo%(C(R-CnXAR$dHn z;;kOtn<|-eYNgl&x$t_%2UBfEl;W-LSd-`~W99X2))K!e!yq5tk8jVb+RSpQ33xFo zjCa;T3t7l+|6=VX%*NY8cb*yG#o|o7nJRtRCdI?uu<~L=3~$OwUFrVMlfJ?lfkO~& zCh)#L<)~!h_XS1JRm>7yW#A2tcgJ@RV~`K;pdUFZ zi|sAO0$z*?;~n#94b@@S#`%C32OuWQ#=D@esw?2dEE8|=9RqpTxz&3CFGfW1KJO;| z*Eqkac5No`&elDmxR9i>gsEDs=rdT2w@?UgNwBVRrAHaw9wwaC;H8h%rAPK#w+`@P zmW{VtpJQQw7XzGl%PR}0GLKjIRT<`pbBTD}n#-v;lT+KEtC1VX=J4Z{FV5Hi+Xf8s z;jL5qrYbl7IbKzUQDM9;A1+h1n(f91c;NuVgxPq_DsT4%yqIO;b+4E$Kc>H@Cg8=0 z7~ZYsS(3N!w?}H%W&-cxh&76o`7`h*-gCN*hpF+F3E|C}t*aa|trp%rES%Ngjny-z z!zIrS0A9?p@oriCd@bO`04H8=D?h4l#T^R%Ix$C_OT=ps+Ky`UZ74oC7PI_#YtSwK z0bUI9;mz9qMYY_Zrvt3K7!}5wG1iazGp{!;M>qg6VK(0NpL^B^yqIO;?YtvFe$nrA zJHU$(F}&@j=}W^Z|2YF*9D-;wf!AepD@EzDXc?T_zUlWysPV=`2z+3Z#_KBe(q(wr zfN)lWH+f?nI=nmP3~=H#-Mg4N@k!LuZX575 zHJBy3%Gfrz6wR>%ycp!eTc`YkYU6}cj{q-5h4HFv*GgMSZu}EFqv}mQ8*kdN^E&}A z7H8s}Drq9`{Hkj_;Khg--V0quOB=mjyAJT;5JZ~^ygwg0D6ZdaaRa96x}eW!HQs%K zc#ZXxZF_aFt3p>#;6u#Kjc zp1hw4UB#M2R~dNYN8ULKcrnO_w@bU%D&LXxRlti;VZ6N`?5AvgTYu7S!fd>5Gf(24 z7mG9TKHVKDUAe=q7vRN+7~YQk7fO!?98Q8ZZ;v4j5^W~%2Im}?XC&Th2vhyxkmIYy zdqD_qgOA_c%N*}_s6tkQmkzB(|MqUu3h-iGHr|01YyAK(1~~B^aXv@A*6oA$Dq)Uy zi}o~<{kA>!MC`2a zt-KRYp7Vm07mG9T{tfIVYqBv9uWi7H7~ah;i=-vBAK3$59D-;wfp>jO3q@XZg#}FY zS);Dw)Oeo?;SKZp;VysXdcO);4PG6&0qy^Cyt-L1h_EXD;M3g~Su_n<~2Hwu6TK5OM805oie)6*F^2eyrfES~}c-uMMls;{w z9Hrfa*(`fI_Gc)*Kw*?7O7{ZkF_Vt^Cxn%di_ zkf@>fQ$OZ-SKdax$Ej%B8dIUGnB~X&OZfxwVvrB-t7QjN5x(bY173^@X5?!$Yh;0x7-vl_h4Us}>qqwB{2FJ{?z18g1e7d8xV;!Vp> zrlPLwErWB3IbOWZN2968b=G^KtC;1-`)p?--bsN$KD<9}WvN1DoUadfF)EBVYp1u?q(vCd^)W?ffRG054{lc(-;oq4tm-FSS9wSX7vvhg~u%NYnOF9taA zJ{q`@8hv{7NwI_E+BQU-%A(vlO|XHkVoiR$H!jWX2-^k>^5H#gxI(q4>GbY^7o);> zXU$zlJeweEg~m2OuWQUU?rJ-<=ODFJ_r|dlh8LmZl%t0(dbZ zhWA#VG)Y@4YNmE=Ch)dRjZnD#GY^7=X{R(dNR78t2ydxwx%+aRROc#W{~vE}E4slm zUn{_ib=i1dIuASwcrn0zaITdSvkCM(r&_RywaG~%>XYJXX5?fxL&cM^ZEsV7b9YL zPYyGZZdzg2OuIG{c$-v)DSEZvR2Qb&q)D$}HQp7=1@^rE#oMV`Y@I4(0q>rd^V}G02Cv z&@)H1cx2^sz`N9zJR!n(+gwii&-=F;o`bW30}vBtY)naFb@7sp4f8M$QUM$YUySTEL z`tb8kC%}slF}z1~y`>AE&{^8GnZVn1{S5h1lkRxYRYBXdIcmHrA-vx$Kf6B}Y0P)w#UU|n%F0=u>m}TPK z=5$OR{{3$v;Khg--X?49r4{FWuL52if@m{=x7+RO3f-GO@mI1yE1&slybp!&j=EUp zK0D?oUe7C>)!?1Eur+-!YSeDPi&-|_jL*+90WStP@wWePkGec)KVGnmIpSR6%4?s! znew|~yaKw4S)!|ql{e1d;1|G)K|Z{1_Dofszq-!|@M2UL@1n_FWigq(55Zq64nRzp zjrVrSethT%W|??h3W{XIh9)HgUW|z0J#nnNuKWl`~o5z~`c!QEB+yuNByLxjrsN!b#>i&0^`F%7m*wxb?Nw3{#+ z@7b8{cn=#EXX3pyW|-VP(BB{MVnhsY+}3lFj`F#O0WS_gw3)#B`a`l}?;iOsn5wFA zr^RZ#iBSR{*mNAr-0eHAHm^cfgO?6%MVC66;rF~)myOpwXIL8G#Q-PX?0MB>dOb6m ziyb5vUXypdsY>ZcW9TZ@B)ZC2c|RRY&jq{~TK z&~CzPy!#gJFo$ge7H8u9?%^ii=BE1v@M1&^uTw&#ph=u#!0p1sWq(P$11m1JQPAL>N z7n;JkU9@09gc@(Y5Z=g5rS7egp0BGyR)g20r8TWM?1`_k!n$m{%bzdAJ1H>0iFZd- z1ZDkc)iSYzD;i-WN(s zS^u1hdD=~wz4C6iZkz>pu{aZNtC2rswe;HL0A7rU;Z1tyE9qChF#_=75JZ~^yn}wc zP;_&8i5Jk-yU{C3jrWZZUW>Eu-1S?S;Y*W*vl_esdo1Z-Y0p2f=fx}=?}HpK{COAy zoOrwcOQ9;mj`f3ci8*2+!VhdF?}DgBzE5sJS20U;m4SDb{LL&_c`?X`cip0$s`JOk zT!)nxqr!L%_g$tQhfcz4{cr$c!fd?n9`wPVhcU~<>$tPCJilJC7vRN+7+xp8TGES4 z4DrE4I0VsV0`ECzD~0h?uRJ)nJu@DxRO5|UA+YByz5LESwv!CsTP&Q_;B|Jkq+jng z>85~yk-k}$O09!@&8gBKoIXu*Eua<<;5%$@A@IvWvySGwfaBG z?mRB0FYW_)C`+_hvZsh-U&@xbcV;p}S+j3ZqU^iuOO}XG5|XV55!pgfj7fy-S+kWS zWhs&^Jiq6e*K3~hxy!l3|DSX2`QCS5XJ+mKcrhY{w`SB%#wOEyAoPe>4QY@lGlBQ1 zOGjl;M$B(GxAqyH>veb|X?Sb=d9CtyKZ4I~pl9`X0}55(nyndb!Wz%fJ z5HAivl$pT0bD5p8O?D4=SStHEYoiWt5)CiYGe_mw@{P81;Kh0Q zc%5UNo4B^w{5SshfH_gTF)NR-Gg^%=0=$?ds>;E8e?grzz>7gKylWaR z(%e1JWG>*vC>?LzwNdQc0kN;7&Wae`pZ8nb0=zgm7q9gbf5n>mcOL>?j7Z@fwX79$ zWXqA+hLxGX`=XbT(#XCCZtweCNZzEw`0z;|-YHIOW~O0{n#y zvwXY}Y4;xhUJMB0Z8Py8TgAHPMX7@n+BSI3T+8-)sCfic#W}_CPQ5V#pAv~dF}#nj z1Znb&L(T(UjMDMCUalzb5adzcum$rw@3b|g_||uvoQrpQ-+OZ7e8qXdixDZjrz0&G z#q*mD4J$K&cjfGFirD>a&%;tzg>DPe;Vq`&wXw=p-CHmSw+-~H9`E~24O4n-eKQg| zFJ}38Z66L?26!hTwB01Vw8^e$l<-LL$+zKVGHKt^|~+;FGk17xp=oK)8(;4P7DOR7?HyJAXF<$ zsFpg(urd>PSLg3gntTo14oe-lX2v!h-jKDF4{Rk9a#X{eo+o9n#+ zFV4%y+mHQ%k9)#^Al|Z5vsr~talX_+3gNZRXu(=sJ=`6tigSwNeLCt7-aUMF8(CE` zyiN8+X*Sf3od$R@O2_-hC5WwYcn1C|g98xzBtG5>tv{8AZ3AYxcn_?6t7t8cGzGjE zk-|H8`Z!s)-ASvV%s2#5W&&?PKs{wrQo|THw`az_*sjBSgobzKhc~L+#M-s~A*;um z(7-n3&l33{z>D+p@jjd~I08B^1_be*ogKzT>{)tS>L7*iTI9E8rw`ly4XTQB5>@5w zdB^vUF@?^HK{33}PHQy>UcS!*ycnh9&1KBx&9?P-Fl@nmybbH+;U$qcITvr0>)jO1 zkL=h0crhY{H~D3RY*t!n3&YAx;C)!TwQ}i_X%k?nRRj9()ZtB|;T_=qR>iLFiLdUU zXZ3gkCO1q`XU2B}yqM+Vy=vv#9`Is75U;x454PdRBgdr{D1UGQ|_BigSwN ztv|A_JK)8j7~XZI=QP6xZz2%CxNx`VVpPwQDy?~soB+BinP|)m@b~YvRj8YhlV#L;GN3R$O_-X zM$hW;zVF{4W&2nU{I&tJe7p~wJ~4n71A=(xJ}zd5=3K;EoH0lIFN$B4-R!-F^>R1q z0C+J=RF%_t*VK7`8}MRK4DZV}H#Ck;+wk4P7^UNNE&H3%-fV=I(cu8Zg86v&UuuPW zUd(dw{+R2)u6gP24R|pkg?DOQQ)Wl{HpJUFg)~T%nZP@5#%bkhTO-c54N1GAba?&O zQTDviwF^{7o;KVFf8%|qSv}sH>DDRxeZrPQ=fx}^uY*I~9e@`Df_TUHnXq#mZ5zNr z#;5ZZDAajftShnOoqjt3Ud$3z<=|a9^*MH442t3P_@1Z9)}DO=ofo5YyvGMeGCoQp zeB~z&K*d{gfA6Qzc`?hyYun_2GVOir0>FzADZG=)Cd$?xZ|h=MnF+kXH`gh9HoJh2 z=1;%VDq4qkCk=00zdY5TZP)R$5Iw8M+w580ly7euIRReG^6_5ovS>Hp#eg8*JK@7v z-(7`xs|eRNNmP}yZ5W!ns5;=qpcvk` zK^~gwvld|I#V8%`l+vASX<-mPA_xZ{{#yBXXXgHC4R|rj#e4Y7HHGuUEByd3Mx^i# zb-OBiKlSxo!^%wHy%sS*`AT*Ve;#&rNsHCtEu`V~jmuL7nmgry3wl>%52VdYu8hI5`*Z-DMpVX>WtB173_s z;T^oQK$hM6)?35MOyK?7w71gD=|0}WmOW}{oDT2$Aj$`}_Y3k=9hVHlA1UbB|Hs?I zG^K*pbr|5qEFW)$k=1?zUJMB09oykKdwY<7ESyWsiQ;W}VGjGCmq#b4DrUv;-fkB& z0`Ou`46p0CU`=B0HZFh{qY`+3xUe_074I0fV1DNTRJ+^sFB5 zqu0hMEuAjo&%>DIx*mE2E<8z2`PNJ%u zZG-IrtCN5igJO6yFNJDa`=8GOycnh9{ocPHJ2G<-{&a)`5Pz+Fyj}myz^lqI%f(xN zZk}SyUt4^{DMqC5+A2CRoj$H@4m|>gAj(YOZR6Tq*)wh;KGy&8FV9mtyq9TsAKB%q z%*Qvp050fRJzmGzt08P^v&FJ}38%WAgH1H2dz#OpKn7wcbR1HPgGbHusCZG&5= z8(TW70X};ZvqV)ncw4o|P6oUf6vMl##&wN4|Jy#mi%~k>^*a;UVQ-`HzZx8XSTG;& zK(ot;7qeWv*Jt0C*W9%KFmzswNa6Jx{!aG5$14`_;t)ic3B0?mjaKH&ID_}FJ#JWV zT8H-)74NAxs;@4KaL-H6>hb#8o2Fb0wQmD>G0Vq0=k(<)z>5Jvyz^dmm7Bb3j?d@C z9C0oYuaS`#TXvu315_2WL{&L>7w=6u4|p*shIfC%Lz)%ieehLQ7^UO2l-sg%*H6aZ zJ#heH!F;?^S60Gp17^8+J63R4R4n#83wSXih4;5hw(P-_RD2r{4ndTez}d%)yrnd}(XVn;Sz$mB@0D_^ z<<*Q{l}H_=(6-@1wi6q_q%J;O8s{Xc%E4P_)2p3;7lUGW2fezgDIQjgFA>Bj9dGG- zhRuGv*3Pg6^YL!iHn|OZUYwkZx6k4Uiu09j^#{Bdk;416x;0Z#d*ul92pobaGl947 z>(0u(KF?mkQmZDtJEy}NzMk@d&G%NWs$088RsSKY$Lktpn$oS-nRb8|=jG$A?^F~9 zofiXwc&jgLC%-YP$}g#d6vFFXLB;<0ya%7#fO8U6<>0OLV^SjE#h@5oqtO|f)lpG? zux-F79dAy*E3D6pfSHCZn2+~S)xRNt7boZ9&33-7X#MKeGr)@xDZFNTy=8BL7L@{C z9D*n_fp^uE)yhsA+u$|1Z;E}Bb$H`xc$rCWRS)jJ>JMe2XZ3g!c2`Kbq1fCS@M4ya z*RQm#GvLL5Al~Cg_OL&@j(H+=kivLF*t9z1@H-rwlc*{O@1upKQGgeNVt5Djny9&v zd&~{+Vw8^ea8q~r%3SL}!xqfPTk@bAJ~0O;=i;rs$5z>N{HZg57b8-5qwT)PJiXRn z=fxq2G81@>E8kRZSa=!#PMHc;8Xev{Qh2ZYNW_bJ=vly1FMz>8Tv-pIHVd~O2< z1o76o9?ib#cNbrRjyYlr_74~43#U2K~}ndn(P-kFR^ zN}I~X?tmAwe7rusi$+7|#eg7Q$4o!A#cZP_se=^myq;{H*G|NXa}rhM;N4q$#st8N zK{33|OP^@=CGKAZcri-H+q?R7_EW7>;|*IdAMaw%q*TC*lXLM#I=7JZxpU&b%L{e? zsvNW(QVAnccz-#MV}kr%5(nyzceuFpX1p;l+D61W{%JZ})>&6i%(W;CJ}#)<3;FJy3gM;fER;ec%#lv(iAT45(RiMO2=#b!;Ot_dWm0P;sC^g z`FQ(}Ehz-NnC0SicKgOQd2e$B@M1&?udLBk*~c!+D?yLIA&4>)cq5`7D{n7YjobU= z4Wq8>@M>syYn&-orOm383V7*RJ>HU-pW4=kCgST`G0VrRb?fmR@M1s^@3jdLOoa2G z8Bzx+v~4&$wJAI8Vrc|a73Uc*h@M1&?uX)eqvd`Nq;q|;Y1W{%J?_Hz&$~#w* z&cagX-G7j-!~2Yem+>xEbuM4m^B=N$ysl$DYquV_JPA54&dbL;`{9GrfENRTc)e^N zvB7KS#z-Bc5Z(;s2KHzZ$1{Kz=On7i!OMKL?hAM^D26xZ*i22gbAyusFGlHjSM40a zp4v0zn_&y)<7Fl~vVa#S=i=RbDTiGoD~JTV7?Hx;uWwK0OUg9d5UEc)!!|-c0|jDmwUW;y+{wydSjwSyS+>?>H|XZ=Ldc696v;1o58qFJxyY ze`_IikV1Ha+8khaZvTc=#W}_C-a9&R8Q{gB7~Td`w`lfwpLq*-F-pgK=d+`{h4U1A zzY`8X-8N)T8RrgoG0Vl<=BHeqp0Il);Khg(-pgHGnQ&PM_6Qt;C^Lb#(Fq4-m(lH< z;oROEq`j-d8@7@1fi2GSi>hyqDZ-~`^>~{-`>Y+@(c~?3Ud;0GelKl{mqcPf5bw}G zZt}j%L+}$R=7@8Nd)^D#3)!{d8$+NaV3w#Vr}O?9wyzxE#h@78+~vJA<6hUsJugP- zcrO<;m#;~fhF@&s0K|g%owrK<{xragSuWnX^LHtir@O8Nycm(foAdsR%+K|kyCsR!U)(akwShxa%QukX^Ys$lEgc;)EFfwZh1@6Gg2+L7B1{sO$1<>T$+ zHG4jEUJMB0UHWvT{Px(o_%eF&>-BR0FGi&BMtpH+ zH2r%%G_1@7-X~7Al^Ij(4}+!lJsST|hc}&ux5lmSs!mlO2K_@;kGCYINISZrq66T? zdHHx-CDb+syciI~>+*R6yK&wDe3BsMh;xZ}E%FPQuf2-#AzGLf$GhZW86UulK{32n zSN+kHyKt=|;60W^o)9|T$mlz=4EKVba8_^tV!?d8U+(r?4tO!k#cSTQH`8xTY&XD* z5h=X4az`*}m!6deyf_3=W&*EjubI-nmhTx@>XMlbPjqVTJ1(zANJ zu37K3f3u^;0bb1V@h)7xb|>J)fFR!CW@+q#M)&aB2FwxX67l-_2D69k(?g-Em?f&p z*)}M;CT|D47!<|ZZI33b-qI0(7o&8%gSJ_)Azo`TrOv2slh4QN8&ej)=f%mncx87& zl`l_T!V7aSB8B(Uu%65*U-OfOm6^cXC@xglB;Xz1J=`+%V5Sc5s$j~Vx5VMM$|zxZ zFDMf|tHiZj-3~SVt5^6o@;Jw9aahOVw8?oG5#QXOdjZF*n;_Z&3}G42b~uu=i)u- zy;C;8Cm{(sFGi&BHVL~Ui}t$z%CIsMcnh}gRCs+V#s6fy(&xR<;ftzrLH^~!&u zAC!rn)#EL3$km1(-{lQ>G0Vs6f3OaI+kgQwsWZQ_)L9Yhyhk3kp96StaxUI& zO}ypuq5Y}@UW`cL{WZdgSyH+6e8b92;Qes$zT$kQ)kj#WQ;}mV@TM;SFJ}38*Vx>Qfo%f@1o3(=>n%U~*hlgp1v~GZZS2GRPb^dw z=M=}g_M#cyfQdmdyzBQxYid**90_)c&prRp{(@xZcD%$XZ85C4)0?c-mC*g zYM&qS@Bfh1#jaV~Ms8&M~m zZ4lNRFL%N$QB}^KcgT9bo6vbND26xga2HLJiwfNHVw8^8_HqP!Y|0LNm;nwzESQhC z>8JB@5V9g!V zb9H!&X?UY6mQnw_?ud7l)3bWKDSl72fsS+pcww zB~oWpY}@etd=>n*0Vn6;eb%6^{P?kQJpnI9r109mU&|!d8)ge-UJy$fB+5+SbqXs` zxQ=;J7M2=!$>g05Z%7E`16x9CBXv8w4fr-7dRC9uCg84i&!;PQ0WW6xc+;mgH^D z#V8%G*P?dGdkfRXNu5zKyw_%#Ct~M?B6IQjJ~UF=bPu%vym-7)cwK!uGU3_sV8hBx z;9Yg2hVn=4fH$zzt9_3Z=SEbJRjt`@0=}F7#@%rZ8)3z>m%^C1wmXG&k zu}cWx#eg8*8G#=1Lt|xYVS$(v#aqE|AM1Dc7hbD}S#i9(oHoV-UJQ!iwVHHL^E>*? zLBNYqI$r;s)7T!Dk9RX{!TfE*pt2r#VGd5t#rwzql5)-9WhHkn=`hXXMVt5Y+ zT)&u7|IS~)i%~k>8BbQQF><2RdKD6q7i220Hw-LXiAH;0DTxBPFFZ>#)s|B%(=4VZje+iu-J z-1GLFPR`56TRv+~0N}-dAl`R#O%)Y;8()Hh#GEMJh&qXEpV%^Mp(S9Js453<*&eUW z0WSu{@SZV_)?DnJG9K_^l#cgK(lFNi@2-1>EtubV%SUeb3V3mHE?)bp<>eKOo9za? z7?Hy3TRfRLx-VpkVPz)p&JP}`d|F{4p4$gsj(ySL_1{F<^BTqcQB_L()dk8#&+73S z`QO(n;_5$#&Wl+--n*7#TmUZy1o56Xxy*RTKHx3Rm=ne8=U#)gI<&$Es)|{0ydzA; z;yr8_6vKO?_ixQ6zjOGYJ&e-vdR25zzT|qViqu&V>%1$xUM~i`I5`(DtF%*mYM*5V zcrhY{x76B%S#bYRYs1P+;GMbXi^A0P$8%V!ON(|TI=nk+cs;)TRaG;s68aBWJzm$W zbnTh0zt00+oR^RH;gnz1051jv@xHy#T|W81ZoJwabE0^gxP51;d@)@CRmH40-Ub8W zmq6#mpcvkd(WRQ&$A;%Z=fx-;ukEE5vYo3EZb+RKF}$50?ClPCadIx+^yv!}Vc(wl z0$z+r;hk1v4%5=k`?+CdCh(4!nWN|s7f}b6y83+VcOBjY8eZn!U)7D{QKtWp)#Lr| zW#QTr%xrvOPTmc2UOwK@eoDN17z2WMn}@w)pY>_l84eP2qIi9MLzwkVQf;8Bm=(v{ zVnc2$;KiUA-d24|GZvt~ddlEY@X2tO~ z`r_vScrhr3cgr`UOF#d{I{;pc((y)4s>W6eY>$sl!~uu}^YI@0IA$r}#Vi-^g*bP` zkSl&C053+Q@D>!@mOXAY#2oPA5JZ^?ythU{y*Ny7qmO$qD=rV&dbLuFH^@8@M1s^Z>_VB*&`EP z;++(jBmNh~&YL^iSr^iVb z>xbf(pEv-qU_RdJw?6KHZ3AYxct3@#RqQ$YVIttgh!oygzRQ^CJ(hO?FAhPJnZTP- zuYxjZ)aNz;@Vo086CK{mG`!8`8>=0=&&L0t=vh5p(?{pD!6znk2fUc&<4w|zXbX5T zAc(i%wp^|bVew*g%n|1j@lMNZ!Pbu~Z3I=tEKyZX=RGkmrY_*cpcr1w{di4Smsi$+ z7o&8%C5vL%N+A;;N}W-$ZyR2DC&U3>oScjIVqK-OrCYhGfEOcDcpIM1l0ECt0KY23 zA&4>)c)c!#&~RR$b7upG{9THg>;9o|wJUe`@!)e#QYef}Y<$7>Uipxy8B zt1jThdHHx9XB1ciUJMB0?J=y2e9z79_`fLTh;xaZH)iD^_SLKL`=Rq`-LL8Ld@DY;0i$%hRhp%-S>-<3N}Uz4&b#JG%xLJmI5`(@QqEQR@$9>I z053+Q@cya)LN`ah&j>D+r(`ITbOt%1FDKyalD=P z^eTouF9yZ%vO%XbS%UW`cLoqYeYY{-{QRShdMfp?4jFJ;ZAmiXL;@TRuaba?O3@H!qdRwsA*!`ttEtftMYE8hVxM(KFNUz^FJH+K9Ybymc-4TUkw4*}laok$H_ zyhF0%*;`L+W&vJ|NZ}pVAzS8L#{D#u8HXUsOyITh9-*B7XCA)MXRCd94ISS1G`zv4 zCTf?N-_4;+^sFB5BRj3OZ{k%K=)9Qa7=I_;Ke8%Z~Lrh)?{8FK0yu#ApTnU zo%eVBYmWdgX1RFRWNu>1$s7U!FGi&B7S9{ObnKmU1IqlZBWaK*GlBQ@*v8811y6BH z82Q+umJV-V7-i4<=%TUuYy%_w{-2)JS3rqvK1!ivdBrL+xM5 z|0t{B4VaiC&LwtUBcru!R`cS8P*uzlRpsDSS%r;<&Wk}YygjC`)2us_(F5>el#Vyt zt13Hs-l9|R*NOuW3+Cfx=C)=4FJ`%T_xp@gBz0*K2Y4|eh1a-jb7pf)0KSs~hak#K z;Pr2}L+O9F1n)!ZQ+TnC4sSFKZ!=dDwddC@tDsEutRCEYF8CWZ=7@8Ncq{l>GLbRn_y$bO5>@5kwH|IW1@P`S(hyY@!`pPg zM~#DV1HAPeqjbEZ#}u%w%m#+QS-}B_1@rM{BUId0I`)=#eH~s64X@+$^6KTK*YHOQdRC7&>!(KB zt^RQ{=)9Qa<9%yX_YvU5fFR!Xqg%+;iTCk>Wy}%h67gDR++{AwGqRwnm?f&p!F#lI zR|fE6Pz-OUTP2!`d#v%D6d0xBja+dF6kflMsj~A{lM)OoGlBO(2P0+9x-yqxslU>GH_+jIM#EdZ<3}-Ru$BTZ39N>c+>N0uv5pEG&O9&{LUM7sNMj;i<5Kl*8RCcS*!NX zaex;iQg}ZvEz3M!Tl@&{;t)ic3A_;xJ1NWNb*KhQ{W4%-Lml4lG`t?OE2x#7%<-vM z^sF9ljW~_AVORf`(0PZ9CFkYiJ$bKucj&wr5X9TH-yV7OtvPF8ftVBRyg$}eU>{5# z;RaR3EKyZX=dJMAzbD|upcvlAu^%)crip_AFGlHjYq(jn-A7urH*CRtyd|Et5r7vb z=i^^vBBtTnz32%~hoZFgicpI`jOpA>Nb;;)sD*SO{*{I&tJ zT)fj7&rxht41NxHF(QSxq}MB1*E`h~16~}0C^Lcgc-}`v=Fqn-;M{t%GwgMEkJIqR zjjyPV-?qBkKV^ht!x$!H5W7_BtcdM- z(@(Zs0G$^n=i;qvW~x-Y^t1uI7?Hwz;90uNsA~sb!^%wH^<8mTaiyRY-YDIwDBnSc zH=T;NdL{LR5A}CJndn(PUXNgncFWk0Zh#lFe7vu(X8r}d7!br8nNUZbJM>Rwse=^i zyl$Z}OqFTZ!=b7;r#RlA*1mW#ItIn?rZ{}l%Slg!1yE6)sDFu(Iw zyq1>g{yABod=^yvEU;*gLJ?;CDbc z0P$Z9AFsm?_ga7#vs}Du?_X53n?E=m@M1&?@6#R|Wl2Wz4ThDOz-v8Ot?YQJM=G4# z$p-aBB~EaR{Q!1m0ZJ70NNA zf8o!=Z@vy|tHT>f!&_rWCH3vV61>%qp4H=JOtsn-jrTqRyqM+V-88VmWWb97LA=eD zC(2EuKHx8Gm?O?5?s+d{2eFHPhTAY3`dmcOB#h@78PO-6?N~U9<173{M z@jgqr!a7b^@EHDDaR6e$0-g6oTr0qfSuWlR)q5%0Fx%<^UW`cL4LwpSyZ5Z>X26R> z5M?ItwjJxL9Pd?cG%U5*uDZ&ILV^>`oIUDC=!w&PW0nC0V@ zJM<_5yciI~JMF+a`4?aBE3m*#6Lb&`pO<2=yGJFCYW{IkD@IH31Y7BTWD2Df0 ztqYnhKPuyM8!$@88zRqS*q+h93|lZCuUT?~Jiv>SbMaa#IxEKd9(e(HF(QR`Q+$7! z&&nBLfER}#%1q$xI5|RDtDAMd4OJ{bXBS=q zyciV2d)O;M6Yh|?4LUDI>39cqs==l%ot`XpR&;-@e7vbCQ|kj>oScid;jaw&^2JXS zfEOcDct>6@!`xClaW|~Y1m2`kos|1e^_Ig@e^^xStixMO!|NDSQC&g1KJOp0db|Mz zaoR-N8lM5Lw=Fp@AMcXzZN7jP1A=(752ngbuM5TNc`+x7H)dsL_QuhamvV<*G|Gx6GvTh*5M7=M)|;Y)4!s+X})Lq zf5__b-t2u$+w%GCmVg)M<>PHI-J%fiVn7hDdzxGx?h+d=b&x{ahL#tavNnB!u&Owx zINnv&#@+(F7!<>s=y^|5XK(f9fES~5yaRSUVdK|@8@OOT-bjq96JFrk?Ql+_ zs+?^@y_Z$K0bUG>;azQhKyxnrR0qI|Q952t@K0v@?mB-ATQDDQo7;bP0A8G&i#JZ~ zt6bM*N<84jh!oz7vwdYHWj(I}UL1lbGl93v(JZCyiVygCrr%W~g${2T4X@3Qit5mg zJ&d4C^sFAQ>zHHOPa7uo0lb*yL7*irVh1Z&)uK= z7pjVL5>@5ky*jVXB*2S7F}&y2Jkyvx%xMpJF-pg48eT=7_InI|fr$f9w+(syFW|$a zG0Vj}bMU!-jwtvwXa_pH}G%crhS|w`NI2x%sj;Nm2(Xgm;y*8GH2NBvZhP za}rhM;5A>|t|Q>Zpcvk)dYPKmt$q3eUX0T5=B4{HZ+3nvHEhBB&O7(vmB-L|adIx+ zlEK@UkBv=sLFX-wBmqg`J#r#NmXuX`49bi{5M?It_RVlm`o8qp3`_N?>Y>)*^$(}) zd5w&#sB6qB4g80!9&bs^X>AAP%LafK=jG!ad}7@Uz>5Jvyg?sr z-!cu&4`f1BaZaMD9K6>G%j1s}7!<=>Wxz{~^NqX90WU`Bc>P`Dm}Rkj@G?3afZBOK z&UlK~^J12ZclO&_$^e^OIpD>J6yD+U%$Tb-ukm``w1%WXqRa%|YTo-5y5ny&BZ29N@({iK=q&#w&bYL+8by7~Y*5uV@~*rPu>rjMDKcwjXAmPK&WL zY{C4_8}_BMH*{W{oQrqw#A3#H`I@$X7b8-5n?FpIRm&~KOGt1CqRa%|H?cm-Qh5wM z?rC9Aeor0V1R7qO4rc1Bxw&PaO!TZCZ*<`)tyRxXBLFXE`FQK^Xuk;XVn7h@NVP)# zv`P_vk&QW`5&a)P{Zk@?jybVjZOY(KoIZMd!F)fNjqM{xx}0(UWFU`&_gwBgWF}!29Yc&3) z?}Gs^M(KDjkF3dB#9N&=Y{7iI)!W`p0=zgm7jN%AtJ%FH>vjda7?Hwz%cTPIdgH8K zQ0B6&NP|R~3A}SgmQzmLWStL7-T6MPpAK&!4ez47%4)A!@m~Ls)#J@tct`8^wXF*9 z;=Fvk%l;^o(0MT+h&SkhTG6x1=j~DlDZFhkVGEAc!5h=Xy zPR)^-N9D%=UL1lbGl93e>bcVD=3o38bmcYq03F`-+bJK|Ob42&$ElpRfD3w7kJrN@ zLp!bU3jDx^Sw7xw`}!OPyciI~`)bK9_CddKCQ=6}g!g88ATz1zml04^oRg?32k#&E zaSZ`42F37324`x%*}l3Bcri-Hd$NBGxpU?Gm4+>tk9Y5oez&0W;^bVs@An^L7N7U7 z4V@PwQg}1Q43b^$ml11NnF+iJo7O24qF&=tF9iJRXZ3h% zw9eGpInM6^oforwyvsUISr2$IAc*(#yDa&Tmnr!91#?6r`agjBJ#Uefiq(8>fSnh! z;&@dPUiSyQ7!<=B@OYBODlPLY;Ke8%@8}Ozyyfmq`v`b3%f&l= zt+8^>4~Oo67b8-59XdCX)k%!Q7meZ&M41V^MUUGntrUY#!&2+cI5t#=_c9Hyk-wR` z`Ok@A|B%(=9gy%)+kaE?c)*ME^6`$ETKNay#eg8*yTJhprxjbSN*$z7=WThRJv;mG zsOHcTa89DCoX&gqy7xxFi$O8G^;;xsQd8K^fES~5yb5y9 z7qeWv=C#`^s@2g%1KuV6Bp@lgM$xBagAeo?3}wb4h%ys+qb9voc8U$Rg>#$Gb^Qn( z-d8ld!TDzD%$#3%S2;ba#~atDZU1+G7lUGW+ctZtnZIt|C%}tQI^M;OLs^fdWAR4{ z9DrCbzw;{V9G(bxG0VjpR_>ikmXl>oz>5(nygRoKk!{{PcAc%L7gKym^*qG|x|~o&sKs(((FV-PLvD zoO_F;&WhMqWh3|QN&vh#ITvqY^Jta-h!d9qFGi&BX8bxJYx{y}2W56xNg5=|OyI5j zK2^2o<-N18)L8RaPaWRy2+9YxtOgcptBGlNV=g_b$NOmC>Hl8ex?u<4#VjB1*jL{o z051jv@z$GIDmOV$&`N57LfZyM$ARp$ahJbBRdG(Ds+`X2@xZb@;KiUA-hme)G`H90 z-UPfDrQPPY-&nu$r&!3QKJi(9TPg1 zc(?`N#eg8*&t(V8TQ_KTQ0gFs@UC*UVy8^%kB>OTImPjA?wG*>UJQ!ieY$R-X4t$h zrGOWsbi8S0VwsQ~;rOcz4nX`@!^b$;Y)zK2Hn) zyqM+VZR>8G26!j<-hUA-3K?)c*plHtBkca!fSFX&2=5G!~33w*YtK3b$Hksd`cuetH&Gca!R}H zYzjVf1hag+wzX&b0bUFU;yqCEUOv&e02>kJh(?5aUW-ZoY?p1V-vM6C5>@5ky)vk6 z5p-S*is4OdwM%m+Z$JJ>fl)eMqh5EICKcR<0bU${STG-NT#+2V=fx}+@6YN36!#Xd zo&(zkj7Z^)e?Oer{!81{urd>P!*=abCZ0Kb4wm}!?X`(Iyn#C?d)`Ht&D4coX2t$P zR*$zN=D1dSElmlX7w6^U4V>P_6!2m|5O2fc0df=XeYK?yQmFG@$nMC>56{7yt8h+n zyjym;zX7}$6vMlAX{zSEcNKi-2uA66Emv=5hOf5jY1o4Kc+>Xm=m(t_C+FfV$_-Ym zD_isu@M1&?@B2BgnK>2NsepIXchVqHW&*Fz`mV|{pWF0>rB+W=P0`_vrs4H?T}A!V z^ax((P0#A_x@MiyHvjB;8SrA3k2h}r<9UD=1A=%bzH6lDkuz_A)B=U@hBhw4etjE$ z9;%9S5>@4N-pbX#tpvOn6vNwBouj!wG6*ls!6+SX_~$z8yG*aKhAo(nH{kmdE#Sq; zxp@1ZHkX&IuagOQF(QTct$ju2ZCk59hLxGXTVGL08Myf!zQr=Q_ql00yc#Or&1ULV zQ72g_6FsZP`@gTUdOH787r={IKHlktL9+la1_bd=k8UHc^v(}|9>yH;zbI}S&QAT! zd^$AM52}h;alBoIJUk9~F(`(2q-Cb2{+}abV9$$DI^OwBt};Idj{YfiR&;-@e7v1Y zPkjZvI5`(@neOG}c2Ay82fP@O!h6HrinC62SW~mpo8GyzGRo@{3ku@w!dS ziQ=`+Si@|bx(C0*!K^r5fEOcDcn81UB>Q!#Exvmghak#K;C-~rS~+yvvAY0p zz4y)8I=tU$cs<%!sH-Ne%K3+^9&g00Ev)mP^1rPTS*5^zqUs+?_u051l`@a|cZulf3E0Y2gsqjbDRAM(z- zjJ$!DTHydxyysiEJqNs)<>DQEbelYWQ&AS+#fTK%;#-kS$G%7KDUmn?QDy>fQn&Ih zr=6?d^$DT9r_9yi4ckfiz*gg8Tv-U`pk&jGv` z5XAf8y9K+pd{K44i#g(4a<>h&n80OzZ2&K3iK=q&YF~^<1iTm&!+Z5inM+o&9y_7) zVw8?ob95c^IO7m*=88RdXH;z4P+Cjf4)9`@i+7&cDaEJsq)5Pv5h=XY0!(Eim%qYC z!r>4^nF+kcwl$PjZ|2~yrrFVNvVPQz={&|JM~QEz-#2|cUFd$adZ?VZ>^4B*8q zAFuI)$O6EN0YSX8(hst2Tg)g1yqFWk+r+IeQ>*gw9e@|JL{&L>-)*QF0(dbfhWEhA zhnjmM3Qq!FjMDM0uW7{APi#8Uum$tC4OjXv3In`2ITvr_NMG`s_B&DAb}m+t*TR*(06 z|I^yS6U~PMUYwVY_r$)@^8qgg1o7J5oTS)(Jp(VB!yIugaoZ4OUWPT_Wnv6f#jH5q z)QNNPsxl0U;jP)Wt)|b}lh*(*M(KFlmNsD(Ys2EC&WhN!VZ){TJJ5M?axUHvfoqjJ zpOqvhc-c`FOdtS%PDr)16 zlklSfJ*&sdn4Z_N?8aSy7qfi4gZ;|I0$vOV;{AH(8ryiA176RIIZ?b#+!7eeyYYPi zFJ_6VayqZ;uD*Ss^I}j8Z{zIzi!(lN#!DhGO2>PA$QIUbTnoIj5CQh1x4pUn(El=j)MG81?ge{8NSr@n~KZFuKcbEOV%Bn@w~ z8fNO}Bfas~cY0Qj*U0~@c1*wN_^dL_^6_4GcYY3dF(8Qdz|hh1-7~YA^mTS(1#pAUN7^UM4$turOe&49SVGHKt zUH@u5XQxFT^ZSRnE2{@KA@{(0MT^hWFroH%*_&+9uF>F-pgKWXgPY z-~RQ3051+eESQg1H9cYjbY9GI@m_FWrfmAB@fpC25h=V2avCu^bG~~5UL1lbGl4g2 z(h|i``xCoisj6yQ*6HvT)9^++n5%o;wXX0FSv}qohYQ+EU6h{Cd2wDoUMrWjO8_qh z1o4hZ4OHApa#<#IkV2i;I%5LcJ-ZsdPzC2Cs>;FZ_aUP!;KiUA-U)p}G_6M^tOmRo zrQ>z#HkJL<%M@S2fdf$SW~Uav1-zK$;+^u)T)w{F!7+drBT{%B0%c6xJ>Ok`H>MG3 zkSH^OcixC{%JOUSAHcc2t+3pn!yB@j@`25@gSmR`@Ac3AA*;t5cU7z1Fer2j;Kh0Q zct@QdejD&&KoGC_%y05F2kv~6I!GbB7qZ*3lU$s)LRE22qN*Ic#Z3?Y2D}&)!~1gk zXidS6<@nZjjMDMu#hhdEta~{bwqSneoxL#m3*g1cxp?`29aUtH*0(l&;n6 zEWHAFG0VsM_rs4%fENS8c%M9%?|m~4e@Vd{(TH%{a3Q-7dv@jvHB=R|L{&L>f0eU2 z2Y4|khWC)sAN4}@I76A}Sv}qw zaksVSEZ-~yyqM+VjsN)aDB#6_Al@EN>&YAS8*o7CAcZ=wqhl&_a>mbWs4C7Wj<EnF+j;r*2cuIJj2RN;PvwPqHO!;D1J6goV0(N4zK?n%AVKser5HI{oi`P z-#9(1$LkUNSleiOjj4bavwXbwq9z6aUJMB0J=?}c9yL1v?-IovaV~M&(DFhqv(#bZ zBd987#qqW({Ztq5Vo(h4O~*T$;~g3`0le0W$P+@x`~6{kHf!7<{3L<{5DVtx-IBc# zzvsm)7w>4NuZkn%4%P>}7?HvoW_eJy>&=qeP-Yy0C^LcgaDcn=aOi+u0PxY!HW50! zJ85_WI#pEPwa>-}?a{M(yd^O?+Fs|jIRakH^6@^jowEh-Vn7h@&nYHK_UuS}0ygG| zbBTCE8#iF{vM+l>RWVCcm9yuq@!|r$^&Nv^c&jaXsBv_uv>EVXl#W;PE=Km{QJW;G zGb*;{JrTX+BYsl*5LT8TZWaHz&m(yO_z?-LN~!u zt9LuGQ-?Q!hIc@cvATKLE%-hQdRC7&*yXGCyw~$Yz>8Tv-cctiX9Hdg2;yyU_lx{$ zmCm>?!kj4HJ)42t1hccrD~gLj)3fES~5ylF>0*aiIt zT$ehdVtA`B>9Ys$;^bVsg{gg%Sy>Ao0bYzq;qA2Nq3q>Pzv+M%hak#K;JtRr&&AJZ z3*N4mKi+eX4sQkxZ@_tD^-d4j94He#tH`&*k;b;BsYi&;M28L>|W0bUFU;`RQq zKylDw2ws4JIZ?cBq0QK7q<#gWM>W%REyciV2yE6NbX1DXhR)80ybiC0^ z>$79+JIs|jD`I%Peoo&DcyV$r-qx00ia8hSTLWHH$&$CH6B zwkF4hz*0LiRrl)f7Siy#zA2|J+4c;(Ha)Ayo6@0d%IlbO=KwEe`FLxe>3jn4Vn7h@ z+a7-M!xiTolUktAw+%nm)n)zSR$Ydw;+*1mE5xRnKl0tJ8t~%eT)b1OU1O_X98wSPVnhmW(6sKddsnVhFs#f3-bsP6 z$|If2cY~!4ICwEyhj)D>hUr?%ccZ$ds7YYVwR8B&A+f4 z;KhI-Ue;Nom>zx?zsSa%Xy>)gc)(bH8;vi;#jH5qsAtZ-0WSu{@IFcTq#0{JIRrW{ zM(KDXQ$NbArfIOH-~hye`FPJi+c5y}VwQ`yy~9x^G&DU1@M1&?uT!0svWJeXS^{1i zf+#bAx7^%HF3(eq@B>>nJEwy>yfHMq5p~L_``HCr173PokN16lla%Im_I7|5vwXa> zCfYNA7XyNL^KL(tkL|n^FNwq)aW3%#Ti2Km%w79&Nl;bH5>@4F8*X?hRsmiNisAj} z#A=Rzh(8T@F-phlKW{Jlban%LN+b?IESQhC^8Ok#0WW5`c(t1Oiqw)oe3cbOr0_oN z7bJUX8&w_3yx);DNR*kt``}S6m*H^(@Uv+n^SDDgyq9Ts->)rIB^2Ha1HAOC90D=&udKaWDC594d*1P%E23J zQML!*#h@5opTk`>Ra?)F2D})h<6YMxh`n=u6+Yhz2cY70Z8jVqI)Yg)-o|6h6vLVw z#m}^lEmC}o7e4^JnC0U=U~)7c@M1s^@3cSOY{{c~MSvG`#JR-IYn?He88=gj_po7> zs455VlFd7w0$vP?;T=ABgr?>1&$fUUqjbEF)(n*AGIMMUTQI-#{`Z2iPtbXBaxUJB z%aP9_@^5CG4sR(9Z^We^ zs?8k_;AbIvR*$!thh<98pxVCxZ?eTRVqQMpo+(3j16~XW;{DibF`F`B_i{Lwm=ne8 z=U%{U)@txO9Ly3`<={2jVTOBN42t3POk1vbb7n>n;Ke8%uY;4hyqB_7Q^OX_$7?s? zjy2%L$+>t3Y^Lq&`hXXQAj(YOoxLwvDIeW#HZ1jUo5d$| zc*CP8AJ}R%C{=YaJBSzG(X)EI3A?MMl&$n>C*Z{_A8-EF%aJi z)B=UJ4W31RnQ9ALq(W73PNJ$DytT&P&_d_Mpcr1CCzmz0rS>%eFGlHjRfnsxTZc}G zHEh9rykGlGz6^MAaxPx&R+jm)Wm7M}ixDZjwW_Dd%q^+~8dhck?_W(r<$=9_-@{V( zzO#INywNsi7PAvhvnC0V5QUu2VUJMB0^$M>ne>eSc zKdA)@;mthrj_G4>7XVeoImPi>Zyxdm@M2I5uVYbwrgZ#{!GIT|bi6JTquAI8tV<^6; z0S6!!%*Wf)-t{)%#Vi-^=XT8%ZFe`s*SBIs3hzm^lg#K{!y?1VOyG4f{ieL?aitCb z^sLz~QHS?E4e!n3Le;$C%IJT{>hVSwHcS~ir%`R_yf`l(Z=;7V{y^u&fFR!1YXjv| z3r<@}9i&j_y^vkR7_W)14OPWC#qqYBawP)rVo(fkxjNG|!`nI@1-uxg+lBdrR;eVcE4A3%Cf=hdFfd_UYmgCDfy$vo(8;_<>OTb%RU2M3<%<2(PJc7D2H?e@7~Y%Br)XyWZPEwu zVw8@zWV2FUu7xH3SAzo(3+ChfajI@l=)9Qa;yu)-vBF|*;1j@$5h=W9PBF4a?}Azw zR%QZky+fy!CE2GA!QZJ|&R)>rji%u(asQ}l8L=Jju%T!5cyCr|o{}+W@om71Sw7xd zt?Z@%UJMB0U43k*qTCcq{Ol5I`pcvj$bCzhL zj|5Esycnh9ZCSMzTk76qveX&X{a3@syJC~`HNcCLbMc;&e^rdg=~@VQF(QR`+UZJ6 zr3-Hs8&+llZ?CJ~E*oth;|n6S?JjF{cr`S>M41V^@#CK=CbVf13`-rpUX`N5`;3Oy)$OCIXv@Uu|B%(=P3ho};%YZ@ zH{iv2Ie7h#blVv;Wgv833<%;KADYX)7&|mk>L7*i#;it+^YPXhx#~T1UYwkZxBoK_#fCp) zO#m-Or11Xo9M9}dely9iG81@97r86ztUHF+Cq#Yim!`uTwvY0G&F1JERafQlWGE9o ztH*0Pv}wwwcRM1X^J12dH~UhB?|>Hrf_OX0_sbiZbjIiNVor3=8?n7H>z%~n_q>=D z$NSj%HNJ-pgJO8QOkS^<{I+Za;Ke8%uhEVs@+-ERn@OD&u|03f{)S5dFHX+Id&+jH zJji674Dez^3a@og8K$DeEPRGH4ndTe!25Aaq%z$8m=i2@c=65aI=siF@Wyl=H}xN~ zfH(X0(0hOv=jG!)ZSuG*;KhI--f)L|@+tM(;>H|vqIex0P1&*sEHj}cV3w#Vr}M6N z+c_3GF9yZ%?)kf4(`#*KFTjgYI^JQ55axhtG9z_X#PGIV|KJGV#mTvN1G}WLkq-~I z1H2fK!W%u{olLE~W@lKL3A{TLCzamAp5hlP2S;tZsl%I2!yB;gohtom)HNs*J*&rC z5@VNAJF#X4;KeK-Z?zSb!vSx$4|$-1cuzlRC!c=i240(uIZ?bW)*G3pE8Z-Es$y0g z@949;n*&}9is9Xm{zG#uuN2>aiBURUqZ19g{;bdpFLK2Jhz0Yv4fb79b^~6_a`6r- ze^l1wu@Qb%h7l>eeT{d^K6`w`cMszbM41V^!BC4>qHxcPQ3<^MAzdsdHXj2m1qUD& z%*T7fZfX$V#Vi-^$gz=%E6baWgU*W)DZEiDQe|2Br-GqJ;1EQa3A}cHhA3Al3tzxe zy=&Rs*Wq0iP1*B4N_nS>`4PD8AF_J99u|#L;&T^n0K7OaAMdSW9d<(J#eg8*79&&G z*K3}PmO4nG4{WQPYcnm%9nOQQ;+#ZPIe2Z3#~%Q^7!<>sIIc)@_wGmhg$<*0yqfOq znB-1>@jD#h~|KG5Nfq~Ud({9ZM*?XnDTLC@;(E*jJ@rF_Ode3cbu`FI;&I(rK6Vn7h@ z?q`Ye*`wa#<*k?_&Lwu$xkezpwkc`-`I z8#wPX^T%@CDXFs}w&%TXzi=|(#mTvNE17Oo{O-IPA1;j%DZCp-ddW&7zLhbo%miMm zCtZ{#4)yR?vU}_6Ki1(*qTyY%>YeIG-)HThO!TZCZ`Mz{luMf`<2`Jc<>T%8YH1PR z#eg8*SHY*5F%|l;QU@v2c|D7s%L@8?;)C{ZPI0^%i3AAM~dN7&7J{X3<%==P@}8D%YPx>fQdQcTw>?7&In>wIX$@nEdjGcRXN)Rt!29a zz>7gKypc~MG`W^`-vKX1>3GWyNM%izo?HrltvCR&U_RcWD;BBHc`?hy`~BE7SQ_qh&lF%9pcLHVjvHr@gMkk#Y8 zx!xhA@P`WTVZ(X(c$>8Bv;pv9KoIY}rM`-DKLh1b2PxEftuvM|Q(bD~J#09qINoVy zEoTB=42t26T9Kof^UL8P;Ke8%@AP&(jvB z4{R8b!kbqxuxqDTEsOx~iMFIcqRa%|TR-0@XKSD1H%T>rZ+of38?vABf$jZ*cdF{| zhYbW5^sFAQM{wtqA(2*Pq4Q#vk9X>uU55cL1_bfGi><8ipX`D6_G6AXm)LnTl-roc zwKDLMNX!yd<#b+)&h3K%F9yZ%j;`}cQ@QFGd~r5L>3GAwnz7bXE32f=irAjFYMbpB zp!4G7T)cTJIw+o8(1gOa0V7g)+ci8Uv%eru2fR20QDy?K`wL^2Kkpkogr%+wuaT|8 zdxVCUIhm_EEI*A;iKJ)sc;nV|Nx5BjSVh2#Sw7yZpgju!F9rnhY8TCrU+F&nzSIJR zI&Z}GU}nJxs~S*MoRg?32XE=5?YV##gJO8=g?+pjwM;$$Ixj})c)vHdl^^|K@zSsb z^S2G3#!mYHcyV$r-n)f<%KxG4&f{Wg|Nns}sZ_FuEZLQvtj(O6Ihm|Cku|b~?6PDn z6h+qTOR_{rkt{7_nM|@~&26W$v|7`G@VmdCc|7KKz0Pu-;s4ilo$Gy`yrGnX?TlO@6^XSSm4!$ z^sF9l$cir7ZePM`0bb1V@zy`J^fchbfFR!dndMZ)Hw*trEl>z=vp)6;N2kSQfEVW^ zs>;DT_~(6Jz>7gKyryS6X-W!r4gtIvrQ_|A)Lxk~;Zt|R7R<*xDd$@`z>AY}@y>e` zr!*_7lLL4$B8B(lyNU9M^I7SJm6^cX>3SerE+%sqEOlSHQML~6TN>WXy!YxIS6YAk zi>w~6#pABp@R!cx0WZ$W$J@rYLVduC0YSWPj1MZ#FMNX!9l@OFwqZ-tWae`IEUYSK z#qqkeeBlmwF(`)j>-_VYt=4Pm0$z;L@wUI#L9y-A54?LA2Ot*A$J^!Re=oB#(*29w zzpzI|%yRMe``lUe`_`>GfEOcDc>6W}BCoQr-*&)@Ll9*q@U~mx%GP>Ndl~>#$=2oS z@cJL2?0MZr722`7Y(cVcTBMeu#I zEru%nPFun@LnzJ%LXjF{sWeJ zIYm*R!y87!n;Dg-HrLvl|3y}hH{?ne?UM!D7Xe+a8&+ll@0zA2?Dvv1yit1T z(=Q)&coS)OL+@v+N4B!VpNF$@X<0p9hk8!hv$eer0bb1V@iKk)*#TY*2;%MV(n1;6 zfBpnGmzX2|7yV!N^qM<M(KEGKYhe_W-h_YrEmaZ!F;?8l9$y6yqM+Uy}Hd-)%c-(W5A0MDZDLJ_vN8W zj^!IxW&-aoqZ6u-TS<5gl2>8e7aiVo8eXIJIqIpe8|8xwdRC8j&Qh7y@5(l3z>8Tv zUTe?ga{(^~1o3XFw@bM+Q@cUxAcZ>bK(jQaZ1(>7P*t2$9B<3zlaE2?#h@78?jeDi zjK}5h22707@ouyEqwp?mdBv~=^YMnb`r)nbI5`*ZODk*DsFz!x0A7qp;mtWaME-f= zC*1Sm5JZ^?y!%c(Wv|}lT+iFdalkhn-p@3=i667oH8<6(2xX#Y^>{6YchipZJ5&zv zVwR6L z;eB%Df@Ws7Tm1kpM(KFXGmbH(+H1HG!~v*ymsYab2zW8e#oPM1rE>0!`?zhuh!o!6 z`Rf_ujqC9l-Z%tNW&*GO;I^#i-E90{wSvp@?>fAZG`xxN+3F6(=275+p4H=Z2vcZ{ zH>Kgl=$Pf;{qK6-x06AY}@qTYzq_{Wq z>qqFk7?Hxe=3@XOtJ!@elzHk<(jZZ00`Km6vFx!8K6r7>AN&1fI=m@TcprutCqtR& zS-?BaqRSoVyqM+VUHi=YHsHm8Al_dmTPa;W%kg(lXz?A;C}J{cW{Aj(YOeX@{YWw9sm;+mv@0e^IOGoUPV zWuj*R?{JSH0{|~(`FP#D`#uA_7!bs}ctvOBf+MrmNFAh5=k>d4sZi|tu?z6xoJ3VQ zc#l2!fiDrnpcvk{$8t4aoKo>e3XIb6HVo^-)V&pk@2kZDh`&}o-kk-Db^uiSccj%(|2A8CGTjZ|#(!s+AKKrop+j+VHU4s)|q9D*k0sc%zHf z;w?nkHfAv&t|ah<8kbU?uDJ_JGs^h46ZL?P8APbsGRx#W}_C zK5jJrI_!BdD27*lDp4~#%G($^FGlHj6UPiv9KBH=FPFjrsCc_w_NoPVG0Vl9)wiCC zEqIR?qhmx0@0C(p`NSH#uNYQl0&nh_W2#pEApsNPz5lfXK8pNR3++4 z2UgvKGSRboybdq^dl+FgTL-|4Sq|R+E=K=3=}ZdX#eg8*v_H{`?ybw?S7n$Z8WHY! z!>u!zht4MWxF^gKRpo3OY*hYuNhAiv@OE{M(KOn-xf9^UC>^inLsfagKJRd;vm&LvOgtVB3H}F}xwG$|uL!s~!PfjMDKMMOruo z9RHkc*n;_;w@LZlD!_}AbMbcU@ov?edpO(*Z4J$K&_vpecsxB_^ z?_sHJsy4FH;Vq!yb<=!P-#%X<@Gr7@yuHI^TH~Rdx4z@Ne7t`K2Ui2U7!bs3x%41& zY3eAvJsNYOoj315M`r4uA?8q3%!=dP;6I@i;KiUA-co<#_0>l!>0z;|*CM(`LSOXbPPdvwXa=_NUqbUJMB0 zt()npwC-@Ot<*sZb>8~vyXBA1%qRrBI44n6PUlTH{AMuV#h@5ohj620$1xA^-NP8A z<2Bmp%q*%u8*dT70f@g=e&_X>HxqAt$1E4Ge_SPYg2&W!<+bTk-Gf91$e0}J*&s7jgxDuwAy$d@M4yacc^jm z&wv*Lf_N*WW-&609DJY}=7@8Nd*0C9$K;j)qwu|=m=(vn;z)0Np$Z1Y@NNw@PCn-p zHxN26M(KDpt5?hYhAnl2zg8T8STG;&8OJ^u(0MV-#XF_W8f8?ai30#HMx^krblENI z+tdp`THp{wnF+iHTu-t+4o7x{r5+uYQ(cEwL&NKq^HqKJYQmtu$m;PvexuZeG}~wi zcyV4nUdI;u@BbK(niI?8J)T*UfCI8=fwf2cpvPWh#xD(*Th!o!M zC%VZll<$YvKUJJe8YIe0;63}k7Mo)ij9+P2T{hQ7hxY{yZ)iZFx@Eb`!@&hTtHN7jIFcRnEId zcWwuGF(QTc%2!RdHU7y93@bB%_nqZK_Munbwq@vHm!x zINtrnK}pbgF(`)Dtk+x3^7bF_L3lRXsh;^bVs^X%rb zlj_y50=yWJ!uxx51$l=LVI_bUhak#K;N4w3guRol#YYi0UK?Cjhj&{Pa&}053+Q@OHRw!<-&`Km~Yl2%^jc-q#gZvB9yP_)U_$Z?y(G zysbzfSS~5i;?J7f6aZaMD9K0_kESds%F(`(&%Dxg!cAMR;053-AcvU?w%g>lPq!_kf zKHen?br|5q$+>tpwC=1_b`Em|ycm(f`>l2Wv-9^hf5Xa5;Jwt>n2oKMi9b@b^xV}@ zhxaxOZ^5}jwacQh___yrR*%>5Oh@hD740`c=fx}^uf?x@_-z9Q1o6&XZLZi5_!#kG zj%Y;Kd5w&A$v=L}z#rW)D~{K5NNEw^#h@78^52b|Jwf!n$Pz>*aIlnYF{I{P2 zycnh9HJ@{gc{XKVE5jDd$2-Y;`8MdhI5`*Z{9m(Fb?y900WU_R@Twwb$>&=x^DwN; z1YYB>UhH5GBLVS z=lr`D@M4sXcXoecMXPH+UrU`)-Crvo?}6`^VgN5r&c*9>`4Thl=80&)ixDZj&mGca z9rLbc7*=Ki??rYbJ1y`c{wH(P<{x_<-UBqe1y4)VJ1%@V31y;Z^?2tj?V!C|mX1$} z#4I0g+sN820WSsw@pjc5Rvy~)YKzoC3UyvtWG&|FwsU8psyL@O-fx{+y8>Peis4oD z_@;@t@x%%6Vw8@z_P0;Wsa_BA3|lZCuU&FzBfyK3bMbx~yX<13_mpFR7b8-5qYm7Y zDXi|@G_1@7UWa|=>@3e1{E63PKv_#2-U~Fm5wpwG6WY11fHKjudb}Yk+GwqpuKfes z2F&vDj#&2G2k>G*5U12{T8@KVN!R3{}OfINqiOuhIZ72F38U zUTK_MtBsu_;Ke8%uPULd{PgF+J*CcySm)i?KK3o(#mTvNR}5UO3M}|{FyO_A6kg-o zzh%x*?gfUGnZSGhccALp<^uf2;QGNWZFG2_(D3#S_@%Crb^(8+pl9`X?Oa-EZ+T3@ z&Wl+--s~gU;{Y!P1o4K<*eXxiB=>=Hi8)ccUS6wY$7YT12UW$aI9{`Jwbub&42t1( zS#FYiZN_DM113i4c#Sd?=iEZO9yV;j{LcGi^n-?g7boZ9weV=|Y-a6o4)9_`3UBU~ z6sMG|u*Zg#nZR4URXp40c+^{1>h7^M+w1Utqv16&|DzreToJGHrf2ndYs5Hc&EX4fYUsQemB1T1NcKL+x3ggj=Hs2C8Sf8xadIx+IV10}Ms@1qJ!}|}!aFT) zxNPu@Rrpjb9D*n_ftNYLvI*0#-G`-Kjo;Q$hj-I)$_KXp!<#(vC|>qV&jQ|%NS7Xf z7qfi4>yNtq0=yUy#A|IePuY5ISA13(=0rQMbNw9VYo+tw0WW5Ws&c+aup5_DdS zNa0a4?iTng_?)1UZMb$S-?I-YA}gLq+H zKHg628Vy3c5D>)s=)R5e)3^I2_}2+J;#}gl4PIV7ncp`X;8Txrf#P^?kBjJscwtg8 zyuMv-YxW+U-vjYNl#X}3&jE$&h`OA=Rv3U-Fdy$X#i4w}3t28+f6JdtjrGxM5idlf z@LqZ7AaC=09)8>4aE~-dl$pT$iS4IqmvbQ=&h0t#;I2Bn*J*e|ewe!K=$Mo97g;^t zOsD4BN>h4u0K7OaA8&C+Y!kqX0YSW$Q|*=8Z_g<&b&x{ahS1$R8K=>C_#7gflc*}E z^L8%lf*;s0D2BI1N}|T?y(|atVw8^8NIOFjHFeA%!xqfPJHYDm0KkirbMZd8VXexT zaqS}D#fTJM_ms-=*Ebs7htBI@OBy7~OyJ!(X^yJL-KI)dYF#@kCmr6mG`tZRW-b-3 zt1kUTR*#pt*;G4g&dgH4i}UjF2EYH(5b$C^5byo%g-jctYQv-sQV6fv{8IVBUEltN zs^XkPRXKQf@4spbofm^*cwcubm%MAT#Z|zIQ952#crCe)@3jGjEtrqDAY} z@fM$NtgzVdbur+@h!oyisqXSQcW<~FR%Qb4xo59b2_+-(=i%rR8|6B@{wHXAUJo;u zqM42HL3{M99&hIPCfY>~EgJ$}%<}O@er_)ZyciI~d%5ij=53J20yvkLBmNh~ZNoq_ z7x~9e>3EGa56@*fj>i8FaR6e$e7x!B zJl_Fc%yRMW>=LT7oR*pecrhY{*TZYJtVi@#AH&K_;O$#v&n~v}t^?<`P1Slz9o{e+ z-Z_WOTwd2OS@aiKJzj?wjkN>haW4Tc&dbL;_qoqDz>5Jvy!&EiDQit@fZGPl5$6)| zeyKTDo%#Cu?=huop0 za|Nk`6xucz8C8+LTWy0kSK*vQRXN*+VU;UKLFdJw7+%G6ljO^-pZNh^jMDKMsrqzN zG+iSzY{C4_>sruvD&WP*xp*t>Hc=i7>bM>{FGi&B8cj5l9ais30K7N^QDy?KNvmya z|4HkUV5!ZoPEqUdrql5Hj;rVr(0w63fRUcnZW}Ns+IhXaswrL+jxP^Y#Vk=(4&I-i?eVSe7!<>s_$)zlZAbrNz>85j z-c774Gqhyxd8soh)_Kk5Uct8k;p9BLC7#L?cRp1Eycm(fd;CYCyyCsg_J)<2z&kAS zCObazR3ljG=bSFRba+40@VYg%aEaU(g7>h|vwFOl=WVrFb{Dz>Ud;0G2D|@!3V1Of zi1$s_fy#4Mxn+2U0gJO8M?7ym6ae7h-;2rXv zJRx+vwXbYdtZp`_0W25?ApTnUop)H;l?~8&G0Vm4RAsJmN9u=7fEOcDcpc+{WU~U- zEeE_f1W{%JuhVuPw)*<#XJM)7H$U~!;awj?`M~D*$--s#7Qe@Tk=5f(+*ezByv4%L zfEVZGKk@-kK2?rYHis)|{ns+`Vi+;i_O zz>7gKyqZqeG?NO}%+4=JgG8ALyhFz1upI}?#|P~#FyHx)4sRq4Z}B$^moMXY;e)B^ zSv_7OquScrU)mo7yqM+VeSg(#JK)8DAYM1GXw{wOgYfrn%!%TypKhwiO11Qcs$!O? zDhKcDvPG$Y7lUGWud^D>j_eJ!053-Ac!zYUspwqK1)n~L0}u=5ciwa5zw`jSnC0SK z@VQhKr7`jVycm(f`zGPEeEj!ok%pC-!22e=lJn*vgYjvuQ)0Th>hPw}@J1w>xg?ms zzHCYM9JnC0WWvE=?+z>5Jvyf_ zJbqP%S#i9}_@uuPA`FKY> z?pq3YadIx+K(iRtp-!pG0WU_R@b2$jOFr;q-HV2mnZO&Cx`FLBxgkE2qjrr^!*zIf zouqwWGqZ3RcWM1EC=)%a$E%I2sx4pP@lwExSq|R+o)Q^9@nRw1#eg8*r-_@DTSxqR zLFyodI2DZBx(TjfEo#^Nt*I0R8<0`It9_H4_& zEAd0uyz3Q4>hPYW;SKV(aA};o5%Vn7hDvZIwM$#1lg)Ikb$ULzwbMf}102ch%goJ3VQcncrAj)2aKK{32__6KQd zyRK~scri-H>lSlR;pu*@jbRJs zEW^r7;N50x>%6c-^mJJ2*|2rvb$EkgDSO@;T`XOS^9%5oS9(^D_wk!5+Ebdh_#QUQ z^6~aEsj(LDVn7&gwMk0H>zw=ZF(-;Q??64pn8j`#psJV^$EzN*Neg%}D28{yh#<{E zc^E!i8l!Z)_1@bnMt5AtxTEAC0-|plMofjigcmunI$e%xE z@g{8?f+#bAci+Ls?C;T**I}ur52_~W@J3MauCR1@(CR1tcty|Z@p>Jprmf_d^d34d zX8CxFqYLW+UJMB0oz?8SV%m;Zc2Wxz+BT%!zQ7C~JL@Un#W{(pa<&ZtNj8pv7lUGW z+jsp(b836i4%jwel#X}ynhb?ow><|8TQGmyu(I+D+&19kT)Z`p1*^KA^tT1P7?Hv| zUXdnWR(55kVPz)p)*RW9?QwPaAy{f)(;P1yUJVVe*E0(jXU25oUu5-oA2+eo=CRvS z0WZ$W!TaC04V~*Wi3PkE5XAdE)>D-c*avTM#++#9^}E_qamsdYYp5z_#qk>TH`)w% zF(`)j-p4zdPrZ{~173{M@fvx4malL>Y2bqScw6@TRu?)iPR_*}oovg7S$#sh7?H&L zPba4G@#)VDD>H$&hcb!nyWglB0DR-*J5`7G1r2YEnVHMKp?iP+MOKg3NM)nVc5uSy z^WwZ5y#IY*OX;&+4R|pih`0MoOJ#HWYdsDcqG zyg$P7}N< z)Y2B@_R&J;#VjAM_fylFfENRTcqhjUQI-9B!cA&{LfeK}&;6OCqrbZV-bKyH;t*Bk zY#Z7g%_;`G7!<>MC*N7qz5BAKfES~5yhBb#C|+C5#s%X5#9u4F^O~l1=?Qo-%f*}j zx))oRu(uGl4H%KaTXgq^?6qYM-Uft25M?It`X=}|=T6>R4bJVl78_>i@NPRr`M{RB z#MC8t+@GU=k=5g!v$VRlD+p@g@~iO$WRf5X9@g?}y^q_0ITRAm)g3`9FYO zbH`8cnd&{OW^Abiv+(WPM}QZzL{&L>7u+2&1Mp%{4Daqi8JfJWKjHu{M(KFjam|&= zVyhylvm(}cEmp3=cMs#_T)eZ+WGN=OhkF5Dj7Z`2s&htGx$@zqhLxGX+pdxaJIK8h zpN14!q3#?V-dGx5W|*l6XG%oVS`r{cB&=M=|#?9JLbfER;ecxRTCXkOKs{21_Jl#bUwz7w&G4=77?HwTZf*cGu`%rmsLC@;(+67r@>we$46Yye|kGJiqdBK1e z1A=%rxmQyTI9|1~)Ikd29pQJF$=c9O3oQZXB&y2kyx)!8wgX-aisAj|XSl|CNB9ZA zi%~k>;~%Rl-W=@G+pq=m@!nq>lnQupaxUIrk8H)v)mITOMx^lms2C+*5!(W{4LAf* zW&-b$*KTZ?@;!cs?|aIAfevpD4ey+q<}N+vzQcF8(X)EI7LP5oOG~`B0bb1V@n&xt znhAI@Ac!|R&s$}EzBPWGf;plQ;kLo=s-t2{;|use0n8Fr<>0mYv2`Bc#h@78lyBjh z0W)3u0bY#K@otKVWKJ{~j33x=0Aj&>yfId8tpG1(xp;5?E>Ud^$>;{#28>AI9e7B| zocMJWpH=ocnKVe0nZVn2ik7We_1_locUpbI!9_Z}fu|{ZUTqz7mxvC_J^muA$6HX< zTpK*+#T>wk^YZZyP1*Ad@M1s^?L zH`g2hyciV2TY1AX&7|{}@o`TWrQ>a%9?T@TSVSAPU_M@_qJW)%7boZ9ofUMHt!NoG zAMj#C3a_W>IC+K1FYg*wW&&@eseRcNJ$_rjQqLzf@YUfxK*KwyzL`tVv&v?Fk=5g6 zZklV8TC7X~yf`l(Z-UL4c)*JRLA+1qCexylj zz>5(ny#2Su%BznG+hbUn3A|N)rLlpt9}I-0nr_~`REPHh4R2xt3m4CbH2gZ8p4H6u+H{w`V@#Lq~7`>b9Y&{8cr;i&-w-lMg$w70yh+ zN1S3r3U7$pRr!PF7Wi0y9D*n_f!F=P5VqdxW1ZmKHfY)1Ux)Vz6>nP$mwT%5c;zTP ztH$b^tH*2PZ=&6PdJKNsfLT6X&$XW_16~XW;=PhPMK!H?_H#N@BU8KXJ`q2-Q`keS&$CzrZbce zY&G^(blH696h117p4H>+J>EpSu)PERNP$^C-r?mK6TpiBLA;epE2(^M-p5PdFh`tA z?7WdHUocY>-#>?{Vpbe)zRT_j(0MT^hS$gU?tgEH$&omX47_qQ66u+*4Y zM!`C~$EkRYOFc8UW`cLo!_snd|6W!-Uft25M?ItHkF67FOQf9!%}yo ztXQkVd!2?iGp2&el#5~bLnJ+`$6Fj(QCpbttpVW0EFbUjoGJJ=APflNt=6uUa`Ee> zqofungm<9XMaF$`Tm1hF=On7i+4JtKv8guT#h@78#M8Spg{x|o0$z;L@!qrTt{k7S z0^ehR15i8f;$PbPfETk|yrVD2C^hqveE}~K?>mww@zms{;XC8+XkGIs454q|FQ9X051l`@Xqf0T$A_nM{U51 zQ99mPHC>gRXV=76S>XUwyerqlI{{wIa`6r{S;1C)u2=(|7b8-5vtrZbce8s`Fs#f3 z-e(;js($)r;`h9}ds=MK;SHnVEiN^2`QtcxBe{PSTWIZlr-uMu%<}OrYjpr` zeaC%W2Y7K_K3>;5 zu5+OCVn7hD(VRbu?S1#3kUB^qyk1`aGS`ofzz4_ToJ3VQoj1nc)ei7tPz-P1`P(&p zUPg2Pycnh9eR4chaq#F6{CWikpmyGUIgN4KfLShHryku^p^hbw053+Q@VX_asxGuWZ@} z@M4yax91XP{HhECf_VK$q^agxcFvSqpb*~q1D`Tu`Ybkrs^XkPRXKRwmp?TDyciV2 zYqICIX8G?EHh>qSbi4&4j1<1_58_XXH~kj7Z_N zA2VBi*Qc-2~i-yh)s#De+ThMc-hCjef|a`7@p&6LX~ zMn(W$j7Z^C4Z17ecG$g{VPz)pK3O`OO`Gu???bDj$=ajCyFQNcfvw>F4|PcE)A&K2 zp4H<``=^q2Z?@$sz>8TvUektFsel&)f_UAw$(7!nD&R#{m?O?5;*~|dWI_*C`2tnN ztT^7r?Qiu4yciV2tMYNuth$|m+Xjr%@wTkCRdMF!WgGZw#Q}%~^YP9IUp5x-VwQ{d z!--=m+who3z>5(nyosB4%RL*lJ!4pz3A|@3gsYB~uELk1OxUzzpAK&%4R6Tl617Rn z<(*I_dRC9ucUx8M<>UV5fETlTyeDV$Z3}oYAc!}q+$z=`0@-y&B(ui9--&Ch-33eU!~!qFxS5?e*iIa2?(h z8s0Q@k=nleS^TPup4H>6G0R%(b~I`d;KeK-Z`kJP*m*G^h_@&#OQk7kzFum9LVI2# zqi;;#%@7gKyfa4a(j;u`bOZ2Wl#VyAWk2Pd8DaRNJq|$p zwes=)bKnTR^&PWZybV~NZ}0~6WD#UETqV=G81@Dc-?0&oa{Un&h3## zzYpo~X3+5ZMii-^&i|AB7g;@C-x^i4%aYgG0$!Y#k9VqD!T{*J7!bt!P-&|&yV@Ra zro|j_F0u34j6KB6dQcAU$;PZW-j4x8I|E(}is4=8nx(1shOO7g^XI&Y zmpUtAows{!vzgF&adIx+g-H)pi?)~K0$z+r;dLH#Sw1L+!TVfs2%^jc-btR-oI_h& z#~%}qzYag5!&^qf`*>ZEx>5Zxu23d=R*yF*zoxd5^Ouc)7qbF*OoRCe{yH0%nP-aysww28FEvF9yZ%u37R*W7B8xbij*II^N(P zixppte2z+;6*0WOu5WDwcyV$r-UTNt73Igs@M3g~Na3BiW50aE%qaYM7>6LrOyE5* z!JZ8~W{gj^vf1A4m=5o*c*+MhyR>iWPRo-YLz(DVJ>JJ}YH7<`W_tl%%<}Qx+fW`K z_k;mKyyhFvDGv?^@sc`7p>0F`^pi~Ls)j27FV0C+m4kPRO1>EIVo(h4gR}o?p8U*v z0C+J<$2($)OtI=|iwlM=n7?gkKYW=F;Kj+gc=OHPtEL3}_y;;KMx^kzIMY#{S(J!h zmEjOXnF+ifXWV9Mm^{FnYfEmPkJjNmOT!y-vsisbdmDe9qi6Ma3#!^`Q@gF`4|p-l z$NOiO_h;z57!btU;Y~&5OXC`+;ap-)wDaa27{eTy9hd@mF-ugHgSWcfin)LngJO7% z=H1n7+b~%Tcri-HYx{Yp;#}XS?F?HmA8*a)7V&@=C+Fhb{=0=@^6*3WLKTci;mxyK zFWYicePv&a4(~lFyoG}l_^uLq7Vw(B+_V+&VwR8h zL9DSk;KhI--lW^FR87Zs!W-={CyLj(emlipUk7|v8D@#9a`3X59?bwR2F36OdH{B4zehrPLV}+crFMD$N7D`4319T)Z7k9F%d)r8MZg7?Hx8TVz1qWZiw-X{Z8rd7SQn4Nd2ikv_JI$l!>0z<8=tDr)_!u zVIttgEFZ6VrAluAF9rnhK5f}SIijOkb*Y0C+BR%ydX6#iH^Dbx;+#ZPIe6Pt9Hs`m z7!<=h;{EB%C5r+N0A7sJ@v3uHD^%_Q_&qNUK>W4xJ8yPr2fP6jvs}E>;-)AMFE_?J zDKH|1_vQtE`LFxQmVg(BAj(YOtrWRh6<1Xi3g=eyt;ty(-rxkvp4V$tnR?4F^W%S! z)#ELWtf$T1WIGJ-;=FvkcYE#G0eCSWh_`07gDTs$AMsZh%n|4Ee*pEruzg?KNb$0_ z#}ue4W{IkD@Gje~^#Z&Y6vJy)&{MPPgh@ldi%~k>!00=Q$QrjL&!|}E?KOA7R_MGq zITx?XqjDcXZ3isMRm0Uw!K&ncrnYz+sD+$0q|l#5O3$`CrXF<8Te)=%!%SPn}3Iy zX45|ks)|{0yf#_2(g809#qc_vyR3O>y*CH&Vw8^ewri|n-S0oYrOt{N-f5Lv4+Ok8 zIT!EZXgjvyKW*`$BN&mwYq}&swy@aWEEXz;d^Uv2%^jc-j7{-v7MBC@D{H-Gd3sb z@V=nob!h!gopW=|eJE3hrL?RbZ^8X$+JC3kSqOMB%g5WUV!KMvc`+b}_mO)!)z@P~ zK1m&<5Z>08QklHKUNrzO&Pi02gV!Od>;vG%pcvlur@S_ycnh9jaYh85#i{D z7ck=h#D6t>y!(uzh5%m7a`9GS%d5O{i>m`(j7Z`ASyUw3pFiK$urd>POU9gFJ3Ow8 z+lCSH{+D!kOKEsx{$#3?RMT?71wE_B`}mN(c1<%c-1B0VkJsI20OG}fAl@EZ4Pc9`imU)HMx^lem{(q&9J~>~PRAjLG81@9d*!h5s`gJ{ zsePwZPS)YwmPq-)<}f5v9ccA)$6sXicq3w)YK<Hb*!1g@8h#W zXzgqnR0+SUEv>&(tHT>h#jDOx+kEu+3}vEc^>~Bwn`n=j_Q(OenC0V*U)UxP@M1s^ zZ;K=Ql=E(M-zRmDLY?<{e04?gV5SaK73UPk`|N8vzBn6$Vt8ehf;I03e6$0+7^UMq ze zUb`Llyf_3=W&-c7owe9Y$EMG3Hgx2!V!(?L zDZKJ&wd66jQ$HD2W&&?i|7z^iwxM`c*};)LZt3s_o}=t}gATn>vx6e>OBs4rkJmT7 zv9|1ZKzqQ8Sw7zFJC~LLUJMB0Z5Gu_dHvD7{(u*A#JR-I8|buxx#l!#5>yql;&^M- zE-nvvF(`)jYU3i!&qpyE0WU`BcpKIm#dte?iZX1$e7wC!+I0oII5`(@j^i2StAI@Yi<6L?3y`_6{+7=q8y*6cr%ro(%HhSzt-TXp!g!Fa(IJ*&rS zceSCmaN!QTdl<8Pyz5GHz5!kg2;!Z}K32Z_b`$?=!JH`GaO?JpuZ7>gLsc;=j`v5G z9n}CY2F37ZKhD?qfB8HH@M4sX_qUUk^81B`n@X`mf+AxRCL7w6^U-QK--E5M5ZLA(iXw<&EKkHSmeFh`tA?7Yw87c&DU z?Y4%hVwR{XXWP)=KH$YD9j|@sFy`3Le)!W74nQoJk5@50 z=^%7o%yRL5ym?zWwet6OfEOcDc;n@pRP*t2$9B-o?O{@Sf2F36?E;*sOe6?{`z>85jUd`xUih4b7jWle*e7sS~ zFJA**oScjI$ivO5Im4IN0=yWJ!dp0exxCUZi?xQ8nZRrLF@-(e-ufOa^$=U}kq+-S z8eVPvJav~TCvkU0&;EbB&Fg6AOgw?tHei;Iw_4}Z!vQY_1o8fUF;w|_a|He`iaDYY zVduR%Jf2w`-`onSidk{IKZf+|2zW6lhWB>4gPP_wD|`mL7^UNV{iB}JZi+Qtae@O7 z3+CfpExWQ1@M4yWcQJEKQ7Avo{2uG@ZaPo-z!v&FUwtnx{3XDrXZ3g!_t|LMZ&@)9IxlAVcq=Z>UI=(GAc*%n z+ff-RTaFKx#vE}j5wDSv2NTvW>j>b*EKya?wju0F!(70NK{338D`aX8Y*fbrUX0T5 z)~Fw?II+zS?;gehhz0ZU4sP9ZI^e}D7w_PMmWq4E5$-NUkw*iMB z%1q$>*m50fb+jZF0B*LjdZxpBoQ5|jDPJ9J#^N>m^sF9lXdN5v+wryW0~==fcx&Bl zy#VlHKoIY9`%B9F5!Sn<7AUlB2y`-HysMdd174hys453 z{R`m5C>^hVTm`wul}X(UTQDE*%gE`c0549?#an4(Q)OI_=5+xtMx^jMbaItF`4fG> zurd>PYdNoH%UxTJFSxH8l=wo2_c{%)Lqvgk_^m(NpiK0v9&beZD%y9I+vE4VnC0VL zQ#u7duwg(D@8+o%N{85%c~S={gx9(LB}V2`2|otooZ@(2)y_Htcrhr3cT1o9ni<90 zega;MO5n}CdExepBXNc;n2&ee%?`r=FHX+I8(D1x`{U#K6u^rSDZD$D#L5dkHo^zc z;}Ard3A`@X+}LZf=VxK5>uu+~*5Q3i!y8j8Up>Gq0v{Dc&+73$o={yIGw90(*fwC6 zk9W}4K}pbgF(8Py?0045>guf`r4}fJH@5T#qv-T-8ngtQlc*}E^LD!O8z1YBK{32< z$KTc58+PR;;Ke8%?>)yhjQgZZ*m-dP>bBwW`auf-FJ`%Tx7{w!-X6K@0N}-l6y6r~ zBIR4dBJg3HI0R8<0~x{W;-bUBCE&i;88>S zk8SuLz>D+p@eWIK#cvxhAc%L~XA9Kc7n)tv{hpt@wR);r?hSx4FSM3_K zY5ZSg^>~XTYiPsg_(lU>oR^QcjpFWl=)4#Z#A{}DjR|j-j8`6EP89F_foAewGupR= zs$!O?DhF?k;71n$F9yZ%Hj=&6OlWpH7w}?~j@RVDQ$=JjvqtKyh~XU(Jlh*OFHX+I z>lfIGHC|I;5a7j#6y8B4HJ$pk%Jns@%mm){bDKN&{CH;xEVX&zpZ7Yvi8Q=Mns@3w z4;j3}hMv{qbxW+F^=@Z$3-Dr=kM~mHlgWS=1A=&W9`B@7Tf8)uTAUgzn67lUGW4?3i1Lf_m;0K6Eb;|;F1o+<8m86S&@0}y|${LXu#?Si?0 z7qeWvc3XW^*`3Pa2R4jI;XVFxp*+Sf3h$)AA&4>)c#UrzVVxs)4T5v~sFH844sSXQ zuU*`G_0$KU=l>$B$7`{(mUeKcawXu!dHHy+&Dv!KcrhS|_hDW$m4DMzTd9K-!uvel zovEC8xEJ8XIf<%rI&anQD<%P642t2sE3i}z>85j-igDjD}$Pj!A(96K*ekR zY8`&tfLSiyb6;(pZG%Q0h0co+DZJ%<3S}9qEt(ouW&-adi%sm}FIP^%xxM)+Ctrv6 zGYxN0^m}!Mb|Vx1BCE%n`J<+`<@SBffEVZG<83r$@&>?*0YSWz;@&EMENY;ZI!GbB zkt-va11maUOTanB@otau{{?t4D28{K`5BGXyH(`@FGlHjr(Nx?eBrGyaKZe}yMJzH ze2E}V&c%B%%2Ty@#QIRcixDZj35TNPO|^S30bU$}C^La~L9JV?rGJ|daBhRu!#?Wp zuD?L}z-G5SSN(3-t;2tj{r`BERM$>h?RFUO;=Fvku6ut)0A36T;$2y1rSe5*UbBg1gw`oEl;KiUAUhBqLnn9~#@%g+MrQ=mS9jMR*EeSVl z!TiqKKc)zdR zDSx@@(i^BM&MA(!!R>Mj0WSu{@MhdB()9CO=nS0~qjbFKDZ3Q!?zh$$wqQP9AM3Ap zCk0N<#XEb}diH7k+=hS`BT{%bXwN&<-Qs9xSeXgDeOzVinY@9x)Z-&!igb80Xn51k zepb)3?1%8Jr_!=|yl$nHwKXPLegM3f<>Rdz)^?NPU%!MVg7@xSQ* z{_EF2F-I2Jm6_IS2tGI#v*LJtGZxwdUJQ!it)cv>@jGLJ?_t9z9q)miLGpv+-5wgY zU_Rd1n+xTzZNSO7cysN2RMQK8Zw0&UL1lbGlADndrZ}LLkIk! z!T(>TREM{WhPU^cPwJX;9-V|T(X)EIzUkGq<$EoC0(ddY$Gh5pH$Ej21A=%bH7%4^ zZ`U

L7(WZ*1vJS>l)^{DlqYB&y2U^IET}j*ol7pcvjJ4kpRw@vVnI=fx-;uhER^ zNiSr-9vHS@KHg<);d8)?lXLMFxOu2%yn6o$@M1&?uiu&WvK=cnUj)2a?@5D1nF+j` zElO2g;_d{%Qq6DY|Ip#xb&>Lc%^~8G`juwN!oSGs@rLfMtX*pV?jGR9dHHx#qT}$Z zG7Jdfz2x0UweNW&{6va5(axJN^EGpA?V3QSDrSkQa`5i2TEQGTF9yZ%mflR(n9RvI z4R|q1$2;5AR1w~Q!N+3a0K|g%cwbHn_5!?^<>HN=5~Vzs9MuN!Vnhn>$Y05F+wh9# z4J$K&cfS8@w(!NncK~pp%ZXn)yk}{6i~YZ-S2nsH_!n6{UTs`;t@hj&e0?j<%g4LW z@3s+a8!#Y<_j_tIbL!TNEm8+5)Oo$UQsrZ1MffxfoKqa{_Mbi@051l`@S6TCpFB10 zU=P5HQ953uN$-<(Uzg$khd2Ng@6{|#O~8v;F5Vx`RaMh|)u{@2F(QSx-Jbw?&f;<@ zfER}#%1q#Ow_3^`*|BOcoZEZ#l}4*8K4q);-=pD;+4)J`wc6(Gf05PWb(~jKtGcu} zA3872%g1~EQOhcT7XyNLzsPDTPww`aC3TQOc;^ock&lhpk5`r9oJ3VQoptE>zQ;#((GHk*8&O5PeTzkNalXLNY-|wny-ROG~;Khg( z-r=jGW%=i);_F*+2%^jc-X9}tu{XL5>j6u(^-nR@;Vq!yWk!BcPdhZU*(rN%mlnRFCTCANLdl!#eg8*OO>jq^13Zal{!cvyjz-fRTKs!I6+ImIf<%r@V>43 zXb0fMpcvkVHYYUA6a0?>UX0T5HcjzRw7+PH50}OPsGT>!Zs&Eti&-w-YO80l{y$y2 z0$z+r;f*i5C=XIz8e&+P3A{(D_h#2EzBCfft!%k_1s&etOO!pY9rNM8J1LgqLr3UY zJzl$@irP&X-aP>?X8Cw$Ke6iqcrhS|cV07pX8dH&eo_k*!kf-+kk9OK6>qM>ImPjw za(aeWm0?f}@9$aPHR~2cyS1#%mm))yEd`jox9`zs{N-`GuPpbpy7>qT%f*CDH>mc zMbGN-#`Ln%&ii_}1>nUjAMclsxiW_9%D&ofm^*cq{c?r}<}!173`dQ954L%7=>Ht&C?IwqX9Y!SYpE zXTXb-bMa;lYsKbnm^c(VFGi&B26-3DWvRya_5>V)C^La~NY-dJu3!Emn?L6 zH8i{-SMt;qW9NB5ndn(PUf&@W+RM%7S^{3o^6?hGcR37rF(8Onw%``CIKu@5k9et;x2Jm7~46l9n63vQ4|3}byF-pff&^?n0@yVYfbyjr$ z)$sA|X>S|=cyV$r-rP_P;}m#x1K`Do6yAzf7i1sa7wtE!%mm({QnTGA zR?^{pLBs2nny+^19`5xQSv_963KrT1^IPBzm^d#Vug{sxYJe95f_PsgWXm_7nCLHc zkV4yrH?1x?HTc=8EmRff6vrF7X!L&6n ztE=Gmyf^@{U_Ra%wJJOXyqM+Uty*)CYG>>82Y?qNQh2*fsVGl>XVuuSG81@ymrX9?E82Ps)|{0yw~@=YzugQ?IEiwhBy30k;ZF{O)tQU zQ99m%f4VR~ueQ^|8N~sJ1@rONtlYH(@M4yWx7EWwsv8Zh@HQZfNa59vS$;n5)F*o= zGY&zNnZV0-tm1s?l5uR8alkOG`wkkdFl@7d;0uER*%=w(M;>mK|UAo;=Fvk z!Q1MD0A36T;(b48tn#Y=Hv9<@bHuqsyaUYwm@DRQ@rn`55>@4N-fNbt{{_4l6vO-W zXPD+gS%f*@#i#_{-A2l}-$Lf9L7l$CqOyHH(vT*+W`XcASAyc>4(&4>L!)w*m z+RSw73V1Qg#~ZP+@-V=Q0YSV2KAcv@2Cl{Lc`-+vOT_DUbvW~AUC0)wDrSkQa`3i) z7=ten#Gn{nk7XH}J)ZUE0A7sJ@jltJjyV*t5&v3o0Aj&>yx)o)UI1Rqa`9%JD$j16 zoiP{iVnhn>x`E?l?wkEj7*=Ki@2!~^*%!(bIRM<++S68tH;0C|AURh(=vMUYzsTzG z{@({S^Zh6Bt1_IIkGIyfhl>F(1_bfG?%zl`r0>hFQU@vYfz8OM3Uha**=49I&MA&} ztb5P?(0MT^hPR;OXU*3gTTTI9jMDL{F5hDY`ZmSK$lw4}yd7_iN&>u?<>KvdbAW2f zQF(X3ixDZj6W*SbHO=}~WLTLAyu$}KW?c$*;w@h4jH>l@cmp+*J+Dztj#@UPcQm-5 zXZ3i4qAO~f*lvCRoforwyiJoocmiGw2;xMkA5aKaPfNk zdn&!!P2Uc9F(QSx4{I*3Kk#Z5z>7l=WhU^3JxO70swtgesT;@bvD4u_K*MWS^j^I@ zBghW2-)7UY{~zykOYQXjD{KHSX8Cw`rMJaf-!UMFcY3G)p3j@w6z`n@LDm4!wz0I+aai^e*< z7if5kH|40GO^Imp7g;@CW^G07!9L?Y0bZP!kJtL+;sMZkF(8PyYovpc@rnwOI!K|; zyY6HG(|CK;_fS=wQylNUCfDKsF9yZ%9vqdcnUy@PEp%Rt(($SmonX9kO}`qpU_Rc< zEe4MOyf`@*ukYh|s!yE{TL4~+Na3yYa+AE(r^~MmD>H%DQaP9PX?+Cm06y3LcvBtT zCp5fi_43pyrw+S9ndn(P-iTNe?XCFH?Eo)k`FO3KFDnMT7!bs}qD73d_OLy8*&ODG zMueT$W^5bAv24jks48Z~@kR|SsQ`E}D2A5}xT_g(vJBtDhEY0R|8_kUb9_RrrOt}( zua%G2CwB5kz>AY}@eWPMWTILOs10~AB89i(kx-e%$Z7bXJsg54Gl93D+dGx%$Ev?z zsUw~=ZlS~bjfOYEs6btNbb}U{66mD8$s*L@FoG0Vpr-D1!vz>5Jvyb8xa zWt}fwHcK6(Q0L7%aDmw}y8!XxoJ3VQ+Xm~Vzwj3}42t1h#ujUuL~g`AFGlHjjl2e3 z@SMCAKZ4@`#9u2P?-0jF*I--h_e>nwsF(QRm;U#0VSta<5Bo0B8nZWB^ zdX0VhG8cb6eRb%7gAVVeWXcCNyTc#U_7{9wfeU(8k2md~Usuk_&bk9$%<}O*dU9kp z;KhI--lB3hRB0C%-jzB?A-n_4_An1l$Ky{wI44n64&I56QV=f&#qciv@UOeh7b8-5zrQ^tt6s4VJ|z-| zAj(YOT|UE~tyq5*-Y9K3qfu)e-s4of^YhgmtJ$Q33wl_q`K|m1FIdJLaV~M&@I1bgBGKo^Y}htnmZ&NR@6Juuez0x8pcvj) z*N@M4sXH~3IK^R}7CHL0^AwrzM-v++2jnF+iL`ZDae$fo!m{v+ERZFP9B)9{9F{-9p^;1xb}gr3#o^{D*w$~jH) zFTjggKHf!{BRv2w1_bf;EUv1GoIM!7ZNQu;UPni3g-yNMx1p+-703H0H8vXXc56je zRSa+SPNy{M@130jcri-H`#E)yqJ7G-ihvgfAQsHuHVhcoU<2UAEEjK&=8kNg(YE+P z6^uyXZSK)T-u?OZx=>~uf+#bAw?VE4%S8OD3QNt}Wzj*0_bnA~c!7GHjWK>HL(l5* zI(YoJ5`F*QrGOW+e7v)aE@uH=3<%;i4e(ZND*vL6)B=UJ4PIWanDY~owNO=@lc*}E z^G2oQjsm|qVF`G_gt#V8%`6rWnk?XQ)1XCV$i#rtS#Fg|Dxvs}Ek*0tDe zS=aD-UW`cL9X}{bRyE!SZxzHLh%ys+jeXCuht}HTRb}-PHahC?`d^{!c|-rhJHx+W z8MvTl0q@ZsorVKm%<}OD8Yi{|yciI~`?Y#mTvNo%*R% zy(=Z9!nOe;Qg}}^PLO}8zx5UL2pobaGl6%qwkx}RM(6gh)P&68U37TEXm}lba@F4B z{@}wj=~+GAIn3`XHSa|41iYB#<9*@13g7yU0YSW5)*MvYj*2glTA&c#$dxPP%QHW8 zhN|M6L{&L>!+xK#1iTm&!`r5B`Q(gtGkpOsM(KEsRQtQF=r*u|VGHKtJ>)ZLC*Z}& zxp*^A&+oDOOrQtg#fTK%Z$af`Cs(}=F|5o4-s#Oc^sqkLV=XK-Lsg}_4sRk2Z`waO z>V1ut;C-s}tR8PnuRm8R-}RUScrnYz`}$+6Y0!BwAc(iwAz#(k3$@QlEl>z=-hn`7 z*MNE~R2AnG$J^&^^&-HFK{33A+rD02-Fwkj!0SASJRx+vE1m@?x|m1cV`Oju>b4z;Ke8%@8oq&mEG^9wKHtN z{LVXl=~+|2i<5KlrfjOKymfsI4DGl93e(JR%+%d20&Qp=Y# zQt0r0rr~v%k*mHt_-FB7Wc7F-H!;#`UEYQRUYwVYch3K->|Xq8z8^S_pRoLd)JC$^ zmP zal(AO0~+!z057&&yrX>C+yoQ5-GCPpDZC~FOO(-T>)seP%>-V%)az`(UN?N6HlI1f z>hNwnPkF&M_0m(dm&c(5z)NrSc;k1=&cCkCz@Kl$mXEhUlYrYjVIYV%#?_I%@zDZj zsRt>v^4>f3gc z;sL05C$1c}5Ab5k#k(qNq-*u7P8R_$CQ^94mL|ws6Ruu1Y?=wY&*f>V@oOXSYa9(r zY{u&F9--k)$*NVK?mu`gxS+RsyeSu3w2J+~M`7i~mX9~NTZ1pGych`L{nZ>;~kVRsub{ID2CV4{FcTk{y-q$#gvY>IXX!3VSX}xJd6jR z;`Q9}yc6KXmW#JCXt8oubJcOci-{Co`JBUVjt2ibxtDJjYo0|jL16~Zp@WwdRY98%wT?2SArQ;2?@Hx9o z;f`CJ;sL05M_-?bU(CUli?@f>bH%d4ze4~oCQ^9g`sd2eSDE!OY?=wYuh}nEC)_W1 zz_p#5-ZoB$_YoDZS)+ROeV@MX(CYCn&aKtj2KRJ^l^4h5;|?yICn4 z-*KhXgA~Ghu6zp<_T3$8m{lB89B+WOt{wQ&UC#Xu0R`{qpL zg*CSJG4ekV-x)KtnE{owsU zfENQnylr3QD4i1CzYNzBJ7OWicN^@_9b=9ZH+jOWVoS^_2XE2Q$=QGxLovKJowsU? zu9%qvUQFqDBQ`%*QBZPjCBfEPnCyuET| zc^xM#PX@f0((yi0+c19weHtQlRdj!9_;|M_c8vkNI5-z?m6D>-Yu>b+SDQL zHGmh#<>Pf4(mn+6VjzgO^tGchXGahG`Bv;i@w!^uFz&WXLjfDIM>x&L$XUT@^9BFPcuo0$v=Pi}&)5drA*k*I>Yli4@-N zE1Sl2&KqT6*fbM(QxDa#X}gx=E#bEtj!)C!t)=08Y1X7RdLYLyveR2VUPs6K+QjWs z;{h+We7pyGUQq*H3ypvBxFfXs&LA-bX;)MAt@5N>2_?r~ia`74!1+pPqdqn|WOr-Ee z{xDrWx83u@hD|epS6T6sYI?WWnQ(2d7za$(;f*e!-1C|wH>pqC4~%?=R*%>AeuZ{M z^kpN!i{tX~n!nkDJELPDh?nWx!d%-j8h`ExJK|d6J#WOAZ21Ixe;b%pY{l^&_Ie!+ zcrg^i`{rW1yoJ}JmH}Q&>3C%wDo-oDF5;&$cmU#r`FKlbZo-upTQ1()kNc=nr>7?Y zUQDF$s;oE4ALiBJ{=9eyVwwrO>pHw-+cPRl063@ZA0HjwBpTlA>KE$NXBD^&7`@fw zm4#MnH}2npzkrD?AMXKj<7>eO7Z_3no`Md1^yqMDQe*feulbbg!6HZv$t&Mv{#cmsn-)_7Jw++~G z@%D_|qAaazJqUO)k;3a3(_cQUmxUcnGaiDNW&-aZ|Gla)mP0GxRF^E=F-wP6L&IC- z(WEZOY{0$B=&c@a$-z2pRi{P1u<~Nd$D3T{jK6@1fgs+5py5i7ksI-Qo7fQx5w5&h zfmh{2FP+GQS;dx^RSsUO$-nglycmk%-4WBGIe$4kAMj#I$IF&Zmj{_!8B1MJF}y{o z-A@5t9Gr{y>GBNMk8S7SufAg)A)i74?#>bfj9T?b5+@rJ}q#n6T^o2 z>G0mC;qC6#sNTBB@98_Vdb~2(6D@PccP!w=art;({G0l4l@mpos60^#|>*(HP0pP_@4DUxlvOM>7)w=*MrgXfr2K!v={5iOd3?6_u zVg7AH%AvS!fEQaX-qsg=*l)Yun*l2?CQ^8VAN=9sdi?ZkSR?Qd#55Cl9ZOcI9^PzO z1OS<=in%(xEi}9)(;L(lpM8PvLeX12-tG?d+N(XcL;_xH`FMww`S}B031~6%>>@hOUhNt zGLypLR6Pd9%-7-Fc7gJOE%Ii)I^aP#E^72vkGJg2Gi{e|?J@vwiW505AMeWMou>dV z27-8fa|>9zd>{M*26m!&CwKglnYHE@XP8xN#qmb6wj%&9hGKY~j2bj{)?ZHqyqMDQ zvNt!LP5g4UfhWvgc{lYoO$EF-I2Z4|pT1GDx4e77%8Q8<-XFJy%Ck>Bx@p)n6L=3s zKUJB;n&G#~tTmr4(BVy!!h0p_8g9}@Zvn5peImZki!C4Tkm%S8fENQnypv|GR5+X% z`2?Pwq1SmQDD;ADaz{6&TUd@9W))j;ygOsMwgbEvis9`M+n_1=X+nR%izywi?7@k% z>1Ic88yP$R@oeSeEk9U{9}i>8#k=+H2KMuY4?h9Cm`LI6KcNS6=l(g|RSOS6Of!L3 zn`EIfNpKhp*Y@e-GvDg)7E0lDw^ibEoZbT7)P0L^i&Jd*c)NM0wE$iW1o4_(*sk>L zAAt8o*b&zfZyO@UgfjPhvw8wvY>8Rr+%|NW|LPFn#ZU~d@eZx#^@#GTfEQCbUUjCk z!aIC0z7oL$5GTyXTi;=56|B72a`9HCo3ix-`oscWOr-GMQZIJtez8&1bcZWvpE9cf6xNX3ekJsVWswBXRfgs+u zJ9sF2Eoi|{Qm`YgCE~U4GiM^#B}T!lVk?gKj8obQz>A?6UbmuRja6O9V8Dwh9q+Ey zHy8&8AN<#MJOFXRe7py}rmh0K*mCi9s!U@85*Nq;FD6oW=LPR^dGMd?48x|G!0We- zWqph{dj!@Vcrg&fd)MYu zg+)tIjnsn_x^2h`^kaN4rSL9niN!D9(ObZK_RP{sz>6&(Z%bEy{5K#B1o0;S>kFl& z!~N-SEwLl6CE_hson$@@?|B!N1Z;^}<=pdr=2M1ym0>7`cSh?m&84hwZUSCRCGci+ zVPXSvmm7A%e7wr27jFPB4$j3pwf+9HyK-mXc2Af{;obaaoZKcU+~2TiCh%I?FK64P z^(cT-y;OK$nGWx58s4Oa4sKuEJ&ezBdaK8~n5ohZFE&aCyx8*be!P0kmvGyFfgs*+ zxA&AAZhN(tIzge^hP0LgOiE1(ZrP1visNk?G%^fUUJS+XF15?nd}UR=4)9`1$2%hLzx@TT;B&&_PFoyj}2dc2M&%d`XcxQ_?CI4&RWo<2uU0$vOR z@j3_msr0+^+)?U53gNZz+s>GGl83>p;+Vv&a#mialp;^S8~Zsqt73SEI@D{jj!fwX zcrm5p4b6&_58rx26?;NV=mYxCYyJ&Lf}3M(%rQh4Xq ZZFZ^J95~dlX(sRv=sQSNw)}?Ye*pw0JIVk6 literal 0 HcmV?d00001 diff --git a/000_image_stack_ram_based_reward/logs/PPO_3/events.out.tfevents.1680177334.DESKTOP-9E17TO7.35060.0 b/000_image_stack_ram_based_reward/logs/PPO_3/events.out.tfevents.1680177334.DESKTOP-9E17TO7.35060.0 deleted file mode 100644 index a51dfe5badfaa69b2875b4f23c0a8f73d398cb87..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 60611 zcma*wcU+DA8wc={WMowovNEzFd(>H}(>P@$lAS0-l1eC)D0^gOg+d}vDbdofj+L1` zqC(3a+59}`@jAcn=idGKyuP1v-Pd)$pRc>leeUBR`tRr0Mu(WXi$Cn?KC$loLB`373{b}`rO7U<<0Fx!9fY!81=^MJXtW_kE8FrVk|9q8q6?)C2~_o?1K zUhe<>m*I8pE@<=jb%#4Cn$<0ww$S|F*VTJbr>nkhBi%ZI-m|=VO!W&e6p8lPOt6-0 z>H2qh(%Ps`b(eMXc=@^ec=@`|^78OC6g}OmhzuOM zNO02MYu?|a-wD;66{UCJ5XqXg>nr+FFfzwuGJ_SNw4E`MVKe!Jsgw$N>^Yw%y}&-wD7?YF?)XLdk<;S6n^ zQ+mCAH|g;=IBP;HXQaqbHB#&Extb5z5WJb zmM*P;KzrS`y2k$n{AT-jPg&qT&ELb*`(K{w7l@kmIQ#nYwcUh_Hps(guGfFDSgj$0 z{JefuL5n}`zwD_-nrh5}bkaeE-QyHD!O8z4O^#G04qIRcNXeR1q@gxV?%uZrq~vl& zq~p(ak&pgvXv}?h{|yw87HEx<>wf4o4<vsnqJ|`lCWdOCT-J z*r6O~nEn-7jC1YUTa9#Edv>I*uGxx3ABseRlNzM1dse9;mfY|Lq-0Gh(s?!)#M_1d zQgS&X(reS>rH9NHx^o{M6Vm#_ddO={4I2rQB{GZn_=&TlkVff9zXX1p4oJzuRHPS{G;nYT?Q950$p9bHXJtz1=q~whg^ZR! zYB_qnL$Yt#QfTq3j#D2s(qCrWNcTJr%MhFdqzB#ndjL|hCKc&?8>f$xi~uRQoDpea zHxKEio#XKTAu^@Dj$uOjdR0&Pld{m+FiA4Wjx^KIcpD%kV{AyrpL>%(sLbIlASHv` zNJXOU>FZxgrgNW%{~DzuH6AynCmnOu4E*A4WUg z=>OV?(Go~sKXg#G*tg*gw7C1;yuNCr&-$_>70u64TDBUn5FjO&Ga}t{|AusfSf>N`;V~iIF0z+PAFeHdNs{%5Nvbat{(nt6wAwKP zkdiSrq_(eL<;(qd#sE?>$c@x(uY)|(W+wxNXf!fq_JX$K|8dwt^-ms zz=!mOq+B}LGq_5~XbGf4>e*WVNC}Zbi(=#Gerlwbr0htis?I9TOnjj&IH^G@(%q}N z@h1NfASG*3k`Gff<_Z?0Fq-2mAsmS4rh4EqYoBi(v#OgBJE7N#P77qi|jYvUUk zASDBQNE@^j~(g#Ms^nfDH&r! zn$kHuU)QJj9v~%y+(@lFhe-BEOE(E=l#bNJXTeB7N*1Ofjnp-_D_ZdF2OuQ_d`Lx2 z=15QV4DbY`y~6&ljTkL~)TnH%^4R4bHqfGI-{S#lq+5rvBXu>sqBv!lmLNE(L7Ld_ zuxttMcsHv^2t)CbE;zXucuSth`O5``3on2s(WRjR9 z<)8bQ%ou#B?Ej&Ki9n|wJAzX6f#-@X>5CQh4l-U>(FB4ERls8=?^z{q#MuXDi&GW zt`nTpAT=#Ls+!(%UIZW|YtoV45uLvTNXg}lNG%TClNo>iFo65;n0C^@MGkUPw>}{- zNwOY0Qok)VQUNI$V?)|ww^e?s^R0`3lnins4ZGzg`PF;PEg_B4chZ8NK^p)mS(u7+ z@a8hb^V-u-0a7x+hjhYG*e2@&$;|5=iY&KT-ND^En1Bnl_bKs*#pV;zs&( zzu18Dm3g+pK5)kvndsB@0uL zE;1NvS6t`(4nRr<_>k7S*It_T^MbpO(Gp0b*IibgF{`s1TeJ-ktC3#tW=AR-eO58^ zWygMklNzM?UsF}-!PU1ADN&P(G{DCF`;f1QlvvJ)bZFgEGRIS+@o#IUM2hvFdmDQP zd1>WZ3!Eg8WJkL3Ls>0Ay2ADUlVn5ctlK-kSDkf>04W*dMru&6seI1tvv?lJIMFB_ z>93cqlz@~>QjvCA@K~9E`<4C#MoYc`FFx4lTi2$q?g3IVz=w3`^aavRjcYv>GFk%ZM&o#;t-<_u z(Bk60)lxOm%^~ba`vja+oai(P|CrB})F9n)CtH=~IY1kbl1VDkIW}KDo!tmX$>oel zoBZ4=d%i~cin}o;q`~)WgdhAHM={=bVNXZx*(%y3n^Pfq|vH>X> z>!ZX>nLScSqjaRXwgqDVDOs3`bkJg7WxQU~i-432@F5Lswnmz3suLk(v;@+o!`~|H zedfP4`+LtoWQ#LSb&pqfm8+3{TdKvbbV6FX!oSzfLg7&j(~6RO)e0x;Jd?jwySzH& zj8&;l{cJiGiCm#MI7&vSk#W6cHvTzDJV(eR)p^qZdG(BxU!DIR;cq`9M?6Ays%zWI zS^yb1QZ}n&%0J}QA3k_&&%YJ7e7f$A6}hoKP1qyt*>>*-LCw;&{#-dWtKHwy^Yx`a zu{4!ygtE4s`*rhrz5gaUG#~X66MSCBx&=z-oV?dq(0~cBKc}5mHu~8&4BG5Bai*0T z?9(+oVDGnRZYDemV6|(c*_-_BR}B`bQo+u)X=yJX24G=5BiNn$&7?u5BkS=TArn~T ztxoduqm~!LJfR{x*pxN%h5=Z}v4I^G^f6Cs@=pbTg(Npvzw4K!3q_lD3Tl=Pc5C4y zX8;SOsbKfS>Dr~a9{dDgA;AZ>vhy#==5={f1r3-0n-QVy*jifL586zqzip5jtZEAf z*u-|{6>0UdPYaJ~z$Pv|t8!bqYCC|1s&ufKl3=`H3Dz@$oq1;Kpe7%-dGH(|6WH2$ zljLXo`}x54p|<9mjpvUU$9n# zJ+hkz?1sk!+rfl5qX70p-v&+q7NT^pn{qtg!ww7U8NoKpcr26XOz`13LME^UT5j@o zbxd7go=}mPC*@bHt#6k61h9}}1KY4eW$yh)5jy}ZB)P$g6d{uMg?7b)nx%tHc^~i^ zz(Q#%*wYCUZTn9NbOx}H-~*dpa!eXG^pT060TW4Ytu2cX{5G7u^LlO9$&3`uHw@ zh0;{8;XTuAF7+D~0AL}(2ljKl`O=Za$DaxsFah?8QKh26qD#Y|P2X!Kwra3nl6k=D z%$kS4ba6%j?CFRR*8nU;>0l#0n122CW9LP?`$1RW1_xN*?8}Oy?X*7$ zk7~f0_PeaQ^G~C_02Zp!!J56TcNM_GdPcCf0(Z-bWC3!XBV+=5q@lLFWNhzKFi)t+ z4z@{G(`^72a%^A^WcSWnTCUv&z(SH6Y?fX>`Q`J*euA2%gSFLiX$D}SG!^U&xq%{X z*6Q{E77~15ZynH*)+@baA!xt^*cUD(iWjX(Lmu* z4cL_>S5zY&diMdaP?Zi=uQccqfQ9vpV2eu!N&U_2Tksqq6Ik1z%d+O*b&kS3p&~n2 z(Td2~02Xp=V9&l2=UJA{O9rrzo{^Wt60TW=$b!t0WIUU#!Z7wWHa8QFie2D|BsP9=td;hQ(!lN3n zdo8Z3Z1j&C0$8X@2fNH>i8X+Q^^9Nx8g-IY+wIZgIYK6|r;O^$8|rvYfq6njcCerI z-TVM7LAq^+G2k z0$51!ftB`YD81+QW1OG?6JR|T>o^{}`*|j`d1|APlNxOGLk_SLwNEHkhil_sIXR;m zunW%IRt4|5?+9QaN(b9hrO*bju$~cY|MTNyH9m|s;%SZv?8>%hWm$1gU%@<~B0Jat zTl_8nSje$~ji389SLb&t34nzpH&~NR{?dq$gJ%RaO9yK|Ue*`DLTM`4p<^yP^hh4^ z6Tm`(53H>Eu*BT6vr^E239ygHhdRnVTIN8Tw~B@hR)c-?j05cM+KGx#Gsl*~qZ+Wy zHr!JkHq!b4V4*4u#U5e7XetP zN(Z|<*fR~l!g@xq_bu+r3L>rWtqq6~x7Dft`mcFn#j>c@@`-bg$YGukWd}QO#fd%u z7IJK0w`Ys;TD2O0zjQ&88?0W9f298B6<>Ky$AABK(!u_@>b?nJp)?ij*te6E#l175 z04yZ-cJ59Ds%Oj9^P9?vm}Zw8q~_a)!ET@aq&t9x92;0K z*9$p&PEK0}J1iu*!78pykr&T2Uc+-b*udV`UAhFoLTM`4Rl7SWx;mYi1z;h;2UgqZ zl4Ol`bNsCqUV#`e0XD5{t?k>ZLF=GR`T2Xp)L_^B<^X%c@VKJg>q+jyqZ+VHFWgsc zx&J91z(Q3z*#7UIJ_N9^o)K(j#gg73J@kh293j&sf#}cA^$mBOVFQ4Q#5^f)&5m$0 zz>k1Ijt%Vo$mq-+pPyO+SV(e%J=~zLytB>h?Sh)6@38Ck4&4l3p)?ijtr|OQHV-|Q z0bn7)2R7EjH{)aD<(mWzm;l>yLWJ$LqRIKtX2~SO;cBoSm)Bswz3^YKrhaQ13y%WW zjU&4F09dF>2m9u-`xpQV>lwjrzPaA=TBaG^PX;m89d_vDYvPvs|LF+xgeW`M@UDMu zaQ|2QpC9$}z#zv4)~tno&b8y`M*~<$a)Vv?aGK22aR9zc0(qiYI@p!10qrFHaZ7jVLc<*DZ^7`EtgHW%5#KFJM4wq zxv~TGFU*B`LPd74=l1>iDEr^e)L}GB)P$E>*Fbp&U?L2P_uNf zmUC(y0rG&wFI~=?MF<=7h&c$mK9UT>Cq0KH2 z=Z#Q<&EL)g_IcSpYvEA<`(b?TmjD*3(!oBsJiQvg!g@xqzR5c!tKJS?%X5TGV82@F zOB+|@<6GTOk(ejtk{~y8PD20-IX1BC3ohq0JQ6t@z(SH6Y@PCC>D3NjYYS?Y4%Vjf zQ89pp(p0bw1GYOg?bh!bfQ1AfSnc%_#aZQjm&1+#uRsi#0BiTOrejy_m%-5H#htrG zs=>y`@qn#JJEssH1+Y(gc)td)P?Zk$CAJ4OkgE%Hp%vH zxZEA)2^EQXQoz34(gFVt3pqBhu1)*pPOdKM4PYV34Yv5Vv;6v=Ww^sap7WAm*ss&udigP%Qs9TwIzg6$R?C`s!5;4{w=GJ$P2 zV4Gy+nYn{uo=}k;?8y#0vS5dW92?kisaH?-4QzpbhlM0J*u^>n<>t#K#0hGazQbOd z^z|PA3#F-GvmJwNu6}!W7!Cmrmvk1NUmER?2#&1iqoE+^@t2*5&u53IwEMDZDiBkKhXm;f6TU&GPm(rvt3 ztImtgqt#&Vo#X&Jxpuz7+eH^Y4#pYPfZd(;Se3N)!3O{fQ99Vs`9tv|GO(Tz?Co&@ zR_ouc#XEZ-#tPPH##-6ZCz1k~Cq&u7I*)Y4&#gj^4Xo7aN6vvE*OmfUNOFU1HuWE= z=#$6|z(SsAmJW8tiI= zy^muDF>0{6=QzN|{>)W$^$x+ma&ksBU_XZysglDp#{*c1(!s9UncW0-SXj>p zw&jF(l4H{NK%VB9E(wC?jF9>^oY4>F2^HDF>J74e36}(rV*}f%R6l1-4XlwjH+SHLa9`qW*bA(J_=NfI2v{}|$3iE`D>|isipG5&!$gzQ4Q9tTr^v@_MfQ2MC zSifXF+3?rnO$9Ye2fHlx)K35lrKw;W9{lcTUzBhSz(Rr#?8x{il*LAdF3{%o^rCTUu&eHJfHiKLqi~z=bWC_u1J>is6IIC3AxmI~g{pM0!3*{E z04%I$1iNU7vxQZ5C;Ze1#E5?-@fy}DR7=v+b?JTp3sGX8l)n-jI5H_6z(S4XHA;Aas;XFUf z((m?b1r3-0d$ai`<+GLf@z7??>n$dz!M=UM19sENDF(u$09L-tO95b^Djn<+kFps6 z7S=O@waK|?d9nLZ{9g)UtYDk>{Ush*KjkgV6Qb;3zXe5P0$9kgfo&g^nk{)%{u*{z zNOFS>tC%ZWJnyzX&*@+Tdt#YRHh_iFRIuMOuR3~&$3y^FNbrFjKcKew(eX;W`2}8q z7%&0$Z16kf()kj+^2v-JJW&nyPB{nIM8}hgz|U{-xhkAd4OqqIr>g9M^@adgh|OKmuxC{rB&*C{dyB zPHem1_)ZrjxxpGY=pwf`d3?N}X6cs%CWT*T16U|c1v|(%)ONW61529)(H5FXWlU1naaI)82O zW&jIS>0o{Jhxx(|3+oxd2390Ve}6G=#dCyA*RZQ1f@SASdxpY1p&~I)3fKmcz$*Y2 za%^B-yawi;{=Ep_>4GFT*rOjO$?_MbHWbt>9qeVxb0YvOl%|4xRC}x4#Fsm!16WA# zfi>HnCGknL*(GSe1laAPUn)~i^~1MjgD=NTQiF~A#sOBO%2F%~*K&mkaYi*@P4bFW zOIz3V1F#UKgT2wVWfFje^^9OI%xWs>({j3u=Lng=`bEabf?R4nhj~IpcCZ7KN&5gS z|Fqf5rT`Wa zd|*{N7bJT;PCgSfU;^xl>QZIVWJ7#^b=I5P9%`^FmTI%#t>tQ%r5N44>=8_eGpYgm z#jZrPDeA;G01Ht%*pyo4-2p7DX9SzrZojP4`GPE-BV+;_96w&xdXqlBH47El!J65{ z<8uih#|E}uxKVCSd{QESg(NrFnxaHmP}Xa_`4{rU^$#8Fl#yHd0a%Dq!480qnR+`R!{VLc<*o@rkss;7PN7ITOZ=Meu&aA{^|Nxj*_ z8o@jvO3agTN#Hu7x)^p?$gzQa?$PXI+B<#RVIj#4_DJm{*-`y2**vF%?U$~C25&+D zER?2#-SA_O-KR|tM!^mX2|lpBANq)m+FU#%Xut$mQ-jCKOLuHLL7O21x_GL=-rCFo zR(Uf+kvQzw1mRH)Sa*4;%DQ3(J`4`3(!qAV8sP+BVLc<*?&s474vWjj8zmsd3U*M6 zvpDY7-Ip*=h_Zv-dZX=V01G)bu!E~@vxB2UHoy)GNp7&uKAe)>G&P?Nr{l3b^-QvX zl~;!w16YVs!PeH%vU6YP<_};Y!3TELvs;#vmL5uh0mCa0117*0T)e4l+-mm&XfuC{ ztCt#VRtyi=#}!rhA!^PjfZgnD-57RQh|<9>%#6n`34`^FVCNf@it}y{KgiP@(26A;AZB!FX?R(3%-Bf(A^0UA(1GdC0c2J+xU>v1F9>l@7K;Zu2#;!@_z-u+e=U9G#Rfus+Wb zGJzHS`SHAAS_SijitJ!-F8GxOU?Il__Kl}E$n&C9TrMc!4_6q+xD=@_Xe<#-~$_eu_|?&bUA(o30{F1Fab6;?56FZq1v^e&A=%~ zr>Vh4CUb!8nwqZA^>n!{JgNa()$*C@;=&gd02Zp!!EPE9ItakRdPcAYr>evmP8A}a zBV+>GaB(ZiyI;?}0W4G`=1JLM=NG!*myAM=4Xm5Z+U#xK<>LS>B)P#Z)7>RIFm^S* zX9;=Y`iBnoOU<2a04zkQV7Kc%u&J7Imo>wakc34R8ft}=7ZdqP(=8B*J6JW=` zzo_iHs|Ma)IP0Cs3^mxB`5a)QlTRqtud%QI4xCX9*xb@*s+u}2oB=FE>0o1vMw`M8 z3+oxd9@wudO{p`uH_s6=fo*uSo8(=%5nf_JMRu^0P2S)m;~~ce)?tZX_N)ur{QxW^ zxxpqyJdq{d&By%%@|<9|cs02SU?EBcTR(1)UGK;d^8hR)_`vRV>LZT%wEF~rg;yX3 zOn@y}d0u&>c{fKmr;+L7XR5(wT;u>N8hAoccGn+&E#-`Az#fx7S7{&0c?Mu1N(Wos z!!jPg!g@xq{hwa8{5AP=CQoyWU>C=TJ9NIJfO$eiVxE*8HdjX*Z+?Ls8`zc;24|aI z^7aL=kmLrte@3~id7iXNP_y()0@>)DDgX^lk%w2oa*}V1G{OhhO0aIX1BM z9!<_(6Z@ngfQ2MC*wjToWHAY4A9zm3fB$#V!5)4xbtiy@(p0b$PIgcZjO=j%c34R8 zfgNMAPNKcHX%c{iS0DyVfV~lLPWdn~Sqg0$bUQOk4R+Z>9gf)B>2F7KD_CudDW^AK?5eh+HQVr`*><&%18IV*7s9`z5bE|?9TUTii*o#p8)LY zx((Q)8nERSFI4+3Pa6ebAxZ~ZwEG8swJWS=1Y3Vw1BvhJk2`pdkZFfqy4g=+>zY^r z^Ms1*V3k&(jsO;NY+xl(LD~D4R^0`#kmLrNm6s<=s47er)GQsWrF?`ofQ8ajuqpec zwnfLT;0@f6-~)TTuCK(`u?6114X;29m;f8$m#J*Ecyk+QGvCO5jvDNVPaI%H8`2cL zuD#zRJgNbk74br~V86FHfQ71buyax2hTv zogsbo0W3s`c~UM3TG_wDFLZ|-8`!H$MrMb2#zz8JNOFTUaMzK~IMw`vnFCqN^EUae)YZlr-Y+`os z9-Kpnv4Xu)P$149+!((_2BO3~DPUdBRoKD~3pqBh&A(e_hqd2{H@`rV8*E_%Bl(OW zqwpzdkSCg@@30L&T^m{+f4%e`d-~-$J>l|^N-?QRjM}Su#226l$ zS+P^;)GcZwoYQ{w4hE>fhA*$letY4;yT=sUW4ezM9@T&iZd|6yN**&7z(Q3z*w}f! zt^-(D&j|KjlN`(TZm;l*RUk&3L)>AT`kWH?ubeRl<_S?^o)oZOpW9UfSje$~-4xe0 zTc@ARYS>{R$qm->O$Yg$7U%Gv6UYuf>08uJf{jSFLln%E3$6A{KEUae)tMIC@tUo=L?+BT$VXuEVD2@vMS`PDsitJ#|zM9Ytz(S4< zY{k6h*;zK7Zv$9Ja)Yg%WGV3{^=%wg(w~D zr@_CM0a#ei2v%FtMe01EKi)eDG2$HJ4*TY{uef#3*g}{mMA^Z5k1)CoU?Il_*6irl ztN|~E9s;nC`L>V*`6C z`C96mMaQlISV(e%Rqekao0gkVPf)Y;OM*^%83-0iQ^Ag%u*=pY;ZQpO3kg2318(FV z%WHEU@85)1AO=i;tue;aE-}Cb|J7^}ws^i8?2f}6V8=X3Rphj|y8$M|8P$NDezQ!q z%x|?ffQ2X(tdEUx?UG{v7S=O@y*s;Htd%hZKVb0sMoFAa461UoF0rh=Waak=ub zUuYiy3kg23-uZLI=4-+vf(A^06+K<03_0qD-|n>9IdOp+Y}hdluzfbADz2CsoPY^& zMm1oo>zAuKi(AP6EJW#GBO)i^<2GSEBiQ4^qa{+`I$d~q@g)EY2|lo;*Q_n~`6igbjsUMf44430J7BExcF1B>=b&S)&7d>l>io^bg=Exnk4{OSkDO7diqy!j8xZ@=Lng0 zSf^dV;=}K+;*(#XA~8=2*d&`HpWu=Ja%^B%Pv4t0wWRq201HWOux)M*lSdt@Z78T& zI@kkqvjYGul%|4xQ){#R@9aDHFgQr?f&IL*op`XZau$G1G$h~=117-QUb9y2deR1; z`D^fM{312j)GHidMfoX;waVxvFd@#U2JHCca@EI_T3rAvMCo9UM|$Gzg|MCxY^*X) ze5rMj9nTRmfqfxz5<8xIiQjPm6^VILz%Knz{|kfd0(p0e8%_rJDTJ7Bic34R8fei}Sn(=V+=#~H$UV#`e0rp&6 zKjqNoX5XOA+KyWmtHEx&!vl6hb#MHh9nL6#typ+?IDmyH9qibmH$||+!g@xq4SgF( zE?;i^j;A>$ux;I{#GXf9;luTyA~8=2*!p`W;}^?8jt%S^RqgB(I+q3mSV(e%9rV#v zp4dJ+T2Qleuo-)9oCL5?nhMr$lA-;z+=JEt77~15z0c%}Q$6ih0$6wjV!#C0h_&67 z`&GyA0XKDC<%Fui{wm@Cdt-5mB7Mg^{2iP#ssS5PT&^+*x;-1fLX-~He!!Wh02bCW zf*rYWV6W{9|G|f$K#aJoQ>)Y54=eifvuj#f6wDK%#5^frU$^avU?Il_Hum|A6TLj= z6arXCa)aF%lOe0oW8NJA3wfehI@rl>z3@>*5T$}0oOsRl{p-c=04yZ7U_b1Nx6|&k4L{}`QBf482K%gx1FXm@MUk92CjchI8P$NjpkJXXeCay| zz(SM`_EBg@{5Ee`&j|MJpmK3SXg~Z*55$Obh+r2yG?e7t8g>f6LX?;%1#G7UbsoSa z0p!@gu9rqOuG{ZI zZ2$`iKClK`1H~g`i|~eHcm-m>1X!hqM7gxrph?hXN>r0@HP}mUIl%gArzre-O~iW% zIHMY{wzieCAyt%OH4Ur4T#tpziRXW&DL7nmWu&|yHtms05_~+CQGkK1X3G6@q z)5IooqQ?PPs7TC{0yeqnzPqr)LXHh=#;2QE!^H)e02Y$mVDD#p$oH+5SqW;E4tC+@ zL3j-drKw=sjh<@nu}W_{?68pF0~^tywdD`LrzV01On@zn6)95=CE@czhF|enrUtt; zT!;N`t+gADDtf&7iMP^nMm1nlwpFNlr~d8%U?EBeJFa1;O|ZkldPcBA>UI<_skFy? znjyw|Nzi7!xp<9%KHjYbQFgF}ewA+kEace0Zr!&uYvBqzC4hw_H(1jl-tu;hZ#M?8 zkSCg@gWdUX=0n(FAxZ^XII4+#-)NUH_U=Q6oYteT9bZr0&uRsi#0DE*ukwb1T zeSB*+t6yA%8tji%9AN8?J*o)x9~uS|;*4s*?mAte3M*`o24Epd2iq-w>tFy2>lwkW zf1G7mJvJ2YhlLn%4)GfH*}!$;r%%EUz&s&J%#*UiCNy|e1HeL#4Q#(c>+CeoRowwB zB)P#BW%|m?p47+hnuR>kEFJ7YaT$J#3`D75`;F1JFN*1o&xeHsAK1ZNPgvRxd%aZ9 zfC;eEUS~MeuOIdr)Lk5MCsGZzWD^fqZLMN_HcqRF98my!{?;P=OczAyV8=bRn*(5B zJtNre^|UN)r?19mghPxthX}UwA{Vi=O-Vk?6Qb;37uPek0I-l_1AD9LRMzfC?OOm? zNOFT+GsjP!=v2!B&LrfCX6axjNupc84hvB#*tl#R`)LCUZ^8}>2|lno4~AJpcAHa8>8QS;_%SDlv4Z{gQAJAzoyJdaK$Ms#<&q%P=hj*P3pqBh zjZCE3H8;nw%T3IyrrF0W3u6V7I=W(h9)BdPcAz_ohm%zf4u}93j(R2`t}hNt{H{_z4cENX(N0 zcFq`A2LKB>Hn6hR&9hsiB|HMKkmLrdzj=my%MQ0$f|{j+wf?ycpTG^JsbF8sUXzn$O!Ya5lU7*RLM z2qwfC)qwpmzEXAN?U;iA7NT^plbekX0+2Bc(0S_T@6hIL>(6V{V4vo3 zfE7(iR-A2ZhM&pcjB3Dc2&+_ykKEq?U?EBeJIGzX1i-?2MzHhl8;F0+t%L7$L5vmb z$`vat`(JbF3G;*~JJ=KZUe5!tkYfXTz3-9CgMMQq02Y$mUOZOV(AuTz6n zUEl!QseiJ<=}pl`;ZY6P`ui$Xz8`xY2e43;4mM_epcufydPcBGx5D~0Y0h-5`17AeYMD#u+0EJ(gCkP4444BA+fzfY)$~~uuD1) zS+53rgF4uKsO5`17Ao>-GP-l{7;NCRGh7%%~LeQ67avXT{eFM-3b zB^%UWH$LD1o2Z+tur_xd4HM#wYQQc$TdCUeBLY7)3sE}QCZgO>*kNHkBUsU&pNXT) zuJ9Zo(+>M@)XjLX82-hAio`rAU^myiavs1!jt%U;6}>;$;g@nik{j$LzhYUY#OkS_ zX6az-cD?TnV4*Y>?3XVs>{f1Sgpb>V1RvPL^T#D89%vCNXut&62Ag)<-Q1CQ3fhcz z-XEm~`=x{fZ1B@0h5o)>2$nOd0sHD%rKt_x8**rq#5KLS`- z&j>cHe`WtOdS~#G0Aj2=Y^T(nmSO%EafgK{JJ=r5`CY_#lSbD8u<#1R zfC;eUGA$gs48A@D+U)cC!bUaNqACusE7Fq`=F3B;2#;#Ode^K{RR({%Z=&Y<7c5kz zgLS#OKNrBldPcAzz1sDyQ?<*T=Lng0SdV)BEhY0$>%lysA~8?O4x1LXw*tUIjt%VM z?zx%mSL=-eu#n^id%V#CdEH@_GXynD-(h>Mihcz8vqLlKCnqk zTrz9UANWbofC;dx4rw_^TtxVGm0ca3&1$e`KXQOQw?0X+a^k&4Fd@#U2JDY^RjMXF zRmK1oqI9ss%00^gEUae)o4dBa!e&co3eOQTfz>tnU>WjHZZXUgDzbyUvwUnz01G)b zuT*wpGKXkCOB5POyScp== zZW|YGr{y*mzgP|ud|)Rhe3Y!oZ-sYj!7C60Ccp;nIAY%?-v0ue(;I^qZB>Ka5Lt`; z_QIVuNs5@PSbU@bXH)}r?Sv{-_vm9k0W3u6V1L-U3m;62L-5VxE*sf{sr=?gg-rV*@+B-}KDmXWIS(uze;FXM!87-_}L){>k;? zp;^dtf~{2Aeg&`)rGnMj?rf*39g6o7K!OjfeVZ#8>DR*c!GPfvhyfE|m(1N_e{Wg# zIB3(sRwt5{8*a4evZxJ2^um?~4J_%r+`;zeSErB?pmtPD0>cXs%P_GRr}Wm24U5P`VI7Jg-)L4+s-d& zhLKj7R*%nj$IgUO^3V5=1ANDY1Wpe0_X!yn>T9$#X@1u+vOQay z{a1QUL*f^fZmi!>Utd-F@4;Ru=_DOy)4ZtTe+gT&;gy(ZuHRJOT$Ko#9x!>rTp$0C zaT6#1?+4`X9%gn~krA?RU0aPBJZoIQOkY*5fA`Tc<)~VHV3f~qvIS|{CN>&`z0U}1Y!u*26~5bqhWevZHq zs@jTR_Xgz<0~RzL1pS1H++dYN$6x>pIWDl1--{GcS$=u|7Lxp6OPgMj__ggfJp7EF^@$KKxdaku%Aq6*Tx1Nr6XcFa_+LnPxJV@gfBb zb6VV{N)_1BTHIi#7Ff%BEO?p)MVy0O;&NdOiSLSSPq>z=jHT3reazMf2h zM`Ff{`2w!B*(sA^cO{H`QpcOt8&IEglYFp)?(A_ko744(4~}0$4~0flaBS zfA+PT`yGuMOa=SZO7_t_c?=BGuJNPhDzH)YxWSI!+eALZMZQJzs2c3S1`Rq~)ZLM(8EY+&V!2a(b1zl?@{LPc({Z-Wm90a(a! zfn9M_q*$`6u@b;Sk{_&e*9l_of-zS$8Y~lR7n3V104$WIgC!pICxhxHHw3Vd5CXd_ z=0nDe_;+$>a71$oJW7KpV8^`llSOW-y9|ao;AViU3T#pXZm_K)tmJ`j>L+L(RfGL7 zOQ}3s+RzukLRA{rumf%-4}wPlSlFHwtkNn#Qd&FZvcM6tfempCBZpqB?g#yZij;oR zX4sAgvX22+$Z>&vxlN?_XiH84u#n^jn|IKJ{5XEqc`ctX*cLz>|_7aF|(2?ZXd!4$A7>wS{Om3^s(VSatr!b=40p!GVne+90$A9d6|AWHGRdg(-5LoTAsg5Xt(D~b z`7L@tKcOO}pER&~Gh4|4EabSrw%jOEJe+gE6~IE0A8f^)r$q495(jtKRil_O6#Z zO9i&LF*n$<^%n9KyJ!5?JgNrk9l1f-q@GqNfQ71bu>0NWpYJpsz{2*dVCPqCmvkCk zXd`fhY+!E=+DQKD8Z#dH2^A^*q=7v-YWh6@3pp;Zj$tB2r{HF{04yZ=!H%twNCf}v zhSx$N|MxPgYOqYOI`zzs16YXC!G^Y(=xV%rtpk9Cgb>)V0h2N|4z2${qXtvJ)(j?O zv-@4@1n2be`;pNquvJFfVBO2iT4cVgN@r7seGQ;xd^~QRXW&xZWH?6XbE6p zdseV+Qwk(q=Ge9uI6^kCo<9$erw*K`0sVxE++YpfpSTZTA;$$)*IlIO-nqIGz(SHA zY?v%le6QW~B^nKu3HFXwLIHq<(sZy-8~y~bL5cQ02XpwV0#Y}DTW*{a|E!E zk*j?t_VD(R#$t7;RUuhmygWX%TOL?>Qv;qJNRcTd+hMRsVVN@^ z5x_!{AMAbOI%NF!Huw)7*Hi1lL6zNvUC z5%xf7Fa@kd<4&^ZfrZ*|P8A1RRj9zGTXKW-u4yGVo4+Yn^Qamup`W0vKk|1c01H)V zV8iyhwQQFD8o7OIY|+Dw^;2M_X;!7^vq)zcim16YXC!AcLrN=u3k z=Kxqp2!UNyXN!2`u3J|%YA^+CUb3NV@b~xEK;4XCA4JiAZyXdh;RYMo(^8&zc*S?k zqiV39?ba#pZhEjDz(Q3TSgpNo`)c+a0AOKzR{e z^b;y_gY|!tf-@}SxWIlKE>a|x*Zv7$A;}N+>#;Z@%hi6dMuTMmtFRRTSSU>gyQrO) z%vkv%8o)wA2<)XJT9V^)gKVL}w|yz_C=I57oz_KP7W4T6{?awzMw+z>Y=sRESPv`t zgC6e2&>`Na8f@9T0m=z``(*=Ih%&*xG`NutU}1Y!uvRy7BptepE)h6FHn4r&R+F3M zcXgnjP?6G4+6-HF-LG1(B!C~ZA+Y9KtkN-k(NWIOZ|qTFCNZuy!3U?Il^wo!;kp>x*P9A;QZ@`LR$MnuNu+`vcEAWs=A z6Ku!OSNZ@JqI9s2cfWF#w0BPgu#gY}t1F5V53FyvMWY5&!2Z%Ul0C^x$Je``ia1SH>w6p=-*OCMVx&JU?Iu`o2tLn8o>+n$0dgvMl=qFU<20QB9y5#^Ca$I092Z|H}PsSAkSV;1Nt^2wLIXil_sYZik zf^B#7%}4+XrRiXIZ8LFw@w`b1fQ5t**r_XYBsmGK8)(#E3fRQ~9pYCl# zRA5tEaf9_+YAN3^=hSS?qiV2OpNf?^_MJumSg6Vbn;S1J1hB9@E7;7X+a>EZ{p>Gr zglu4M$wrXlyuI?EpHPt-thVm@a{v}{Twq-mi4?zX%ccNWNb-Xf-E$`IKAX^3qro!4 zZfIr@24JBy9qgcG%cRYYnpOf>NC<(wTPTvGJhS)>4OVzi;87Y(0Xwuu8`)diTW?^P z&)UVTQ-RI3=LSm*Fqa#it}41Y($=sos|MZzu#n>d+ke5I#|t}+y$N6;$q%-&rkv~; z@+MKE!7{~070~?m$HuiA#WB?1> zvx2o~xc069ggFNpV_RW4rT*E??4%T3xxAfE(={^7p2_djMHcb;By`TL78tgcV z0*}&Q3Rta+?Pd1Sy8YmshJ6grQGxyHzzvoNF_JesG3k=#Q8n1$b6Qz@rruiyV4*4# z>{7#@;{hye&kFX&oV}8(52qXuI6^kCPug@Mt5&+;(oY&##X`@P02XpwU{jZi z6yd#p$^a}R`N0P1>61gmqQM#smN~;#kMCg!Gc1&*gLT|BT$a~uiWh)|gb>(dzvJTU zeMh|kEbM{OU<%kxzMW+r5wCEVs}IdAQ-O_Y&kZ(xikaNYX9wPM;Ek%mhEJ`Nm0Ddj z7r;W43HFm;1H4KA+p~hre7aup!|?&$i-Qq|a3t=|>ELY^{MCfJR7x(xsWD~j=e<)HfQ2MK*j;z!Wc$%FyzvNmUa&KME~o=w zAxa19)+p3$01F8ru>A*47dKq_%T=QWQ@~z4XCce~ePT46(-^~}=9~WB>B@BG z25WC?C~xUz=dF2E4K}?=obqA6#SQ=#s?xxQ?Qv^ScN5;}g6&zsW_27Z@jU$j--&=2 zSa@kmCYtd_bfK$ZVAhU?Is5HvNPSxyI4wo51N% z{d6*C*oOwc@OfA$O$R$e(#O@f)zB{h77{{W59~`6i((g-Yt�SV!AAvX+6d_z%g~ z#`&F9V2e9*gAFE(v%5?Vw_+nh#HVHB=_-I0*G>hoz<;hGJu5~7ufR&BE_fu9nSz*Nb-XX8?;J%YT26m z02cC;!7{;CB-Jm485W{+u(qDouHu-b=Kw4ugus@DtrdSi7Vi#VVGooBQ^3w!7uaLm zfn#`or2N}i4;9#|uH0blyPC)g)0~Dvhj^oEu<1=|D(&p-n*mseGQnO5%w7&l0@$7v zZ0n~|$>Ns_aSaPG$~nXtws)f%WM;*EN9ZR+DgC4^3DVBSHvq7Z;{tp0xJc1#$_Enw z3rT*kT0drq&;DMg*#c7o{yS>H8Nl`zbf(tG<!RlWym46$OwLtTz8f;O5vm#1A<2QhXs!Xth zeD=Qsu&_NVSRbRI64~i5o&rb62Da?GKG|oK#c=2+ROANRqp%&mH48Z|u%C8`6dB!* zJp{0jxWO8(FqgkLxT%@uQ8ifW@EFDHcY~h* zSg6VbTkSs89Kgc%tYE)vmP)R-%o!_iglu5Ht*Iomc3)0~enLe`KWS^&3ZqzjYZh`` zU~6p^DI7N)!f$Iqk{@iU-&nG4;G3Ts4VDSE&cXXL04$WIgZ0neLrS)#Z3M885CZEr z%l?k?M=Cm{b3){1Tz58~hr22V(eE0=ooWFF%nbjaqt>23e6G4<4Z1x_%Zm=YP z92Z!dKQrvXD9`KX5%04zl5U_-jqcikNG>nwnU zgb>)Z7F)!>b}q#)zrY?S4W@vdH_}q(?6#-^)LpD~?z;+XSWj-S_L)uO_lsyt0^X<^ ztl#s?%6IE}eFm@)WrCe>dqoGi-j|BVuqua$}ePpdzK8 zv>A4;e&TQd3pp;ZN0R=0m!R6{JAj3x0NBELB^pYb-??pM<&-ciTQiuAl985Z19pM@|@lQ z-=RaiQ8n1Ic~#1aFDpF&EJT@L{eq82!VC-Bvx3cd*;5i=n1l;-h*2gTysY(FC!aVr zdg5v5Cq%iyp1COY2C$Ih0-KsIQds4e>H}Cv@`Fv0v?HI|-F6o^9jc#BCfF;hYYqai zP?`?*%vfXDZyVEo02UHLU^{8G5^w9KE7GXJ6tL6A7|5){i|}TUTfs^v71-21++d4N zS<9dQFtLOV@kZ5PJ<^{j?+*LE9Kb@91~zQB+pj}?>H%2To)zraK4B75f6Mg(N60qA zE}Hd`IJ8mx4EhNbxxqeM*BIBZkmCXyl_*jyu5oiWfQ2MK*g>oP$*0a295fm%6YP-E zIza#yO4Gr*|F)4%ne@;Yz(PU@Z2jK%#4amL7HZUB3Ruq>5?PYV-dGrBK(9^%RbX@b zaf8+Ow~;$v`HojPd82BuT3Qv#t1sg%0W3tBVCVJe^$Nhk_N-u=2ltgsDl%FjFgP}_ z`bC!s&s7PVpr25Y8|>&lP4!@gg&Y^y{0kz*g*U5%0W2i>!A?BvMY@gdfUlE6p7PHL z6YPUo$@TyiqI9qkx@E3wjShYTu#gY}>veF9`0J>L8#QV$1?>7$I#fqp_oZm=&;Kl=?}A;$&Q=!{6wt?iI!0QSrj%9-E?E0MJ)XPTD{ zgTX?c7wqO5Kk&;h5T%11x~P`)*rz@CP8TGEz*e1z5kIUrcLEv=d!RI!0#YE2O*X|25p zU||oG22;S=oA!`pu3dZ%hH2;VHc;f>C?=tc4{3MCo8>ukGxba>n2;fQ5t* zSkbS|;x=>oF95Kx2TFq}V9Rq#rI`^;QsA84Uw==b0-H398?4qU6ZrxgSG?238&!kV zFUnEccJ;uAUm(f^+p6pA0ssr!vx4pMJzOID5s4r4gBax;;tZSm^)WH-?rQwD7DOri zq=B6hlaH^+K#mKn{y~xAS$}j=2kPrfUTz|HBfPDK$01JDdG?)VRRKGqlt@G>f#zAJvi-#((nIpKtmd!Ji z|Fnu52-bO{YOs;Y6y^14=`CP}g(ws3^nRP204!|J3ii{Magy~ldmj`yLbe(9Nt^RT zhZz>wPpC-gCk<@hy?c+sk^pjCV6FbFVQmiP;F186{9qTHA57}^y_2EQV3}YSmvqyH z85T;@!EUp3aDDwzAHhOG2<)gAdXiRVJ%<5U*aM}(6tJypG?n!-xTAn!wmaVBy9#Xa zNN%u|olN8%7d9%>JgNrkUY4L-UZ{8gV4*4#Y>%NtLjVigvx3#PHkPywFvkmT5Ti^w zIK%$hag3|BQ94*Hv%RiOCpKyWGb|*8z=j#F6bJ7$3)ZN?6tJV4j+gaX)!{Ix zlRwEb-2C^(L6sLb*nC4X`9bj(x#m$d*hpof@{7#C9l%0WCfEZGbMYla*q#+^{svP? zP+zlN0!PR;!+y9JPUO}c_Y?XF6}iE#l2|+gu#n>d`?5%+NG_3%2C$Ii2Rms*Q!=g2 zb9^5N^1NX68X1NFScuZWt~t?&X#DWtF8~V(A+W~Xmx^2OG&0wy!4$A9?TutV=5P1} z=k(y?s`e_dtHyAHb-HOO-!v);uT=9!)nE-BcPq!Q{Fn}4A<6_h(ypTe%&@RME7(K5 zNJ(l!RDFTLv4Q|tIDsqE$INo?MfQ1|v*!7P@iuX1qS^yT3{9rwA)*yQ& zy5l!|AkPc7>(jHdV1|V#9c-khscVzv-<$v}B!s}WpYJQ~uwd67jT%e=``od)OuNk* ze9e2?)OSQ8n1g!9NxGZL>B4ScuZV{<$^#EkAA^fQ9W@ z!A`WPEt%i%5#AMn808$|8dlMx7ZEg|q6zd9qTFD^>W(b{u#n>dyW+V>5ma+g0f2=h zKiHHJ67p9EFAss!q5A1$u3NS-&Y24jb^QanZr1H9=b4hLlfQ70wuzzkG ze6@)w0E7+#LtHh_qPro2=glseH$Js-Pq)83%FH1s2Zm%!FBd6N zz4j3R7Lxp6wca26^9RZ9;s=c(PxCyK2BWwR9eGMg=x(GB?=tMYi&*)kICrqiV43 zWzQ8ucdrTtuuzo=HhA1V{G|)FX9t^^FYad79AA-v808$|k|4IC4Y6Y1%j3{bh*J7V z1KYV~F|J`D#|5_Hu}JYHcVhwb9qebt zV43cw&Sn4>5<+0_4eu=OyQCvNzzut#G?)T*PZxKY->+48yM4xOpZ6-TsnfW@?saY| zw-~e@ACKmZs=?ZOM<{OB3#EJT@LJG3IJ0W56K3RX9#M64t{U&A?s80QSDrKLk? z%|4A^gM=uhpR^fvtY<3zQ4Yv)fj#l(m#)QCy}SV|B>BPCGJZqo8m8RUXs}GM-l<*i z6&WZ^2YbkK8EIASHx|G`LI~`UxQi}+W0xL*83Fb{X)p!sr;np$TOV%6YwNDw`|5A` zd*dK?IyYG2imkl&{p_XCA>ODOY~0q`nI5kaj<}uh zQQ!#KX4o;(uM(?Om+=qvK}AYGX<*k#W@Nw&3pp;ZUn@k4>lfGHvjmXj2OHKdPBPam zLg;jGEeX!8la|2@3#I8`gTGd}KKQD{8wZdO0^5eHCw?10Oa@?K50nN|z?#do+-BeJ zJ_pX}+)GW{s=$^8bAv4^x0Q!Kc;%~kR1MZTJU}_6{faj9z7Baj{2o)*)q=9XA=oHSdkmCY-cZ-2}TW>`q_gN?nd zMVjTU`=!xfnKP_jjCoT43#I8`y_#i9D{3eAff*JOLSQSK`MKmouX+SvVGooBQ^4*U z(Me|0a275^+uDqBSAqRHgBxsF6I=O{a%BVP5N}isc5l!?<(F^o@#}>UWr7WTW&aGo z!uG6S^@c7JpMLZvLf{D5z?vy;NlwpAz|U<$MM^(uVE3M$)Cp!-$Z>%!tQ09~*;cm! zu#n^jTR~nT23#Bxq|soRV6!sL>;te+nhy5qJ4>?Zh2wJpEF^@$-d_C6#Z6?~6~MwC zC=I57UGv3S);MMRZWw0o!xty0z(&pD2J3XyRxUZ>gm1kipXZ6H!D?yEQMSu8x&$*U zM44a0m7u4UuMj4ypjKkPre} zUTiN8&-23ThOh@pgDGGaA9j$rPwI;IS4Gj^7OB7{&EW>CKg33UUOS=*Sm%wZ!Fr?* zQLfnWU=4tUC=+bsHb-$u0Nb;IJ=*5FcxB98SAipBn_>HXd?IOFw5ukqIHI6^kCgKE|!CY73(LO-D*H`s-l z+u8wG$Z>(qEB^BUx6RI4FvCKUAFN&QOJeDQ@A#E8$n(yyr9+eO>xB@dgN^MNDoqHk zS_ohvAq4j6=(A$em20XrYA^+?%kcnN$i~9fa85lcm#3+~7BAoiJKwa0ypPNd@6_`~ z)nN1U1}IzGy#ESdA<6`MxiG{7mISapE79 z4u91gz(PU@Y^CUuc=Y$GaR3(fKxr@qY?qlMN>JE6=rGHlgW%b+zYLex}uBnw^zaeI5pg2g-`J zLuGeKc!!}Kg$|NUZGN6P@u1n9c>DhjvdeEDE!sg+x=Lf)YVKIJ>;!b<+F zR>7oy$g1&%Pd%WVbJ3tD;KjO3ynTJU;2+V#04rX<9Ze-G18Pfz4w4P;^L2WJ>j$^i z&{eF-jd#k9Z}j`-#o~0l z?n48lisPS`0N&SiZ&3gV;g#CH6<=IBO95@hT~OLg!COz#P3E5#5(+~Nf0oc(g*QE% z2d{msx!h*TD)Jw)YP^xk3(DGeei{N^tjomfG^%tv%)A(2#hdKBRI>iV-mXFi$%fZq zx;`<#c{h9LD%PZQl{WL<7_$&xfxsXa-a|M3{3+VkHdcTaqx^WImb@cA&wlwl z>dx<<33#zM9j}GwA=f>%UR42Jj0oY4v(T5sf4TBYvo=%kUQ%?F#rw244?}&^E6G)b zw{Rs7-t@;7@_wD(cKe4c1#hu3dD`Y>fVYn)wJsCy)4j{r0A38R;*HO#DQRNuIt30A zbCh3L{sQz188;zx^7KHXVdmE)EnEJIg05ng8*iQIV*FYu2D$K_DikS-jL&}oycp%j zTWjGbqF2y+{AtA(j`z6UbyBBm?@53cBSLsr<}VeG?s9?Dtj!d> zwY{+0sHTzCE?wKV;Q-nWHOuW|53_8Kg zivd==DPx*TirXqug$|N!*`Vl=C7C%-DS@tHO>VpsUP$l}GYoR!b^G&oJzh0yJRk64 zlpk;QF#|Hzq<58O17_mA`FN@x;Kkx}yl(L>uG6YgZzI9^1+P|Iuej#lA~UC)Cz?zXx7dEH}Y{~@c!n>DjS+4!hOIN-&)OuSQ-NAdwL z23YYPdFv>-JWkn1=pfnfE-B8IbZGA330=jS+<2dT@_Y%GsxZif_fg584|-o4GaB$> zQ~E^b@GXO6}gzy?1R*H|_ znHiv2n<;puq@V0-m$)Jrs^N*#S5$a&H}c>uTVpBr3EzxY8~C$oyhRBIl#8Y;j|9A! zW#a8~UOEtFUJS6}y?np37gHyt)@f ziXW+UOaL!N`SE(@nUM<@JI~W>z)ZZvvHphuFBYfco%Az8I;CG!4Zw>LA-o^f91-vG zeS(+MaTk;}Q}DhIHkR!gr*ja78rW&WGZo&_O+0ubb*$u7<2@GsLspGfOKXSHqT9F0am<)chbadS2^Lr9CMt%u+_-kBYEy++#m2_meN()%)7;MwIATc zAQ#>qcSH)~p4MFfFGl(ChOOQwZr3Z&UFfW+ep;D$+dW-{R~xW69j}7uEq#_@xe)MT zLt;%ZjsLm~E4MUyMUt4GE-*F3VBB)xI%lR^Vzn|ZtT%#-}wT6ZCI6>D}HGcw4mAlNgM*{~u8x_aS(_<%OTW3wNSnp!Fw|eWe|1seP1?qTcfPHK+_}~4CI66B zCG{cn4W{ zopUvfZUJ~PB81l|%}63G2uanf%@n-;(P6SWCP^(}s6JXphpO;q?%=`ewAe=8wp$0i zf5@uwrtgeZu1u_240y3F4ey^1({#ELf?qMg04v_@4^~J@E_|~RI!HFW9_g0E=&-drpI)Ztk)vNQJjJo(J#eNtW{6 zS7T@VLspH~&~b~>V${N5z>9U6c%53UzXxkx46x!&>)cebb$GW~LI=r)xAbzgWKO|H zU+5~<5(fyf5b57dw1P`=D8yDR{$YwU#|GZG;cz_+B5pR)x1}HxFL@ zgJ$yYKGX4+J^rj3Z+^d0rQPloMt~QyOuUD-oF@S<23YZCOn4>PGxPCbz>7J`xy0MU z$<8iBJ-yjupsSeW#=EaTXC>gpAQ#@D6GV#W6RYk3UX1eNt^0WxIrCT|Uckg1PzKDz z`@*xsa=?pOI^L4hC(`!Iv)2G#j0oZNAO1mnvreXgW^Jb6?KaF+w#xBN37p%E;1NkG zysP%|;N5FrCSRg^7_(MO`Lb%f^9?5{GbPq-0WW5mcpEgg#1BVcfEDlg@oAC+%E?hM zK+I9jCF0HcG=`9^IeZklidk;Fr$#2?$JH^&g?Hzls}0XuSbhe)80E)Xb+|bhol!4S zvjH>lx_o+-26(YJ9dGeKUFn$Dkx76TBSLtWTo@>MtmyPevo=%kK5aN!c79hs{C%dP z(~B$>-d+26@LJ2Pd%Ud%G_27PKGhM5-wta#rgt(GKK zq)iYyNVa9em%Cyj^V;P^=qlFa#=G#KGyYKl407SExA)J(=!9FBSLs1CVUes{44Mg65Iu) z%@n-bYnaFy-#LB{&aLZ!5kFLT3zK>9#u=H*2Mo)=>%9C~HQxNZ7RvRHMu-6~W|?^1 zGUhDjuT^SyndjhF7h$ONx{No8`+JA2B83NUR++I}uf+t{f5@uwhQDgBOnLM03gE@M zOuRFLI{yH?7+}RadCMkAtp{!KAuG&LCL&z(9vfvyyt>gf2D*w_ZoIc`W@rOm407Sk z+WzNr43lc&gE<)G$7?&sf*heg2G_i}1ImDzcpZ$tw+6hJrQVa*YP{)9T$Gll zbD{t*)@9-yJ@MpDz>5J^yk~=MN#4FsyeV{$Y%}k-HFbz(W%uycV64fFcTj_0rhpfN zTzFr_ixgX`KDxoO0i*nQqb>|0`_6FC(QLp>yeZR8l7JVB)A8Qb?JnIuDohD@F(QPw zMvHoqHBs@UfERZ`X)^`yjo0;L(f)QlV5lZxG5u9|V~_ISja*|U@6pwM{y${Zcq<1F zR;G1*d=2noT^im$ci0XuJ--?7Vt^H|opyv|gw9$Ap@U?@Ytz|;Xd1SzD|8iWQo2f8 zHZ=bHh@RtMH~C=fP{AZX~~$ zygdWj#Gh5;O>a`7JbJzUNWhC(Cf=X)T|=pfnfdM;>4JPuvb z0Ptc>N>^!k-Oa;m0bUGp;k~_DqlppWjX|u@jBaCloHee>+YrR%l0bVRl z$2+aPtIRR4_9(!M5h1*b7PXOliGKe@vo=%kc3WW~o7}NDABOs(&b;L+yt!#Sc>jD5 zTmB)i!H$2(s_~Y6zoWctB5J^yt|B_NoqC=xh`~&Y|S^S+KjuPw3&i8WYB0?qmr%(Fw{*;1L9S9 zOHc9O&EM2W?rQUH;6G&5c(t?&lussGeE_^zmx(ua&=NDiivd==A-=VV;@6vTU4%Kx zxx`=C>aJ=?TyH?`fUaVe(pB2byQ{c&63o093CgM`pBNtx51kf7!ks|^L9f?!qPQ5nzfmN_h$d$vIidw zE(5@$``>4%@P0kbgZJ|$Be~9}kpcgZRpT{ue4u=Ltt&p5gLRpB+ql%P4|p-ainq~@ zF2pkDd|Ve{j&d#$?}i!8iB?I(ROl*Zx$#!#6ubhw805lh^yk5xUdPP`0bY#q;~hJ+ zAvtI6%s`>DqWY(XiC3}A!x`{maXQ{Uw^mAfIn-0JH|abNUZ;Xa@>bGQ_yQ(>R*ko)`A_A{ z^A8&UUd%G_&fmI!CEèh6kro>v)LAWl$94B6%cQT@<)iivz0kf2@((v}aerhh@ z#UK~nYDba6A$d_Jz>86Syh%@6ki;`>N1-#yh4);C{5Zgi#p!s9YHxNOI_l|Uz>5(f zyxU&3l;}J;y%+w0!(C9?Ou_qlavND(jmR<>szdRrhTHz$q{z(V!CRKxNPg|9b^m|J zs_|A1{;169ST+stVqGR)@A8UufENR-c86SytN`*kt140AJc5W%w>blyq_BYFBYfct@U*% z5xaXpKH$ZO5Z-yN(Nf!UX1eN9onG{=`*!FNV5Sm@qV_Rh!3M< zaXMcAwi~1ebNAH+yciL}t8MHk=_PYJ33&6fs0Jx*rr>?@*+mvVdUgs7HD^xeJ}SIb z*?f3k8p*4_EAUZS{;V3WR@gJ;a-$EM054{lc=vS?bpyN@V8uJA!i`WI>U&>kfNXe+ z62=mG7dy(Jt5}oLRT^Hy6y-p`i$N~Dv#WI#zxzsk053-Q@p>1VlS4-h!Y58}2b6UZ z6K{_*fn8zd#Vj4~$FLpJCn5F+053*_@J@IYA?ZK#aBa=nOu_4N)LfQ3b>{&%x2xK9 z@KfPkb%_UWq|#I#9&~5QKV;Q-NJ1PopU|w$6ubp7y=6r=>k)8nV+KxM zs=~YLG7nz+Y!i9DulbjM$g1&rN8VRjIk)%@c(E=M?_iw^c%2smtauAcOC%$MYCjP= zNH)A~*E$iY=W-pPt5}m8@A1bi%m6P2x$quy7bz|m?hylCjPm16sacbpSal2+`M3jK zyu+Kl#HY$IOUK*9=C*5q*TN<+^I}8@@2neIl8R+3T4~m13SJu@E1BP{<@i*YejU4b z72fo#Ja~ywCi4A0L-12k{8=^L^d`@g7U>HP0ba~9@kTVg90fBk23YatZ`nZje+nG} zcriygmw*51SAXJE)Oab;uU&{MbQQDQc=vcOYz25R$c6V)eO-mK_Tmb_i&1{Og#n&q zd7rPnH5)K<*-+BFK3;9W;&i;L&Dy&@o15ngcrhY`w zmJri3C)o)dB-_lp(Y6;+o#(R_x{5Wq@dhk8aTD-jkPC0cD_w=B*TG1@i&1{OQE~mq zgg);0au)7@^3%%1J4UoK1C|Y#rQ@w_Y%5!1Ke80?VnhgU#M?xg}0)B2k(3>Gr4!wK>Um`e^!mxBmK5A!fJ&A@M4yUcW|9wrvNVo zSn*2FI1y9c9*Y$kARFFyM!ksxdk+LdSFt8H-mudB69F#^F)VnhhTReER>>9~Scg3v*y!=@;-m-a*l>T4b ztpG1(nRsuUIfkD&#Q-bbTH`W^8~NFJLI=q<^M1G(L!7)lXCibJYjWd___X{P;Kd*p z-t%Hz#f66f1mMLeKi+gdQ}Ri z@sgn_r6SGROu?HnG*lMrz5X%`wQkvP2NmAbJ3M&H9@dw8tdrw%l0U1)tEE+}+&b#@ z4#109Cf>#=IlW=##Q-bbVPj$luV>{Cg$Brm*WP;x5xAhWDRdQUa^s!<<2U|66%2CW z^&hOOIHjYv3GiZ+AFrKjAUU{K&uS zr7at>3RV}u%!@%TyrRvziuB^CO2CUze!OQ5SCS8xzls99xC6?7nRs*7_~gROi&;9} zTKCQoPmMdq173^>;Wd7|QZhg09KQOFyP&k0f_L{iSJ}0*R|msT>sjYbRN*Zx;lXR~ zZXln&vl`!F%8+K`y+?-#Uu159e(Fycp%j`}FHXlDx3>qtF>u z{Zqrl8z?!u1n^>UI^JvpEmy-CZN~#%j0oY)wuqNF&F$%=S(_<%qpz9Blw0_=6n|EY*U9Oo@@H|$BEXATCf?vge<|R_04v^> z@f!%cO8YiK17yQHATg47zx5n0#;_(gUd7^^p@0{ITzHGt>L?EP*oUtHVU!>5aw})D zRrf2OH5)J!@14r&2LLY?r{i_#^pl+V^K~Z7yciL}>#@(8`279JD!_}optPBSS5enJiHzM)fh8&>*vf+Jb>QC&+X#NtqiZv-+r7auo&OU1ncrnO@w|iGzMc2Yf`LJxj zC_mo9X06DPA&qcK!5#35Vnhh9`K*PKk{{`HHES~k zZtjUeH*X6Ab0WSu*@LoKrt61+h4gY*A zM)~ocl{u3m2F%6V!?*)pykUV+>i{oi>3DtJYPn9mo}UPKF(QQbNw+{r)P&XD059%> z(q;_6k*%9NN9Z8g@V$%8z0QU04v^>4=RbrT{7`CAk0zDC0=caII@=bxPNCe=qhHp@fO_mUjTS9 z$c6Xx4jo0BZx?64i&1{ONe?QB%|mA5(<-1(9|B&?(((TA%OGAqKHm>! zUW^FgT{GdJh5yuBNmkhLb)Z3P2-`I<36wwZTH@j)WyW`Pp$ zVwTcX+RSUO(+gjH#~>Hp>I7}Yg8r}Z1x$?c;kBN1N1{_4s;^m_DR{+)JIflKibjAP6Qg^o@b0SQ!5ewTRKDuH z4PL3>&#LiS>upxvD_jr)crnYw`|6sDIpDqLu;e}-oP}fK}wq`czZ8;CB6CG$ODG@L7q5Xg*W{T z58nAbOywa9o+DoVtQv1oLX`4Q&N_UD4YN$V-+UfC1H2eu#cO`yE@54M-$iJEY%}kZ zHoJ*#hK)KvSFt9gtF)Q7_mhfnz>7gHypGGY6-K6d4Pn`UQGUE(S1yTn-*}7PK*AkR zep;D$&%eB926!<`$Gg6Mtm}oJ#W{c%BSLr|T}YGkubD<_)@BOcalN&A97-;Wfph!Y zZtWr!-oh##y!oLP^3mgt;|&h}tQxPA(?Vs-uMYSo1!kFeGdv0t0WStv@rEyGM#g7N zvK1O28(xR$sf1VbsJqZrtjUeH!aa97;Kd*p-s3g26{3LA9|12$`SBX;SxOdv=!{nz za0k42Bi_u!uS8;&jyHeJFVdtSqYCh1L49T^Mqvs)@9=DUu$D$z>5J^yk0G|$*|YE z@gXbBQO+eU8)8;0Cn}e8GlZ^UmK(2Af zP08nFDflot?tt>s%EUW%^>tmqi&;9}KaZ~wPZFfP053*_@J{bhElIxJX9cv`$A@Z= z(q;$=S=%$-0ys=++@H)kt$}=K+Hu#6E8n2U6s4_441AeOv>oW2F zc$$74@M3@!@8#X@WNC4pr_e#N;XU|l1+gMP3;#4D)}(Zmw&o4m@gWPA4H)FY`^Z*D z@$n;B81m%!*0pS zu>H>fFYbcUW(rg1rK@70sEofpy>J$yQEp(7niQ*`9gxY@n-HlhRchUcD8wEdehE zx$wrF(^g!o-{&>Vycp%jJN9)?vi_;|{+bP#IrDBFaBMZ;#o~0ldscZ$v)gsWFQa2b z2(SBK?bGScr80e)3E;&jKi>P_y~#Uo4qXyDE2^JXCf+5J_Tgv! zu{a&?+KMnDM{=PH;Khg#-jP=?NMpp1#f9kGg*zRx9~-S#Hiv>I#Gh5;J$&i0vQ+PeHO#!2W#S#)p`Qid#Q-bbDe;@hInzd12^}Qc%sa{C zHqq)rDdNSN+<5Osba?`JG026t(&|@cv9Y)n;Ke9E-X2Ap$elAic4{_YCf?ewwa&uK zi^b`9_g(EFZ9S>^V!(?LA-oNxza(y*CXEBUxC=^~DR?^?c*q_}znz7l?%wvvM};?P zsZQ&^6I00afPm>UL)-ZV`2_d|`b_g37igrfYb4j2QiA_L@n_X|i<&=FE^<841@K~) ziC1#^z!Z@}+zZ@`N|F1$v! zsxv)SM)m=`80E)X%hZKD?iko!vjH>lT6oOw19-7G9q*RJF0P}-w~PV27!kz#vq~~; zctAF^xmF6*Af?R|yqR$hvR31s;5Gay#J~kAyh+P>@Y+`z$q#SwoeXW_&#LjJ?|h}S z)HcWhyqIO;wQ6IAR~s^HCx=O=qQTg5t z@M4e)@3b&2Mci1o@qibj{CJCh4I^b?kADlD6|QB&ty)#-fESC?@!ps^hMYd_x<25= zh!EZ<^;0D~E|}x80e3-ZGX?LnQbJZTZ?icJ)$@IDtO{@D3Ld=SH7(?$a>RI(fmzu<9`bOa5hHy@#dXrKz>?%I#;s+GiP31&*j*KS zU>H8zfLTgcX?Tr?B-R7G805lRp8GR%yse=J%)A)o$Lr!4PQJ=)pDc7nxn|yOVaM=8 zdsv)~xBXZnX%E|~Ie-@=zCe))B;tMFE> z;lb;dY$)G3+XG)X;m@k^x|e-Yj$eKcFO^}IiP!S+v}u4B1FU#=_uWY*PwayaEMtxn z@8sM>;%;XV0bRu`rK>c&S9{-B40tifh1ciH&&)z^yF$Q=QGUF+ZKjh^UUGal26sRi zFmvYJexTJgn0YZv$Lrrq>{@5$RwKZR5h1)~sqZD*$&$mGwV8tV*7jbqh-)oy_N=K} zRjIox31e1@M3@!uV?Ib^3mIO ztKg>-bCh%W7ohqpk-ax=CZ4XCy8yb1S#G?mhMJfFUJP>KjR?|GIG@^e1@K~&A8%&Q z-sHmV4tT>KcR(316Yr0WeNF>j%+m3iW}Y~^)@h{{;Khg#Uh`W<CC3E&Xr%7)fK2rpE zF(QOFc~geuMsj`pJ}>Tq(q;`ICz0mj94d zZ+vrEIY``EFUgAM@X1`CHW&>V~^5dOj*o$nr(mYDD0W*+jksyjYx$cgF4r zX@mOF_zoLJgz)Y=l_x1sJRPlBn<;q9CmYKa^^3&Ipmoxd=d19B#q!|wzS>w`Jw5_& zaPVi3CZ{sV)5!8i+G5MuhNgeSAUU7IJoyW^Jb6^%+abzCKRF2g(mMY!Iu$8ym-iH`1e_ zeCUpT_--SAR*knP;fivdv1MJri&-XK=YrD3fENR-cpaNwB=c^i7Qwm19OYc%vLWzZ zG|}0;urG8Kv)p*wMQp;E7lT}QJtWncA>QZn053-Q@ovf*L$3Phinoq%2b2Lb@s506 zg?|kQvvj->;eA|v+%kH=vH>GPcy}~BLWHF4$4h0n3rd?Qcr$gH$_maXmchAQtGDWe z3UBIm9=z5E8p)UUB=i0utHxV-{l4&^>_siYW#O#0r`h31a8DXB8X9byp=KC$k#;k zIH9w`b+ut`^|d-M^I~y2-c1woT+JS~!9Qh%5h1)c!hT6!d_9MM`U7`CX)^_{a$T4# z*SgnA80zeO=L%JLb9eIK_3L9O&uBI~`yaAuy!m;>%67)%5iizd;?=P#Y7BTWz=}7v z-F33zx&r)rTbSd-D{34|L>T6M1iYA~bd`qp%mf=_z>7gHys@2sWhTk&s$u5EC_mn{ zm6OSZqPccLXN3!IP9METfESC?@%HoZAjA~|rozmN5h1+YqW-V4I}eMh+~WWaZh$O; z4O@C8r-D2NDi&T!CCT*y>hN<=7x#IP_GMY({ALJuj4fs$Je>y*kBL=cx@Mw3)1 zm7wB6f*T=lMN$$0Z%^|)bI zD2F^?(~a*cF~^H{n`9s1*zw<9s48ap@#gzVZv$Qo^5NaMqDK`%4h;vq7!}6r(H2hT z&R*IgwxfJ_%d1kN0WVI@#9O`3+Sl!~taQMO5iz_`#`RLyXYEn?m6?Xub%Y(IG@rHx zmfBzuZF2nYFDd>!A%Hi#(o`ODeQxalvO2ucal%iUrxlIzok7oQylMI$&WX)t1SocVvrAStADR5rZcz#@M2ULubJ(7 z@}rld@F0i-(EeK4XWm`yE%+QZ%rfz=R9g8a4%;0DcrhY|chUVz(&RUm+v-| z(>~rIfu-Il8bxXG=I06E-4|>rUwh#qUW_iB)!`jpXRVREo9PL7G0VnV6l{!-vcdo- z-uqE0=Sy*~16*I<0U2FV=a@i}Zb1g*?8ymbqms8HW3ye*sS_laL>@jf{zfY+ar$Qy6; zmjZm@?Emq)nP@IWGA>5PEF15LkZD%|F9taAIxLzco476)KhMJ)Z7=cI&=7HysNbtH z1-zK0Rh5Bv<^{(Dz>7gXyn91>R68;Yjsjkc3gfLQ*iL38F8)evSNM(%nYWwq{=7Ij z6K`ynhi};yc?{sih#1~G`^uyNL~EOVWv1a>aP@7fLK*NBmbyIm#J{z8lM4m#RvFvL zpVqpf3*oE|Z`Pp~>Q{X>v!L^0mW{VgR?-T1F~Es8IOa6zoO=Z?-oP9$UZuwoB5G$f zK9d5o{CM{rukiuA805oyXF`u^to@M?z>85~yrs$^z3R-+mT16>SvKAcj&6A7#Q-PX83_im2BinycMfyBcsCp7 z5egr#Yfx3p(yGenyw`V)nGAR_$cH!d~}-#i%gey%Ua+mG6zm%jj?b+Jf1~ z2CqqlUVs;~OuS`r*JWvM8!7-VM#S)5APc22dp$SkS7sXCEQ>#U2Y3jo%WiWV*2 z(qaL;P3uR>fA}KHVE|bjUWcUL)gMl;#-9PlM@e;$GqYf>bGDv z-p8vq`vG2@oQYR%@}=yoOVm`rixDxrVc{pGML*==M`bt!t;{sMA8xUxB4%B6gr(j} zdN}y&zrUpTu|xoG_RkXem1asUh(2aDs*0)myLJF%U6DY7XzGlJ73k2 zLDSsvX+W5xH6lFoel+1Qaq0nC4=n++w5l>XZ_KS`yl(>r`S5O!>{DHxGDZe?F)ECA z^wurpr3Ln_V!Oh3Y^XJU-5v1aszVnhtD#Ofz$kcm@@er2ZNwIZfc z>B_P8u+$T!wGLXmEu{i@lOEg1>#jMyH-M}TuYc%o>d+|-_$39-%f{PcLg2;d7~sTv zZ_^!e!mGCe#9ky<=e4i+g4ozZX?)gq;`WW#g?{ z(HMfA7XqAkGxl4^>@S$%!<9K+Bp2R>hyciY68%89Pd;X)?B(|e`o%i&ardq&@lQZ$=84d9(uJ^A6yciL~>v7wF2sCT{ z8t~!}v@+B1?hmr1y!#&Gxz*sEj-^_>2QLcX%^qSa-}OO_8I(yltHbMF)S>=X>J|ie zG0VXF*RzN7%1;>rUJP*Jb?Y~hIk!3C`xng78WA2FehEw`QkTvzfvRGbR#gVxvgRYc zfER;&cvmgxQN0&m75rs;S(!y#y8rr}L*@uoJqsPT?D>ZponE#AV*0(ghNW-IrI{Jk2=B%IaZ z^>6A?|HCXL3h-i=`5}B+aDsH*hi{$FO$pN1e86Paz1bA^yT2&c% zht>x>16~aB;f*}ot9rNpQ8VDhs4(6^F^OcdUn2fjg9Fh1TG_{jTSdFl0WW5mcxw}~ z$@?YCCjwrKh~X`Na78*Tc(#>(Wv1c19X5ixSNx4L?Ct)Zv{WtL$_fFzM5~RwxWv?Z z09hSggM?RV+cln2z>D*;@jB06u@>-RfD`YtaXsY1-jout7s-X!EIE^Cj5AscRmC~^ z@vitb-~`~sARpcdgL_p*H*?kjUW^Lk&7T!QM!U8~=(k`t-qZ2Jj{;ttoQc=1u|sB6 z=#EbV!iX5&F@Ii@u4r3QtY4XFcn_IQqW0gYeGQiC2N z4sXy1Lye{Cr&7R+^Rn?qbr`q;UJP*JwR|*3cIxh7ylf70v_^!-hKo~jiJkyUL#Qfd z`SBhuKUfcVG02Cvv#(pV`(D8)z>85~ydOG+lYK#V-ly*-k)IBIhF|#O0JH_OJMXogP9@;Q zEEBJJg}H3_*oh&47b9YL-@nl*{UYS}NGLN7K`S#2@36zh)Y_-HKCri=&DZ{>#hX?s zfHx?@Mjq-vuW|rc9p0dQ&(xdF#oYzGI4>J-drZ$1z>5J+yhq)}%cie($D2!Ij<%QB zd8h6uCyMS|{t*VSO?=97767XV>53f&Qrz+>uuCss_qr!NNE0v_`;F(^rUE%Az zXMM)o0bZP(iMRY-2K90G=7WG2BVu?PV=Rg7D^u|6VH|>1W*XkKiNmP0bFIez16|vi AaR2}S literal 0 HcmV?d00001 diff --git a/000_image_stack_ram_based_reward/logs/PPO_4/events.out.tfevents.1680177771.DESKTOP-9E17TO7.35060.1 b/000_image_stack_ram_based_reward/logs/PPO_4/events.out.tfevents.1680177771.DESKTOP-9E17TO7.35060.1 deleted file mode 100644 index 4fee189dfce1969e66eefd37d6e7ea6605edaefb..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 46983 zcma*wd0b5U8wc=0qGYeE6=hBPB3g!Krq%97wwq`{dy=?OmaKB{4#F zN88>tG|1mSXkM6+cd&=Qcc4dr zw`ZWb!nq!z7ryIu^G=3(&;OGg^j6}4l3KtA=RU-5VA3e!!pD;GZ6N znB7&ns&xDv`(-3FD0qQ~f6&~y>Yr>{6m~e@*xTq&Fko8GF;K6UindCZKf#D#|6hH2 zdwGO=hR*g3oaz1R43=7c`}Xw}pGN(?JwpR$2l{%1dWLzczxtYC^}dg7WUoJk75}OE z2!%VTbWl_J2PT z(g%pFnQrrK(cS(q+B4(-uZ zCK`~Eg{eqq9$e$FVEDqWfRqeyA&qyNYAa}0ghPmq zJ)cJDNG~rsTL?(W!c?TAO_n)7`!Q=QASDA_NL9`K?N(@e9pp1w0%_2L-Ogd_wAMn4 z_O}XmOOfs$!i+SqVzJ0%#|XS4VN1%8R;ZLowpk544@k)*1*t-;u;z2UB_Ji2%SC$R z;xs|eD@7&jjmbmW+IuZjUF8Q?e(}+|l(x)P3qzb1NizHLq*YQrukVeNpkhp&Jp9@IInpC9Agqite!vQI|TrSd6 z&)ft(zvgUZKRkIz|0%K+92IHl#Vo~^@Qnwlq^g|YU~{Coc;Rc7eGn|xR6Hbtg`+2HRlnZ(Gp0D;_Y45 zkM3gtEgru4Y_Ak)@)%~MW@d{;N3}|3@lMK+`b1Vr3L~700I5pV|7%i^Mn?;yyPXmP zQgXRmq~AtW+SRJ3o5JCdDe03|c}NFUn+xtwxA*~*B$LcY^PEl20#Y)@gf#s6m;%)U z37Y^Z8DvK~>_oE7&V$1r@M)Bev|-ORUqDJ0rXuYXTqZUPI5r26k^wHHj%m@htE>-( z@EI+Ew8!Ju&K0{i;uTG@-NJoRr1z&VBTXL|B1+QTaSDdRmXsk?xb{?1UZ?#DkdjFX zQia9BO#}Yw14zl`a*+lFY_}EPI$g|uc=C{jOir|$dD!hcOp>g}jI>XpUNRshV@ybQ zZB!`uvDU{Dkdi@mq`?t-w%`6L=+CE7I@0R1J~sdn4(l{8c!s!2NBSuRgof|yEfK(A=K@1tVQz$D3f z#3U(CoPzSR+5=KD#)Py}^0WN9Y~4&iN(R}Hj_H|Yo9f!efls4!q{%8>Hvv+zFcqm* zr%=bY8nfyFDH-5GTHEE2&9$lkKR%-+kY;^!bNLW{Fbi5#P~Un`iu8IYGg5_NQ$-`K z)(zyHlp)oreJN>nEkGBLk~OJF7YHLK^|uA2Bw3FcsmJ#HMSzryF(KV~c}%|Qo%uTfDH&u(+GyCp&Q0xp6rV=vNNr!mHUUzy zFcoRg(dN$EHwPXBq-1~#X^_)in}(#Wi}{R}K&mrfyvvEn4?Xq&yonIoy~wq7@1{M6 zrARNVQe;+|erSZ~_1#6+`A20;b1JJPJL)!V)%jC(z}tgkuqxGQgz(9(nm5oK9Hm^S z9Zc-3=jkuBju{4#dvtX~w%GdQHO#dYG zx=yIU1eaHbjXQ_9-nSI;8ZZI2?qZTl^xxgbLz~?yjWeWRe{N&}>vmBr8spVPjek@I zR-w(ml92r+wmN_Mm4bz;RIu}fT~qgU1hBAPF4(I_LWf!po4S#MUu&38Q9}ZxlG!^WM zH|rgD)a{!JU?IT;wwY4ekhrV?w!8*Rfc^BZ*d=K6Qg3MU{)xh)Qm}a`EMPCTwHN6f zFL=T~Dg%4`$iEWLL931fSg1+`8!o(X>2e%^h4pg5rdZ@zHw|*X%W;JAz#aHA@Fux_3XO^4Gl`{SSbJBscWHA@FOY<$c_01Kt5 zV9U!#yNvLf^#;H~f(xu(X)7Bg|JL{`3?6|PFadUbmY$2V&FmUz)BIayrWEY492T(G zbFD?4)1QU$kIKL%zp9Z8tx)v^uuzo>cAhX_N$D1Vh4pg5F7MIN#@E*!e+NK}@g0DR z>K?Y1(Q{7$Scnqyq`Yv|p?-8NfQ1|r*hea}&(`kj`w+lFk{#?7g?n}Zua}2%oQ~f= zopi8ey;n{Guuz%`w#xuR=bZYY@c0TW<06Mip*dIk;AqDSjaJfO&QfUf8)nps{kw{*}=MBFSA=d zWQ7i|X6az#!qqMSSSU>eyIpmkW6GkD{s0ydTwp)XYi|<~a<+iifC;cqZS-6&T+SE^ zZE7y{(|K1qN_AO=i;4SR3q zqNMmK3ffG`I+r5_TUE{i*0Qsu=*j!+(0>wvMgcTC2`0$8X>%#(6Su;h78TL23=Ca_9N{yBU6*S-4y z7Lx2>C)eDy3pxG(U!a6Mas5LFo7~6K48TH^3ig=blS7W!r3}DAf(vZxRb|$_i$8th zHDCg4s7o7{%O5@{!#Ul#YFe%o?2Z>KV9n;5i>#DlC-9HTz^YArCvn?;rzL=es#LJS zLeFR2DgZ33mkYN286yh?_eZ@rj!+(0gH#VbFCc|t{Iu-98nJ_leS#{~AMO?+Nm z{D83l7Lx2>b>fr+hx)Ym#;aL6*dac{TLD-oO$Gb9qOEf`$A_-~EF`$V)+##={^;=~ zkk^0-uz@elTs~AB4S_aag;nNB!Issrfc0}R6&dDD!Y5seTWhi1v2>&J000XKF0kFt&9Tfpp>~_s zfC;d5V;(sN`4_oEoBoNuXQW^^d}9H7znO`sD0);q|ELUX?bCOXFwc))04!9cgOzBx zhXGhvFBj~x?Ox^+zXXGOBw92kYfU?Sg)3+@o~;801HWW zuzg*73nsM77x8MA4mQ5{+F$?+rKw;o!!levLRC`$EF`$VHZOQ<*=A<>YF+~-z`pLG z=CWev5`4SLcI?lyQn1%nG-G*d*2PG)W%A)SFd^2c4D6HswURG^3T^-vqExWK!m7iI zE(2ItFBh!$wN%rMS^FMx93d0feD69lm?u6&g(N%JPB)zd zBi=aR{sDQ`Ctae`cP#)cM5$m;EAuHZFb0_-u1^UmWR zrp$$Nx^<*_p%iS!2>1Y*Dh*#41j&Q*B} zw?mtCN7Bzr!TvbN0`{+FgG3tX!iD^!GO#`wwURR)=`8^)RHcFq5`L)7a{;ihUM^UX zqMg}B?LkjDj*toL&hH7EV4hHsm?!0BE!{)cTmUTOn84B#!0K7)i-y*WjO8Ddfn9OER^r#>{|dlDRXW%U18?DzE?6%Y?D)8? zM%Q<)JIir|Okgz+D|dl;LPch<`wiD;09eQ|fo*HsF*n=gco=|%Bs*ADZC^qEi(%7w zHA@GZ-*WhM01Kt5V3oG3ITZzcI0|4P!3B1s*>JO>u(i#24VVCH(671kJJW_9&}RL` zs~4qU8_%(T?cIBz$m7k+GX7B+*sL$LlD3(*{QxXfrGvHTw)+L_u&`b(*z&<`4bR2s zT5=pA6Ii9yeXU@gP>~tzq^mcR0W9R0z_#wBlRLs{(h>j*Np`RkbOHp`kaYMS;} zl0L@~GJ##Lqt_GW2^EQXQZ5Ou`g9)zU?Il@w)c7W+&99A+W;1l>|mRE1q(JS_S(d& zSvuH}540`;SSU>eJKDC)(Q?xm7XS+hF0k%}2Q2z&e!%y>;Sq=d6JVcyd++30HV`jF zAAWjMECu_fj0Nnixc;J)GOPD6A=ao2tkAknqMYyP0AL|X2m8G!bSr>`^>V>Bd>%RY zLUri_jw6%@)*@ofkj-`ZKL9LLB<4v0n>k(29Kb@33GDE+R=G19jPb2mNV0=n?HDSE z_S%!kt64hO#(lGr0W6fJg8l1@uk(3}Pi+A#B)Gs1xqU9D^TZ)Hcnz2UyCZ0e(}nL7 ze4)*f0KY3zuxZa&z>2^06OCKon8`mX13PnEo#a(|;d}rKRq0^w1$4n{SXeI?Y;lH> z@s_G$eDfG$#49~gb+T_}Q~337?-r*fm?uP;!G=Wz>;SNkV*=aknR%|JPW&d=VIj#5 z_U65L0{;rznH;C%_fIDs?Az%}GXN}#zP(eQgcT#;oK{EzuSvmf|H1*;vCX<*cIC99bujjWd<9ZK2Q_DLXHWnYEHl0Vy*NB z01HWWur*B!1fR0H_UAYqOgrqTa{api7D`jW>g~{T+?ucd2zFRVaDnaXzsB4z{+%hW z0TW;s`%H22`*z|0w3+1j^STslX-sqGw`NZ$_7y#HS$v0oR0ekKo;u0?(QeBDEL5d~ z^*C9e1z=&lT(FCE_ZUw*Jv4~p2$^=+{guWNm?uArKw<*N2fd3ZXIO>U?IT;w)v@Iv(MX}Z{amy z0_>wBica$)z3|GXdFLHBrC`^uX94>@v5#oxi?tCjA=ao2tU`93#I?D81Av7n9c&BN zz>NTQh8}U0a=|uPH8W1}{5%eh5Mr!5?4fOwcfmX%$_#d={gE307II8rOFkRr)tL!b<{p z1Y*Dh*zum~PU}3+;j4FUWfr%kU`uwefZg_4PqcAd{%V*IYg7g{wxmvC;L?0FfQ2X( zY@l$RQnfySh4pg5-q2re+}X$|i{l8HcGx5JKWqRjR3zp}d6mGqyQ>JmLXHXSD#gZA zNzG;?0a!?~gEib5DG=u@!8?5*PyBS!!9JH<_5rXErGlNeL)Y=P?=b@a3kfc;>RCzV zmy9}u@ER}yHhAA*$2OM~+rT*;u&nTo6zqxvEMUJR>4`qH2%5n^Dg#?pQ74(z`b8T6 z3svc0pHyD*0I;xLE?AG?uEs0QEY9UPLME_rL0bmGJfR{pSp8xlep^4}n7~eV8Il`* z;zC~l3rTjcQSOTb+Djww6PJ)@1#9noJOaQ%lnVCp&lrbkdp2wau#n&aTj#argwu(g zqj(LN0P7rD;23M(65n6#W#@EH3if;!3)n^*J<*i5tMO%d)~F0@^qV?Kf?w%=01Ht% zSpSgL696o%mkYLoX^P22<;R}@EX0U&NPp60(EY|ym?uP;!ImD<)P@}va!g=_bK2+L zo4jl|fQ2MG*lV{I36`~xyx`R=eTVhB_xS^Wh0;{8;{x&={Pb%~0W2iA!0PL4J+Zv- z**snYCcxh5}OF-fR9*8Cb(M^%4cs^D6)>RHcKp zsvI2)U}3#nu;Ep&Oximg-pO%$A40$9i~fgPX}o*Q-~(+j{t zk{#^)ZHomaC(Ur{fjlc%l@%(t04zkQU}pvRJJ=|>=>u3uaDmP0XnCSo$DtGk92iZ& zBL+->ou=aI*m7P1zH#uV;#Ij6?E8BxU@IGYi>h>W@I@oms0{3Gt$K;mq78Tr3sE}Q zTBrC#01NBof>kc)W}4Las4akn7;z5imjt;>`}Ko)LX?;%1F(=}2Yb0_vEYNR)kt2=(s$VQR=pMhSSU>edtsuP!-Sr(-2p5lxWG;+Dmk$^ zUi^;NfC;eumD@Ycel~Otw0UraXN44OMimR##Pr^xrvbO{_Gs3q46Nh8ddU<~yBDy- zLX-~nQmSq`fQ9vP!InPNFbjzH(&T84X@_00q}C7S2^E>aR{I*509eQ|fgRZ~F*m)u z%@zO)Np`RSU7`e6+ZUYU)hr$CsKMn!0BoBi0s$55?yfx@))o&{1hA0c0=r{K(#hM+ zIvc`(;Sq=d6JR~vdOF(n8?*)5)SdX@p%iR&4GY+j!rr3A#p4b6M`d8|53QFxP|Z{Y zuuzo_c9!m2{7e_DmkV}mQ-Imr7mfJq17fT@tZ=;w-mVEzVxE*8R$Zgy9{>wECa_-K zfw>Byckq5#NV0?d);CI!Suwhi<8=J~>7;{Q?K^BQfQ8aju+^I84!eIoss^x--~zjC znRZT#!95!RY=SQVj~FlkwnMp+|hM$-^`i>nd6QaaCDPTXm zu}cK7kYfUS;Z1$+{$@Y-zzz#ZcCZ5HC_xM3gmhlb(!uJKYsCUsC`|=>x#}MWt;+1R z02UHlVB>aNJGuO|AdT0639#Qfes$=6qFe#mRN1ERL<+WYSqtX3W{bo+qVh!BV*XJX z*qFQZlKTZi>;WuPrGr(xzE&B)!g{%2wJ#@HIF^N+;W$F3O9H#|j%-MhRMZ%v;N=SvuG)?LOekT2Pt_)^y_<@$ux-_5c?!J&Www!jR0h_w zq(Ndm!r={og{pM0{R{470$5lt7wn;E-JvlfygqUqp**my2GtMkHcAcOh=Gd4JSjVD z@V>vp04(H~z^x2&W`jNoLu){)>3f8x) zvctB@efCD&cKAIHyH_n?I9+y|;}8tkaTi zqGMYBzU3d4fmIQ`mo!+v(F3qhl@507#+|AF7S_uJJ9bsHx%;>l_#s4y5$8~<4(^9- zlN$C6<_S?^o)oZ3H#aW@u#jT{dw-!y-o#zbc>orY>|jGeqXhXIj0bX@4yJ3^iz7!B z0$3`ed*2`;c*y_cLkbT)Z7uK^Qa&vZz1a9wKb0d2m|zwulOcHKS} zuo+vrh}Lh{jpHAcfz9{@cF0rx)_5A=Wtd|S6Uun9z(xUMJ97ibcl0f0t zzaxs7D`1{bkr{01gY9nsEaaHL>K3Hr9@SZu3Sc404))%?0#O&(!oAInS@^% z52dMKoxNhk?{6L417IP+1y9l%1A4z}do!wdim>*azS{Wjp3<-J#Z;T%GY*mUTZ z1d~&K;LBPNWd{4o(k&XmLXHV+_@O(w%SOEJ3Sc404mN9Ll)%;39B=J_Jkcy2tl8uX zPvDXOqExW$-WH4VMpummu*tUxHe6tf?%X%qQ)k;6z``RC117+J85HF3yu{=@oYQAl zBCDlf3yWF6PF<@Zs#Y$l~f(NZM<3l)iZQou&;9Nr4RLXHXSo(T_5_oy(#uPTBhJJ?Rgq690| zVhngSO9vbKC_DjnSSU>eJMFEu!&Vn{O#llCF0k&SwphIwxfgFZhDRU0m$Q_WJ~2VZB_iUSqo%3_hle z_fA5L_$^7lBuI&T{tduFl$a+4Z18(k{Pse~F@atFy)eglmEAztVIj#5_Rg6ofvNp# z{Ay~*6V1}WR$DyY2Vfye1#9WDP8_oS2mXx%NN|B2YBnSLPPf_Kyar5w)mk&jp^LHz zzg0c0W7~I9unliGz&>hag&*-_jRM#OO16N+%6Koy%2ItVD%p@%_-QtV>y6@BsfH`F zr+Y7D*Gj=2`N#owpvNQp)EjFQz+RuyI0bgt_V9%oJZcCa%pMG5vy z(7^YhAx|_*2Rph$R$BlIQ7Tvy%^PCj@}`df77|=w73P{{uPM#OYgl*$V!#C08Rr4IU?E1FLpsU1rOKcgqd8Q3Sc404tCBj zuqBFT@qSpy6V1}W>d&pjKgt17D%is7H^rw_j9LI#NN|Cj_%SuB*W!ps_!aiepMXaU zm;gIxyM@D4?K6kroL&~{)8dk{K6WQf!+4&N!Q1{M!NwlMCo9Y zwIc@sSXeI??E09TLANIL$3Kw+G2$H3!DfXfo`-otl$a+4Y*f1!_{}enV*;!8&%>P3 zh}HPU0VLVMn%;;Kq|aBx&jUf8XqFE4f#VVUm^VbJVEZVY5GOk(*a28baDi>-v)06K z_H+D-b9e+|zy#PrPhAI5!xQ{ND^ZL0HA=xgPGSM85UnoymgzGRtg}XCU=@CW9kn+8 zHGqXE9c7!*2@L^d4TDWmMQnUaU7w%R|yn;{d4nGj03Pxk(eh1?3#EbU$`WI z923~@{Ws-&-}lJ|c34QVgSEaJCGbcKz>j%Do)v85`b+L`NdQqQ*n1Q6!~-h2rvg|= zaDi>B){q%HxaAWV@QXDBJYv8ESWl~F4(+z4cYt$x_>9>{DcG%hIlvw{kZs973Sd3X z{EcrMKvg=}n>D5p02bEE1v|>)vf+;0I%|$2WCH8eXt)682^EQXQow##np+8AA;$zZ z@$Z*8r%jAD16WA1gB|)HO7QrmLvvou(sx*c{I2={7D`jWwn}mkZ|yft6~ID*3+%3y zz07j$edq8RFab7T<9G4EEA2W%n`W7(K1speJ<0)AXYxDz!~ts*z&5;X{t$Lph|USIL(Sr|6ztm59AG{7w4;2l3R@JwW=X2?BQj8x4%R1RPY(bK>*a#oUyz%j zyrVZhafTT2Tatbad*EH-T9_w9nZas5O&JbgA;$!^zxS>jt<&{U02Y$$V7He>37Tn5 zzrb-OfB$sS!B!PzxB*xwO$9qu*hcIhxy1>%^_5jJ;DB2qSbYEsIVP|g|2E~=t6ta(U?Is4cJ%WoL1D^7e3cRM zM6-0TDLeg!0a%Dq!PffyCAz)kF#eq`NN|DeqSoB(`|bTjyar5wwU4+Xju_fzFsQrP z%>A1bY|L#AurBwFEBQwOY?I%WP`D(3s&ud$lw0=%u&`b(Setg=k33lJXUuVgOqT@B zMOiv9PpHTY_HUnKO8_k7n82o8$;eS0V9+1HLXsV9#FHq&ok>aGcr{B0dnGX8Jb;DL zRIqO}*NBU!8Qg{)77|=w=RHg?F)=N~KjsUMKn$1w`_IoZ@szsq-Oy&tzt!KRV9!0` z0Nb&3=3f3$06T1&(|Q04Rq0?0X7!8&u&`b(ScAK-4Gq4lpkgU_z`>0NdqU?>GPpQ7Tw}VcAfPIsgmn<$}FusAtgmb2a|@fEaNO>0ou6 z=2XKxAxg}X0@iC`&0zowIVP|zBXe?8?TE9|%9UD)nhEfhUkmk)1$ zvXKL<`N(y6?>B1{z`ksnEdj6)rGpKru~`gYVZB_istalicdkCC13yv_BhDcm?4xs? zjA5P-Wd{2;@Du)VWXLgr?XySiR8fp_DS(9}J6OrnD1m>NVKlF1>0q-z4GIUaP?`!h zrp0aXus)0MPj^Cs3v6VXLiVQ2%O1Q2On|+W_ES8oW1u#)S@E&BnG|gOPY$rVbM8Lm z9|f>;_Y8h?Cp3n|#caV?qeCHU{1F3W#^A_vwe zfPFrp+du#dQ99VILPch^KB>Sje-2JvnJwHvkJ!D%dME{lx7nW9Gmm0VKG< z#>XAa9#ZTxi`Re&uwEOJ#i`dLr@%Q~;PqTd3ij1z4zNnKE0F_h6u?d#AM_N!LX-}6 z_w5TEV26eEa>2$Pb~0EWo`s+Pff#WP>6Zi}wrk-h4j{@5R^@n;1MIMnV*)$p-G!VE zoy>y(EF{^%{#z3zs2W%4&T%H0UWbiw(+dT#P?`$X(=S6b`ti1{02UHlV3TgvWS!OD WrwCx-5r_d3V6O(pixc~)&G;Xxac*n? diff --git a/000_image_stack_ram_based_reward/logs/PPO_5/events.out.tfevents.1680178207.DESKTOP-9E17TO7.35060.2 b/000_image_stack_ram_based_reward/logs/PPO_5/events.out.tfevents.1680178207.DESKTOP-9E17TO7.35060.2 deleted file mode 100644 index 6741459b308c4372971f723b722a290b4d6bb6a2..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 12629 zcma*tdtA-;9|!PbLLL0Ntt7IvLg_+GQRkd;j_xiY6U%Yrq&S`0=`L0#mO|M=E}>=m zk;|f#F3NC5X09u@W^G1ATRPG*<2R@CIKS`fd(QWJzWwR(d7by=Jp1(R$dA?c_2x^z z0)rc-je~>+cfBo#E|ZC(q|P%E#nSj`u5+E)j`3n?T#Rg4j7YZJIW8eOS|m$xPLf5% zi)GH@cc+9AQ4+DR?_Uzm8ohN;z3%ZX+qw#KxJiSg-k0W4up6p%hM{k+Q|V=25rEVr2^UxW95_oK&~S>bNPNzkS|(XpvZx z)MEM`{(=Q%sbf?V#m)YWWk5V`!8T_b#=m=$Ttu<4vY2GyDv8XuR;s5hKFjBP|n%0$u?Vl%yZ4{qQlufg`J znA=++wmE`5oNdw<``3spCN@PViHVCdQ{;&2J!Ny&x~PKDVODdX-e~p*YztK|Iac!T zoZ{ueM3F2?Bn=mvvC?XN2?0=OMUhd z3Y)Tx+3dc;%1#X&uK9kp@LttKRiI$~`ZfrB$R5qM>SZ^_)BJ1G943QmBJ~_qc?ysc3zLz4W#Jt7 z#YORbKuQegLfUH_%q=|jdJ2=(5|Hl5HVVix@i{qO_06$y#Q8vj8{K0@Dv@>;_oG%C z(j6wq+wtHJ=211%k_V0Q!<_wv)~c%Z9f#*&RgzOy2LDJ_a}Ep#U228uQP|~uzoFeu zM~B*^woVS=nXZ~+Gfvgv+gS4e?2wx3&`Aw-Kn6OcvO0C$sk3G2x0@!YDsJz-F2suT zSaTOfawH8_{TL0asWssCV7`s2bh0t$A1qDg+A!^NKmP2}bXQfvcKCv4n9$|*S?8Y| zzJc>xMhhl@HJs%g5SnSsfiaJ}zGtHZ`|Jh{*l5=P!Te(;YneyYV5jW)SzaZ-y3blQ zuM#X&C4)`p-~GN|J%EMtTEV(*7~s`8x&K@p9clx6|L_J*{>q#R*e6t^277nL;Wz*b zIV!Mb)uU^yZxnwIU?E8l*2pZDGsD!XlhLr6V3+^&ehz?z(qypNEnWd8shJ}IEF^S+ zoz`4mGqZW|W=0DpfE{L@A0R!k<8K(#h1)t-3AXib8nCO+as_R(eZFEIRfDzA|4nXF znKKf=LRB)@RQ@E-T>Qxl=e2@e9Noq3+WFle9UW=|n|2;6dwP%zqC2?W6?z=$rRw9tlF+1lP+af6F|o2K(Xf zzsq-;SB(a+P?Zcek*~Ley$x~ZU104$zgex9o96%v7M2p=5f)4UtH|EwzbmJt9p2M(K4 zz(4XxJ@cp3U+X-fhVUZpjStS+Q8O12tB56 zYGcDbp(0_Q%3sv}|CzuAtXrgco?f2!EVFo)+xp z_@c!C7NTUZsby`x%|Z1`04yYQfi-bBRTYumlEi4i1hAqNO@6JtpW-F7=I;HeO0W-l zX~2f+y9f>(j1C13v{5zK$L?+Naf+Wm2Cxt%gZ-2rR(vc0z`}X0V7X7cI8Dovf^>AK z4eZZ8^F4|eWQbv(P>~v}*d!IfLXHaT%QNX!+)-nq0W2ix!G3jXHSh7ElxP@Mzn%O} zQr)nNHgy#PScsCrjyU?QuWkYIQ?{J8}q0dY>22`p1;Q-6u?4NGT0b?^nkP)01M}}f;EYs z={@|1*Bf+ns10mxgfAzUfA>0og^GlIl5SYeqs$<pN@SwZi}w61u>;?+fA{ziJf1Xu$-q!u?DA zYiB#e!zi*c$l$ER4beu`U}J-x$|rbqZw0UrC4-gngOmST3Si;9 zR+2{(L?i#>}i`2Pwf`@1X&kGIN|D=;jqy=210R{obeY;hqCa04!7`gO%``Bfb6u zVBx%0u$K~(yegfd{B(4v4Q%x5U{1)FLkeM^P?4}t(hd6{Edn12AV&puQSIsK$riHN z02Y$;V4L&T@HXCfJdx3`nqZq!XWs#^P?`+3Ys+e1gCRaM0W2hRf#sg$a(dQ@_Ay#8 z0c?QbV877sUa?@z-mja2m0*7;)T4eR*uBYCuxn3DGxMk#?BUuDd7QhT8^A(UGT2po zZ}Ez701M}}gY~TAnTK_n>*!D$Si|-_PU#?4F6}j%(YPe~!_xnqckxdWHa4C`|@CFHh{dZr9$402UIuz=l>s9~@30+|G-<#n1W%B7|j227) zyLU;M-+yd6F2I;Gh82b>!CvU50oydmQc$#U)sM`hYOwYW3VCVo`K16Bs*=I3A^oDa9>x)*&S{j2>XO6HCS8Yij4pka#UcSWM)-A z=stTJz(SH9?1h)lxtE28AM1EK`o23g!N!gfo`f3~N|V9nMs)gx1wNJlSV-ssJF0ew z#}_7MqZloi0Cs=S=m64j+ZlSR1J2w zvqC;-t8@f_g{UT27c;X#02a<`1dMtBeLk>DNJoUHDFuuq6mgKb)A zQUPEgM+MfaAiHc$?4O` z02UIuz;0eT&~=LYHU*;v6TrUOC--TUCEtWGXPrn*P=YNh7)bp{kYh4Zp!e&kF6L1+ zSoaAEdAW@!48THFGT2Cdu*H6V01M}}f-MQ~c1oT6O@)pQsczWjDIeT|eL_WQu)FLI zOaZWvqXL`o+4Zt9C4uDt7LxQ}tFqI0U+m0xW;CoO*s}}goCB~>nhf@|?BE$*@cu=yVOK?riDl$dnzHVTF{4&?4*e7dm=?iTBePZWhiCe zvxF?sLiYXFXL!u_yzb0he*W}0ulqjdeV?7~+_^K^3I6>16=Szo?O5%lFgLY(!*yDC z1i5?r8;j<9`G*WOcQ#h<8{*|391!FY;2t#7I5^bL&pjy2ctMbNh*yxY*MFnjW_kO1 zx&8Scd)ue_27iy6vVPM?wFIMM|NM7cjp7yt9o2QzHG=|teFH*6OuPc!e7*eL{Jh-# zwFCt_sm7=KtMN_-c`f*xd{id=*{J2OE`Mu|9Z6|J&DQFz)SHHQ`+1qn3Jlf~Ed69t zbA6OE6uQ4?>tfjyx9BoYG09;ab)&>7k#|x)#iXYfq&aRK&%+eSn)E5|wwV_ActNkf zD+(U-OrS;%*H&+*-YVq3lVsu^7#I|=(9OqJYvLS{m2d+U%Raq7DNkSTK(|>z?w%pu z0sdNZ+7A#8OHg^y`)|FxCnv;EuY-DfbqyjJX%!)fZO zcTjKhCsuDHC?GJ*%{L%8SS!J$QQ_4vpYJArgMQOGIYGT{>Rr^e{{|NZ`qr=0Yo^`^Mw`j zd?KKeWIdvjvgH4eMmA{K6OfWICZu{ny9%Br#<>AfGRT3{Iw;pNG2VmELKTs^wVyN+ zkdlSzNM{6e7N1|&`y3!816)YE?9;XS*JGSLpVksc173}H5F}-W!4jXZ>9JIXG;ts^ z(xiWuQPo=cr+FvkNR!@OkZQf~vIL}LO*+yDo13-v=75wOt`zC(!RxIx^Zb6ZPfr=r z4V%Ub$Bqq(giez6n2~m>8R-E?$ruyTsc}sTet7J<3P{NyJJRx{!!38d{`sEILKTrV zeXw^iASDaak$wzrA>PqkdjcRO16)WKe`;*Cs%Gp3KCLB?9=rd{zTwy|Zm`5@b+4Am zkk;8SBNhBuPU+vuE90G%BQ5BCRcdK^^$j2;YtoP|U1bw?Bqt4!lEalE%`=D^zRzCg zAp7)`A-!GaE4<#NAQd`E)?-F`?fLt!fRv0eAx-+)@wC&A40k|E204(rHMcaZa*5`% zP(`GDa_@QpQnD}|X~<1C+wsnWcLGu}z=br(EXr!=0NbO`+GPzZ<=TkW5=bY_qa4b{ zcV7fc{OXarLWcC@SZ1W9QA?t`ASDA_NVn`S8D?SVGM7(l z38cp_Y;d@t+VK!9QAay+l?>@>H)f>bK`W_1*Z5-INjcKW+N|S;oD}J=-Wv|YekZzt?wi}R=NjlPmpk)pXk_SY=zr(|oh0iqBOM}cxf_s@ zF(#zbT=(Q}tg_bvq-2mCsYa8ARu>Bf<10im&WcpnWM=^&C6jcd4@+VE!mx?G{j2!2mO$ESt&W4mdzCM6E)7y0BV8h9eflPWWK;ojQjXL* z<%u-RwOAXFl1Vz!#Ws(7jW7VD6r zk{Rjx15HK%QZmMbbVCp6({(zJ$Oh~9_^Lt3$> z0khJej{a24q>BGXRL=Cm{%6vWRU21#{adw9^${nmN_QG&vwP0~0W1z?sTAsqqGML) z21GpMSe)|hG}>xVkGgXGzcc(D*vOc-1_mV z8&+h;+HU_bD?!xE!Mql$cyZcXpths?-_i?PTmHn-bgoa%X4~z&VYScvZ$hubgepvM zdA;LeG3DkqK7Z#8fQ9i&!6wDN5atQy)o{#E8CZiB53TBM-+cl7go?~y ztyDI3001Kt*U|XiT*d5LA ztp%`<-~wAPPi%Sf-h>;x8ccvSc&hHucSf58SmvnCS2xJOeu-lNE8aefvJYGo&p#>$ z8xs6N`fbG4Gyn@#6~Tsg_ud9zVZ2hX`Yy|?u2zf+X zuAVy;z(S4*?DkfM`4y^TX8~A9vV$EZ77BCIYPRuOtRmQjFE?cYSSU>gtGOoAw%d+# zX#f@yTwr}Z?Y0muJ@S=Tg9)&2O49Aul^XtlWm?^j-zWonCY1&3`177rb<6w({G)QP zx0b(@?n%iw1Yn^m9qa-d&n^2L0W6GH3ija8v%<}%yEWpNp)#;;@1m{x#q^y9{e+6l zU}x+-)EB@)jtOj~&dF1jd78@rEF{^%9&wr~d}4q45U<55g6;a|L?M8M(sZ!DosQY6 zZ7;kEU?IT;_P|U_ON}eya9#~2!D@ThZ!CIi1}Tg0)V^6cHvFS< zu&XY=lJ;#-xd*^PRXW)DHloVG!vQReR|vcPn7}49-;vYOaY8nLg(N%JFfDJPbD{l3UW-)(>tdIG3cx~XI@sqqiMFv7 z;iCa8B)GsD-1E#D5v7&PtHA`=)gyH6S0#+R0n0po!EuWW?Cnb|V0-vZr$UbGOyM7u zgI&3*Qfk<)M>hZqRq0?uZQ2WT9|KqzuN16JsOCV2>nU*@GgJolK+D%dq+7QhgnmLr zX0T^=EjS5aA;$!EZpO%*X0b5`04yZg!DbH%6=rum9K>s}ieRUo5gq}sP?`=l_4_MZ z$1>f<02UHlU`?tv40P`ixr|qX39tddC3bV?WUhu~HgF%XO$Ijh9t+rR=cZCe-|I#5 zkIKQm)O#&0NlCa3V4*4188rQY`eER0tQ_G^Nw`S2@K^Eqay3~c=dD{y^QG6MPu z6`8?OdO>&%3ppmRJ#Bww>)E(Q09Z(}gB8_=2^W`bd&g_BieL-N=i32TC`|`@u%U+C z*t5;Y0a!?IfxT?J+dS^+^aH#aOn}`PIL7YbrrdL|%(EWtcF4fKe!&8E<(Mgy{>-;4 z`A6kozofpFs?G@U0I*P%4mQ|k%Grlq04$7G3buCT9`nxX?}QvPWCCj#yqki4LPch< z+jrizgB=!fOkl@YH_ma|w%-fDLXsWqkr9i9KMG%W;k8&ruzLf0IsjNGO$Qq-*dSgv z`c@Wzg#;JaKH425F)EJ-@M0swRgRPenLfNurr>O zg#uW}F@gQ~@Ad3aU7I}yu#jX2>!A6s@YdIV&3G+V5$x?|rquuzO4Gq+?wcxBJG&V# z2_V4*c5Cu9Nn-r&TwV<(z^1!iu&sFg8ei(WZn?Ev2KLvohRkmqY;m1PeZJ?1cdA*V zaRBLml{Gp zA<7Iks@0G202XpgVAr_CW}EzMHx= zCDQA))(Cc3NN|Cz9AlTUy*P9cuLcufJKi{En>M0m94ynMU;JJf*o)CDU`waEQj_d# z!}&+$U|;mDk{)Zi-W>~XJ{eF9o%i@?J6WF(xI^KbPLPchc=voh@ngK>}bQ$qx4Lp(Vl$&gqB>G8vEW37V z*)sqOIVP}nzS-GFuS5g_SV*#iZQeXwXtB5lUc*A3xL{WV`{?UK7XS-UI@p6nQQ~d$ z3=aZWNN|C@Ce+B#yJ@V-tHA`=Lq2-8*NjH>gme17P49Ra*th3dz{b6Ep*DP5IEH^z z4)#fCwKR5Y@j3ttRq0>@Z4P(&`3ZJd7_Ss;pGD_P!nHc$D@uqF=MbMO6x9FwRC7QA z{e&np*!5H%zUYD+6Ij8WhB=208@&gxkYoqD+#+0fZNW-+j??kyr&AH^j1Rpt04$WI zgPnYRmiS}xtHl5o5?o-deXG+K_V>BTtHA`=yxx@U74H`R!ZLf^*GiCq&Aq__w!Qj}|W&Tk)*g?murPr$7i~z7}UlUd7U;}I}4sKu!U}3ycuqJ~8&7S@va)TK{j1}y? zx-@s_Cq$XS<_s7y40c$^F@ZItGO{oFRb2qEkYop&I4oSaw8^IHycVknHsEdZX#f^V z)4?|CB(bx89908gA;AT9YIM)^Xnk#4UJWL|-m&dun`a-q5tgapqjE$BcI6Wmu$m># zlv!`LcKoAqutO`VrPqB_9|KsZstC4EV!%}Z3*(i7eR@O3Y*%P3-kO9ME7+AI99lv@ zA<7JP#-!L901G)Luv=#4XB$lKx&XjJk{#?8pKzgx+o%~Fr-NySZ6gx22Cz_?4mNC2 zZ?RVQ$bkSB5?o+?Umx!m6=RgbtHA`=gg52lN3BlJgJmX8d~;L=_Hqpi*fI9bl*ikm z2K=LPupU}9(s!}%n*vyy!>)A;$#vw$IP((&G7#04yZg!K$na7kkm^ol&IYiZ*EEF{^%zTFlsT$d)o2PYuU3f66pabo}rQ99Vt zoaQ3c$bTyVEF`$V_8wx9qc7gLomYbiu+Q^PiEEm6#fM)G`K(Nlfqfd$i20qa2>r3t z!e2S3fCFn(4z_k#jr7^fCPM)%MCo7yY@S~sIa?hjF04(H~z|OMhCUM($-~@n$BsX1Q%GHpf+g<=Fe(*HJAX~duD<7?uK6XLEV{rmsA>DS(BlieRrce0dwd!g!@%?PKmIcm78M?-WCfIERXN38t4X zd*EJJ{^>aACJscky>6iD=3Bl$<=U^kZ3NHf!8tN|=kRRk+hwZ#XxVZ2hX0)cf>h1sn=95ZCvVZYh_EQWqU zMP{(pbEn}~*g=j7Y@lgX=C|>hKLIQx*}-1T4;QvC-G^@+K%NzBl!eVz01Ht%*gGFz zQ9Y#^PXH_=xWGom>ZXrtJs%%9h9eLSCct{k*dkV!Hd+Jc)L==c3>nyhG#0RDRGp~g zFGi{SqjIo|Yiguht1jFJuuzo_*5AhIyx9ZTVPU*duw@br9BjJonYQwDZj z0Snmv>&8%Ta$TD9kIKQObgGrkcAftgz(Q3;u+6)AOaQPjUMW~X!A9d#y>wS_%#dk^ zy<8sh3Hk{YnZXYEu`V3ILXHWnOEL-IG^?39!*^UB#yl&9H-I>YR9*B?Ei2lm)EU zurbt;v*HN;Q90O}p|#TKdsJrwSg1+|>u2*J>USc5h4IS43c4D4_HT0m2Zmir3U}3ycurYc?M|V>L+jA_AX@~W9 ziN)JmP?6{-?ULZvolSU2068YG&Tn)i8>5=90nGl&x~?xQGv-5No($}( zS1e$M9ve;FYO~}8|EL`7>A+fPQeN&)01H(W!8RY=J_o?Uc%@)_s`(kOH)>YJF+(P> zEyvFt1pS1HL_cX@hegB%!VU{LCa@{R29gg;uX_MkNV0>?&IlJaRgco+wOB>43!TgR z0az$a2fJQ$L*(P>dJ@1wf(z{DNlE4_3QyoC4&Vqxg9)&D0b=nR<8Amt+Huv)Q!=n= zpIE>S@fl628f?akCf2ANY;;7ev}>k;5rBoLBG~EC-b(>2j8_UatGbJENS_0{;T%GY z_${gUqN~foSNOCRM2UXVzz$tH9dBzvjtOkS6${DnL-WT1SV*#i^}7)+bk{Z9%4@NT zV2}8C;L}=AnhsVqN=0lxzvF%Y3kfc;xmUKC{oFrpEbIty1fszNSkwA%?5@sD$In_O zCt97Bf&H;Uh53zxSuICX6OSGJ2pwXL%E1OF*Gh-F=iwJ=KvWTInr=7zhzyKZ3f8_& zW8+Qw(^_-PkZFev{2tI0`Uw?@e$v2hu57jwc38+Ufju8;FS)aL-ar5gNp`Si<>A7? z|9Um!wOB>4FI4Y0gdG-2)4@iS#8D&HhD88aNN|De*dsf2@vU9Pyc$e^&DGEsd)OO+zKm8h*J3U?Is4 zR`W@?@J;2wvAhwcI#^#D z_0<(A02an81zRRrpWLSHz3v=~V**>05qk;x2^EQc(!gHS9fMy62RSCN#!=Cdw#`hX z02Y$$V0XR>7f!w^DC4zQMXI;P@X0*Dd6C1vX5fBj8R|IgvrY=9Tsv-V6S#q zE@^Zp*apBtk{xW9dayn!DfpQ#$P?C2h`zvls1 zh$@2ZKKvklKP-$_3N}V>sg}Tr1wpN^8w{*b zIoR3uZ>6?zt;Ygbh$@2Je7-;al@S=P6l|8CuF;(@bAP}&gcvJW!*PB!&`*dG{iK2I zu)nSs?68ny0$XjeM>14JlLD}iWCxpD9WM0H4Z&BKkS7+a2zKw78*c$DMCo7`jqEN8 z3Tkx?z(RrxtaVjtTFKE3g}fR}fIWI5Sri+!0q;$1i0)bc2O;YJzVfzTEMTk5Mp4?5 zkh8#nH7W-i?eq*2001Ht?u!D9#Tn{@ej8_UaMlZm4?Xe~OIcCUoNnn0H6TcuD zDl&r=^txpXU?Il@*7{PML_adw5x_!{9qfYF;X+aQ4IN&KRRnwJOtVD*7E05>dhW@g zHilPZ09Z(Hf$i91b=qf_bSZ#^BM=QHz@FQdE?VE#whoqAs;6~b2DUu1G4nfJXXEXu zzzfarQ~#_{Ias^N@1zf=h)Mt~L>0l#)fV*!urOXJ*mOS~;|!_33&-M^z=mfp%!7VH zMWUay9d@e2pcDWLIVP}08md|TYeH`VSd#(7nP3Oos~)Ve)dyTG|sp{>FkR(N7xKRh35j0W9R0z;mLPhh5rl6BT_5`J zmJIBN!z^HD&9|f0-)M=KzpPO?*ma-lq!vehE(fp>rGxdc88z+rB-mkLyi%|+dhSO0 zC3c|z7GlIXR0JE)<Bps0nxlMeHb%E1ci!S=Jd8wOyZDjlq^jqyIM zkFdkSc%@*y%X%4SXwRO=F+-+n*reb4@sa>468)rsH7PA~2C$H00(&B(SW;yB`YC{g zBs=a^j8_VF zo1Ttw^HX2U0W8FbbEtSpP@d;+1^t95(N7xKhhLBN1F(=|0(;S*b5^Ed&>jE_Np`TK zKh=L~c1vS#UW--SVdr1CX$?Cpl%|7y?9^W5cxDYg`~nFsu=;Pz`Yqg=I+Is}39vR% z*`h}Uny+A)|Gez*PzH9-Lk_TOZEHsHj{?{pK|b98EL2ql8*#~L4SgI%-qF5ZWQ91~c}__kS}8mvAAU?Is4cIU@%;Z&_&z8t6H z�jutwQ?@r?s0O$Tc_ewsK<+sP9y2_V4**6zUij0CG4V*o51foL!RHu^(>$WVV1 zzK~vXwc?Qs?2FeNV0-l|F@X-TMgi>lC5}G;EJPK-Mw&&H09Y8W6l{KVdy{6~pYRJo zA;t<;>vZG(&`*dG{iN-%D+TeZVTXkr6WEz$jk9)G?=}XokYootr2dkiW7sNuJQ?!D zVim!zIF~mNc36ng!9E<@m}<5AW;TF@1Q*zz-ja-p(>?Iv7dQgZU;^ywUg@HyO+=4D z-SUpbG7Mn^QNy8^A)23G61rFOsC=op%9PNV0<+RS)*u#^=v@Emje1WWcl2 z02WHq!A6FCqNp85$^k4SxWL*y$vr+?KhYO<1ULfGU;=E5{Rc&9upM_a&1${rD1wC~JJ_)LOM=Y4-|=Zr$g}RSs!ea# z09c69!J4mDqvF!HHV3ef-~yWz(IRtS{|z&EHJAX~^=^cyvHso7a84H<$gGfoJ-3+y z?BL){c&C~*3Sfh+G`<2@h$@2Jw&Lqb01M-lg3YpTllQ6Dl%; zO>Ajt20JX|n81F|_Q?_!I}C*#7Lx2>`_+aE6YtMOu#jg3J58mb6@Y~(9c*)LEm4W? kg*pHW2`;eZMPcSSIg9Z&3><-IFah>##cGk+$6poy2g<<YVTq2|>iL9ECbtL#ArvWO`6`ZdR6@%nzDR zDsvQMkmB7bS%y-jkad42U6a8HG=A=Ze-yQ`mk#1Jzx!O5&Zxk@5*~ybsZpskxj6!b zR;E&@WmyWjn#0oNiCf}5d5n{!V!kn1d`$n|h}z5E#+vc5VlLElC7g*qIm#@BAVZtY zVXOB_Q{5Y3zC!BNMJtTo#t0grHWOG%V2e(<{u58?)v)x{IDov%-$}&iK zT8>hq=5SZ{7j6;XBK?i^j@>DjKs_EYfN(KOl5+KI1;=4-c9c)=FwX#EY;>0l+w>%O z#QWW`w?;^fHeaUFWM^|!i=Uquk)TTv7=u|ez2cxApYSHQ#^3_2>g}A0bXlI9RLa$9 zinmX2*by(uok}KysuXfktyIsJk@6e`Cv=Qr%(YUt+k9hThea*zP}q%dC5Z0AhEBuU zbU^QeibNA>^otgd6T ze2i5Ce)}d4t5TinL=o)g^)MWCX%*_eRDtl(*7nJEI_%ymN}VNT3mdafbPX|f*rj!s zVu$op3*EQB1~Skooz+aj`9z0D$)jLn#p1SF8CJB7^+a=ego}rFGNWNFwHB_G^%`g_ zy}&iH6H8OM`c;=nJ{{IqG{Tq|%$weV342~Q6i6b+-*8>WXu)P+H#%*eIQ2y@0>&(v zb^%P7C~e4;3sos#S&Kx= zs=`A7ES$Fr_F?*ksOEj@Ep|Gz2KJ1`QRub3g%A6Liu7PLrJX|oEad3GZoaUphL?NQ zAHYJ=HdvS59+7?WBs&=mYk9+VXg2%~V4*Y>?3k)d>B3Dv7XVmD*aMqUJ3MmOC5=0y z1)G6A=SoPwe^xXO#w@+(#5I6@^2!F-IFHrhl<75VnMX}vlds&~*NYw$rOfQ1|#*wIsF)W}*d ztp%`9W0glpne;$4WW8U>y$Txs(u5_foVar38i5-0_rZSJ3z^>o&P~Ww~odB@0!_BHv z!OjyM%FmktVBx$~uyOex3tv4cD}xRpX7*bW-(g1vOQY)Ii|b*Z5TyruA`Y;8qET* zkfQ@D{B2s*l1cmr02Y$A!AjU%VeIF^j~NYX3HHbFMOOhVl%|3ux7A5rs!HksEF|oK zZI(Vh!o4;85TgZ~f!)Lon>b``*?Aa~*C#5(0QNyePx>2nW0^**-s!iJdDH~9wzWxr zacHg+fQ715uxgP;#@+y6;k;F_DFs7A4z%&S>~v@iEbHx8OGV&)*e6t^2kXssI0s-M zM+f%g=v9@suKV%;EF^7%?NOL4Oghzj4WnT#!L}4$oef~2G!<;)z~z#p<6rd!u#m6^ z*4gdi;qaolGZ-z{3@nj2WJ2o5;!QB7&TmeH0qos28(@zP$`m)94#Ky5n^66rOuyEcg*f-Bt2S+=kW!f2z4s2lL-Yc+As7McX>DuMV02Xp| zU{5tiRId1Z@lpT_N!wsIuTTrSc2);78rBkQ;O}v<02WG9!Cvm%814K^iwl5-ggvk! zr$!x0tV(ELv|ux^U(XJW8PHWX9>&xhEr~XOZ8+paf5Uzol_8E>6mXMy)CAV^WwSnQ z)L#5A0aT@e%@l3lzP<^-!g;G;pY0NVSANFl6FVK!fi1t2Fdp^^73smg9-LnaU?E2b zHvYx9O6{8dtpFC1w!w}}%N2SxCblyg))H*_XM27Cuuz%`_Wpe*$@J&jWB?Wt_P|z^ z^b>R(b3V^#!De7Lee_V$=isiFFs8ESFH;O)Z?@V18{(EKUbZOBhk4WlR^<3ppLBeW z9Bx>sN(HMFWu(mfCxC_XR>7X7y~6h$h?)Hzf`4?qeIsBscys2$J|RjER`?=& z1Av7b9oSPf>dKgqQ}F;6lD5I><}VPQ-JW~a&g1C*>9hpfF!}Wp01Kt5U{kYVqc^U4 z90On>VGryc_wtc@_tn)hTCf>dUCJ)WzCl}xV9fY8?TH4k_22iRzhO^1C5YD@OJBk~ zY682c>6u>p8rBkQ#|+O@01Kt5U|qSBqXpOZ hcK}#O*aLe!;KrzH%??u-E!Yg~?aK!wW66=8{|8KYnl1nU diff --git a/000_image_stack_ram_based_reward/logs/PPO_8/events.out.tfevents.1680179576.DESKTOP-9E17TO7.35060.5 b/000_image_stack_ram_based_reward/logs/PPO_8/events.out.tfevents.1680179576.DESKTOP-9E17TO7.35060.5 deleted file mode 100644 index 89b6ec0320ac4deb6d2c41978ae03303b66245d1..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 16763 zcma*udtA)f{|E3%xs9)GluA^}C6`i4YGtaKnkl*Ou1grBro?nH-4F>CDc4w(+T8l- zi?q@`l$dC-F6)}5+KAk<*k$R*)T8g`^_lrx`qSgQ=6&Ap&$Ht+QzB0L*O%?0%$_kV zW9BdDdDq>f_d>ZOIMl{7S{fSZVn5x6J2Fxl8WAR67$%Vi*hEBygh=GeZDQoXky5#h z^xG>U<(hE&$irl^u&78|X}DM> z4Hbt-C7}jKT4DqSHgkMgC*{(Z_9Vyrtzz52G3I6+HK$D!7(q=vt`4_HWN?VoHZVNG zfW!H~-|zm96BJtL_eX$oi}h~QTjYqM1cuKHYgi{cw^%v#g(5%si5F~DAkH1TxpHdkO(dt_9bmJrEuy3-(_w4w6d(g1>!BC|{r{?W$|+ z!+J4{_S};HX(Nm_S|W>*w#PnenD|ux@~{G0{G=ZrtVFt1LXEWUy`P})exQVPvJ+|O z-B*gfiR`*%dgH%C(c>WMuM{9_ub zL|VBt8K$y{X;1H^bxTI2cuq)S{w{#e+IZFVl1VjHSt3Gm|F^Kj@tCv+qb) z8UOek6HH#MZ)r{Fe=x0t)qn|L_n0R5q+gho1#O-P-6L0meZ7wc>}JdHf{6u=@7YH? z!E)l>C+tKc>orY^kCy!_DuL*v}z&4K0Vz(Q#<*hZ6q z6SZ%7eg|M7!2~ul?%}x2&HJ@j4VVD7_Hc;LxYqd_q0Na$=Ef+&W}l@2t7GdRDBU*I zihZ;btWMnG)q-2{dmssnpBInzb=@V)gg zPpC)@R%Y{L1%QPd71h2^4GdffpmB3!zQ@f*vcCV6QgPfc@)@jUdv& zGl+e(6YNZ*R>eMl@pAwRRmor@_$&YU;}L*`^=iQ`t?_gT-?sGv!w%Jfje4c)qEl0Z z|6@T#YOtr%mmUJJkfQ>-Q1fZ|&o3W`0$51WgDnwu=Vfn~JFse273{`M)=vQ}lqQ1} z?YiS_Sa`!2z(RrvtVT`c*o^vqn*c1l0%5=eu*1uFKK%48FQCnYs?2yL*!Xo_sPC|x z@goE$sxt5nOB?M3Tgh)#Tr#`Z6~IE23^tr^<>fE{z`}a9U|ZJ5I`>_Ebq7Op>cGyA zdgbi;t8)#^6DktsN&0bXaZ}kc01G)PuvzD9${L(DrUF<<(t}m}J(9QnzfqrAHLD7C z^2C-@01KtbU}OA_cxPWX{|mrEf(h)MmfWJMqlJ4}4VVCyf2N<$(mj!m&}N0bZK4uv z{s9`Wbuq&PJB=LiM;h8_Cs@;fR>hswt#be@M9E;o_%2aDr2$x2uNJJ`%o`3lb7$g} z0AkAb57mL?eEnLUXPF7}geW!GPi|#e02XpoV6E$}m1dWXa|f`Hqz79!U%=aQ(J`Lk zNwznu3bwrbb`pSv(qyoPQ=g00d2&MmEF_q~CMBkg-4OFGm(_p?U`rG)y*Gsfgh89S zbMumwVC$=Cz-G=EA_%$Ja*utq6Rh>BR)wiw!eIalRmosO`F2BVDgi94R|___*C5AJ zC(d7F*r7VGRXYEUn`D=)4fBMG)L^4`PQyDabW@ncs38uOLSV+=?b=&_vFI6{f z5vyiZ!3JI&JPg1>X)@S=75zkd9?~!X3kfE$1$MqgZ6?>(!hq#60zATi31E#ERC~9@ z&#QwrBix2>R)XEyL<4qjmX+Xq)#Z=uqn%(awzVpD)%0%xuuzo@HiWPJgX28_3+vT_ z?KMkh%%%LiVul^61M84;(aA37OMjRrR3yxkbR}5gR%r_-Eaa%bHk{g0`sh2?CIAab zda(AJ=kwy0PJYCySyix#$lKQdER-gL^@D|m*{%dznV?C1hwblTDL6Gds~7udCs^6OR>h*h1BwAGR3(Fz@t-}F z+X7fvuNG|myYcpGn%Cg_7!aeq5)4S&R1NclC^cButpjfYSjbUtZm0B`qEE&T3;JfT@tun!NdX#}tkC4=oT#M)ciNah7#A;ARp;^)1Ng**2yU^QR@ z*aSs_cbo61wV>|%Ujue2!M;971GYkMkU$pPyNP|Y6YPh)Rz>k@cMgDss${TB_`|OB zH2|=%UM<)|51hvYJRE$KVTbBYSkBk4NB^CY0rP~4)L@@vZT1APkfQ<{a^Js{uhkvj zhlM0P*!>=hdBz@%nyi{t1v~U~`33+BrO9CPQZIXR&lwE>u#jK^yLp1A!`>>5-&qZq z09Ny-Dc(mare#2zU*8YRP=d`qPXjilpM{`nA7^9s(N3^|Wvz+}dBXbu7OIlLF6JM( zRC)!#!g{q}k1bq2TJ~kq2!LVJkocZR02)mQ9?4zAv>(90-%+CtM02ZpMg5B{TH44DO zdbMCb{t#kccIxw7h8_eBX zjw|v8c4akS0$2-&P*GBS^a5z}+R**EO0fAkG+?U-8w*zNx*o?q+6i{1`&-4bmD>sd zEL2qmTebbS$p9ACs|DL~)y;0ek{eSPc1U%?`WU!7z&xQMHQ4uiW}5+6$Weh!Gq_Sx zB+@AZu#lt&YnZu`_uvPYiL9Dc1>3{wvK@eh(qynN$NuBR(X6Whu#jK^d!uQxL&?gD z9;^mT0DHJZhTg9j1APInls;Xd{ z6VLYou&`b&*pt5FN6%=`=*F-^DzF@mVFAn&DpG^p{&lj|1|AW>vwC-M$6ihlMB^Y@e#%g-74|E(frXU;=ylfYAy6pq>pdV0Z<> zfC*r~{CHQm_Q87mxV`cI?qVg_%Jp5T@37xaSdSEE{FbJT0$APRhaUheM9E--_$j*D zs{t&mR}1#<%xuRoLo_$QGZeibH%E2CR_={9fq6odFi+AQ)~|JOBY=e*71%M>*(KT* zL+Sx6BOQ-vE3_w5E?A;ARp+NL~*3A%K4`OB!H5ba*w_EZ05&mp7=Cz78wIepo3Gyhun<)Rn;>qe0vv%9yG-Yz(SM^*5+ufm*%k@vj8k4n85zDV#mqfZcm-dYQO}r zo7NNwkAKQN3t*#ck5?+eW?x_cYs_;=U>^mr&j!^W2e4386>OESSO8#Qy;`tQIkC1c z>a{%>c1U%?zOFsy3G;-C)L;t_6qN#4$WejK@;FrDbZO{x01HWaupt?7JlV}PZ&@{~ z3fBICWC4JM(qypq@k702rjES&3VfORv<5pK7v#b4kaZ#VnA z671C{3}Ew%g+iDRZ4|&RO!=h+z(Q0NY)am$VgL*4)q+h+>ubC7n41B^4ynM-_P@UY z<_Q(4!N%M>oDN_iM+LUvb56<9oRPYg-=2TivBQe$oYb+7mY8$I%%87NTUZ z7rOrDb)_x;4uFLO6WAL~JstQ?1Ms(t(%lL02m>a7^`Ep`STlIW9(bmiWB$0P1RI~+ zjs6b%vY`||)uoLBSkojip0E%lgAL?wbbf6KU}3#luw&cG$L0j}AI{L6IfBsk{WoS+vSkBk4aT^ce z0RR;V^CW@w+}#KNZWVG=URP=gaDJEa)=z2G9wZfSR`#o(j^E89Y92o zN~_{sQR@J$XRTIB5inFt1<&GvRcVEUOF=Cnt%{|R>|kEVCd;49e)-;e{K!C-(KKKG zZC_SSANgTQ>l*qWfsR%QI4Tsgg4SVT*<$Y~7BW|ciPI!_f&|5rSZV30sVJVs%D{y( z3}<0uPYIHRB21w94#TCgYYy?cCrh`zpto`M-X42h>z}>ne1JG2wzxzjlBCPnm{cIb z#DY`|6*FlM5A#*!OL8eEaV&#KZa$*OYO0ny6P=Nve0$KzK&BuTGGQvlPL`%IX*3nj zqiSOqD0(s_Pm;(-thFfNbK+e3C@0^IcN(IR{nkW-W#7ssX z-QOj0Tk&k7?_9@^OF*9kVux63C2>@|7Gq+4-*Z1&!FiD0Hw^mb1yNw5yZg{U|Yd;1f7xZv)E zYtB>_6=5hY7K+yja8!mdx0b{#8gV;TsGN2kDoV#RF~Q8-;Gxp$ z9iBw*CZ`Lb^nx`_N;T5T-6rHpn-WX-HdtIA_2@WLPQpEfWs$1Jg=qB{I1&L{b)6RT zqyjq?SPo377ivgkLSRSLmghz$)La!xrTL`zKTrk4xDykON~eXu3CXEe4ynpUZe7P+^M&JKTqkvT3|gTULhuj%&vhoZAKnFQiFZaYyfQd*I)7n zE5mkCkB);~|JOrB4lCoR3$d>nENImQo6nou)3XGC1<&gRyU9uA7k-9$#mI#Ez!pT& zxZ>DpufaV*BRSXsx4H-b7UamlnuiWGG?{E40boJWFxUWk9_PDu*Hx63od`CXo7)Y* zf@)o`A@(ztx|>#)1F#@r4D5(^5y#=w*$7Gp)&jfq&is(G4UO}_nnGLmK{eR25d&a- z8+Y@sPG$#CkB);ap(zzs9{33W7PRVsrDgM$&x>UMu;6*UV5{OIxzk%L9~+raAK2(G zthgm@=JDX3pphKxFq<<7z=9kZ*oFSL8(M0PI|8sEX#{MxHz)u2d!3Y)od}jT_4#@L z7F6qkZBTZGT#Q4YuW^DfyoS z$=&<-bK3uf)(u9-!Cv+3Qq=7?l>@LKstY!QcQ@9~27m?6>jfJb;~TK?=>lIP%jpCA zRrq~wKv-ZRxF={N2OBr!*$BXb92waC$~_Gpc+pV+79TZxz*kQ(Y|y8(Q&Xd+PW2S9dZwYA_HJSwJzAGg~dVht!Oj=79@;;{npysPxZ@a3#9{VfxWYHAo%*F7yV#OH;!_W z8f;CO8TmVGeR385{GnbR_2@X*9kY8Cth%7<04!+L1uNlIB-TFz@37!`y4C2Y zR31hq)CV?Ymb3p#++qv3Cuk%GtNgXQ41fhWGO)9H|E!mVp4bM!f}~-vw49rq8!aBE zDJ?q@Y|r4L#Q-d*)&*;G_uw+6{QhMC79@;;y%}+V6HYs91`d2bObedYfwjOg)(iw6 z-CPz7*7VCvnxY2#^r8W<1-8fek(rDQ)T85IkG$+vJh83m0$@R_E?5!oS?Z)-02Vy2 z7i`o$ckVyK$$3U5)CV?4I+dFrXzL2@2^zKTss4cB-3MB2?dCTDSdb$FYiS?UV75Fv z2!I7i!(b2HXyEv;$}dq`b|Tos&(l8zU_rGm*k bool: +# if self.n_calls % self.stage_interval == 0 and self.current_stage < len(self.stages) - 1: +# self.current_stage += 1 +# new_state = self.stages[self.current_stage] +# self.training_env.env_method("load_state", new_state, indices=None) +# self.model.save(os.path.join(self.save_dir, f"ppo_chunli_stage_{self.current_stage}.zip")) +# return True + +def make_env(game, state): def _init(): env = retro.make( game=game, @@ -32,57 +50,66 @@ def make_env(game, state, seed=0): obs_type=retro.Observations.IMAGE ) env = StreetFighterCustomWrapper(env) - env.seed(seed) return env return _init def main(): # Set up the environment and model game = "StreetFighterIISpecialChampionEdition-Genesis" + state_stages = [ - "ChampionX.Level1.ChunLiVsKen", - "ChampionX.Level2.ChunLiVsChunLi", - "ChampionX.Level3.ChunLiVsZangief", - "ChampionX.Level4.ChunLiVsDhalsim", - "ChampionX.Level5.ChunLiVsRyu", - "ChampionX.Level6.ChunLiVsEHonda", - "ChampionX.Level7.ChunLiVsBlanka", - "ChampionX.Level8.ChunLiVsGuile", - "ChampionX.Level9.ChunLiVsBalrog", - "ChampionX.Level10.ChunLiVsVega", - "ChampionX.Level11.ChunLiVsSagat", - "ChampionX.Level12.ChunLiVsBison" + "Champion.Level1.ChunLiVsGuile", # Average reward for random strategy: -102.3 + "Champion.Level2.ChunLiVsKen", + "Champion.Level3.ChunLiVsChunLi", + "Champion.Level4.ChunLiVsZangief", + "Champion.Level5.ChunLiVsDhalsim", + "Champion.Level6.ChunLiVsRyu", + "Champion.Level7.ChunLiVsEHonda", + "Champion.Level8.ChunLiVsBlanka", + "Champion.Level9.ChunLiVsBalrog", + "Champion.Level10.ChunLiVsVega", + "Champion.Level11.ChunLiVsSagat", + "Champion.Level12.ChunLiVsBison" # Add other stages as necessary ] + + # state_stages = [ + # "ChampionX.Level1.ChunLiVsKen", # Average reward for random strategy: -247.6 + # "ChampionX.Level2.ChunLiVsChunLi", + # "ChampionX.Level3.ChunLiVsZangief", + # "ChampionX.Level4.ChunLiVsDhalsim", + # "ChampionX.Level5.ChunLiVsRyu", + # "ChampionX.Level6.ChunLiVsEHonda", + # "ChampionX.Level7.ChunLiVsBlanka", + # "ChampionX.Level8.ChunLiVsGuile", + # "ChampionX.Level9.ChunLiVsBalrog", + # "ChampionX.Level10.ChunLiVsVega", + # "ChampionX.Level11.ChunLiVsSagat", + # "ChampionX.Level12.ChunLiVsBison" + # # Add other stages as necessary + # ] # Champion is at difficulty level 4, ChampionX is at difficulty level 8. - num_envs = 8 - - env = SubprocVecEnv([make_env(game, state_stages[0], seed=i) for i in range(num_envs)]) - - # Using CustomCNN as the feature extractor - policy_kwargs = { - 'features_extractor_class': CustomCNN - } + env = make_env(game, state_stages[0])() + env = Monitor(env, LOG_DIR) model = PPO( "CnnPolicy", env, device="cuda", - policy_kwargs=policy_kwargs, verbose=1, - n_steps=5400, + n_steps=35840, # 64 * 56 batch_size=64, - learning_rate=0.0001, + learning_rate=6e-5, ent_coef=0.01, - clip_range=0.2, - gamma=0.99, - gae_lambda=0.95, + clip_range=0.15487, + gamma=0.9483, + gae_lambda=0.81322, tensorboard_log="logs/" ) # Set the save directory - save_dir = "trained_models" + save_dir = "trained_models_level_1" os.makedirs(save_dir, exist_ok=True) # Load the model from file @@ -95,10 +122,10 @@ def main(): # model = PPO.load(model_path, env=env, device="cuda")#, custom_objects=custom_objects) # Set up callbacks - opponent_interval = 5400 # stage_interval * num_envs = total_steps_per_stage - checkpoint_interval = 54000 # checkpoint_interval * num_envs = total_steps_per_checkpoint (Every 80 rounds) + # opponent_interval = 35840 # stage_interval * num_envs = total_steps_per_stage + checkpoint_interval = 358400 # checkpoint_interval * num_envs = total_steps_per_checkpoint (Every 80 rounds) checkpoint_callback = CheckpointCallback(save_freq=checkpoint_interval, save_path=save_dir, name_prefix="ppo_chunli") - stage_increase_callback = RandomOpponentChangeCallback(state_stages, opponent_interval, save_dir) + # stage_increase_callback = RandomOpponentChangeCallback(state_stages, opponent_interval, save_dir) # model_params = { # 'n_steps': 5, @@ -113,8 +140,8 @@ def main(): # model = A2C('CnnPolicy', env, tensorboard_log='logs/', verbose=1, **model_params, policy_kwargs=dict(optimizer_class=RMSpropTF)) model.learn( - total_timesteps=int(6048000), # total_timesteps = stage_interval * num_envs * num_stages (1120 rounds) - callback=[checkpoint_callback, stage_increase_callback] + total_timesteps=int(5376000), # total_timesteps = stage_interval * num_envs * num_stages (1120 rounds) + callback=[checkpoint_callback]#, stage_increase_callback] ) env.close() diff --git a/000_image_stack_ram_based_reward/trained_models/training_logs.txt b/000_image_stack_ram_based_reward/trained_models/training_logs.txt new file mode 100644 index 0000000..21bba61 --- /dev/null +++ b/000_image_stack_ram_based_reward/trained_models/training_logs.txt @@ -0,0 +1,8951 @@ +| n_updates | 11100 | +| policy_gradient_loss | 0.0423 | +| value_loss | 33.3 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.03e+03 | +| ep_rew_mean | -188 | +| time/ | | +| fps | 344 | +| iterations | 1112 | +| time_elapsed | 11555 | +| total_timesteps | 3985408 | +| train/ | | +| approx_kl | 0.10220521 | +| clip_fraction | 0.196 | +| clip_range | 0.155 | +| entropy_loss | -2.87 | +| explained_variance | 0.757 | +| learning_rate | 6e-05 | +| loss | 1.23 | +| n_updates | 11110 | +| policy_gradient_loss | 0.0211 | +| value_loss | 15.4 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -186 | +| time/ | | +| fps | 344 | +| iterations | 1113 | +| time_elapsed | 11566 | +| total_timesteps | 3988992 | +| train/ | | +| approx_kl | 0.17900813 | +| clip_fraction | 0.277 | +| clip_range | 0.155 | +| entropy_loss | -2.91 | +| explained_variance | 0.252 | +| learning_rate | 6e-05 | +| loss | 14.4 | +| n_updates | 11120 | +| policy_gradient_loss | 0.0291 | +| value_loss | 23.3 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -190 | +| time/ | | +| fps | 344 | +| iterations | 1114 | +| time_elapsed | 11577 | +| total_timesteps | 3992576 | +| train/ | | +| approx_kl | 0.1340187 | +| clip_fraction | 0.336 | +| clip_range | 0.155 | +| entropy_loss | -4.23 | +| explained_variance | 0.697 | +| learning_rate | 6e-05 | +| loss | 3.48 | +| n_updates | 11130 | +| policy_gradient_loss | 0.0211 | +| value_loss | 6.49 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -193 | +| time/ | | +| fps | 344 | +| iterations | 1115 | +| time_elapsed | 11588 | +| total_timesteps | 3996160 | +| train/ | | +| approx_kl | 0.0845661 | +| clip_fraction | 0.282 | +| clip_range | 0.155 | +| entropy_loss | -2.77 | +| explained_variance | 0.726 | +| learning_rate | 6e-05 | +| loss | 1.06 | +| n_updates | 11140 | +| policy_gradient_loss | 0.0103 | +| value_loss | 12.2 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -198 | +| time/ | | +| fps | 344 | +| iterations | 1116 | +| time_elapsed | 11598 | +| total_timesteps | 3999744 | +| train/ | | +| approx_kl | 0.05515183 | +| clip_fraction | 0.291 | +| clip_range | 0.155 | +| entropy_loss | -3.5 | +| explained_variance | 0.171 | +| learning_rate | 6e-05 | +| loss | 0.511 | +| n_updates | 11150 | +| policy_gradient_loss | 0.0151 | +| value_loss | 19.2 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -200 | +| time/ | | +| fps | 344 | +| iterations | 1117 | +| time_elapsed | 11608 | +| total_timesteps | 4003328 | +| train/ | | +| approx_kl | 0.05628523 | +| clip_fraction | 0.193 | +| clip_range | 0.155 | +| entropy_loss | -2.59 | +| explained_variance | 0.157 | +| learning_rate | 6e-05 | +| loss | 2.83 | +| n_updates | 11160 | +| policy_gradient_loss | 0.00778 | +| value_loss | 9.16 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -201 | +| time/ | | +| fps | 344 | +| iterations | 1118 | +| time_elapsed | 11618 | +| total_timesteps | 4006912 | +| train/ | | +| approx_kl | 0.026415596 | +| clip_fraction | 0.211 | +| clip_range | 0.155 | +| entropy_loss | -2.66 | +| explained_variance | 0.447 | +| learning_rate | 6e-05 | +| loss | 2.66 | +| n_updates | 11170 | +| policy_gradient_loss | 0.00288 | +| value_loss | 19.9 | +----------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -200 | +| time/ | | +| fps | 344 | +| iterations | 1119 | +| time_elapsed | 11629 | +| total_timesteps | 4010496 | +| train/ | | +| approx_kl | 0.061573576 | +| clip_fraction | 0.3 | +| clip_range | 0.155 | +| entropy_loss | -3.27 | +| explained_variance | 0.401 | +| learning_rate | 6e-05 | +| loss | 15.5 | +| n_updates | 11180 | +| policy_gradient_loss | 0.0153 | +| value_loss | 21 | +----------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -200 | +| time/ | | +| fps | 344 | +| iterations | 1120 | +| time_elapsed | 11640 | +| total_timesteps | 4014080 | +| train/ | | +| approx_kl | 0.07422925 | +| clip_fraction | 0.306 | +| clip_range | 0.155 | +| entropy_loss | -4.1 | +| explained_variance | 0.589 | +| learning_rate | 6e-05 | +| loss | 0.387 | +| n_updates | 11190 | +| policy_gradient_loss | 0.00997 | +| value_loss | 13.7 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.07e+03 | +| ep_rew_mean | -198 | +| time/ | | +| fps | 344 | +| iterations | 1121 | +| time_elapsed | 11651 | +| total_timesteps | 4017664 | +| train/ | | +| approx_kl | 0.048671126 | +| clip_fraction | 0.249 | +| clip_range | 0.155 | +| entropy_loss | -3.71 | +| explained_variance | 0.491 | +| learning_rate | 6e-05 | +| loss | 4.96 | +| n_updates | 11200 | +| policy_gradient_loss | 0.0112 | +| value_loss | 4.76 | +----------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -201 | +| time/ | | +| fps | 344 | +| iterations | 1122 | +| time_elapsed | 11660 | +| total_timesteps | 4021248 | +| train/ | | +| approx_kl | 0.28469458 | +| clip_fraction | 0.335 | +| clip_range | 0.155 | +| entropy_loss | -3.21 | +| explained_variance | 0.24 | +| learning_rate | 6e-05 | +| loss | 3.01 | +| n_updates | 11210 | +| policy_gradient_loss | 0.0231 | +| value_loss | 13.2 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -201 | +| time/ | | +| fps | 344 | +| iterations | 1123 | +| time_elapsed | 11670 | +| total_timesteps | 4024832 | +| train/ | | +| approx_kl | 0.1107897 | +| clip_fraction | 0.274 | +| clip_range | 0.155 | +| entropy_loss | -3.51 | +| explained_variance | 0.0963 | +| learning_rate | 6e-05 | +| loss | 2.03 | +| n_updates | 11220 | +| policy_gradient_loss | 0.0308 | +| value_loss | 8.5 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.11e+03 | +| ep_rew_mean | -203 | +| time/ | | +| fps | 344 | +| iterations | 1124 | +| time_elapsed | 11681 | +| total_timesteps | 4028416 | +| train/ | | +| approx_kl | 0.055620257 | +| clip_fraction | 0.272 | +| clip_range | 0.155 | +| entropy_loss | -3.73 | +| explained_variance | 0.485 | +| learning_rate | 6e-05 | +| loss | 1.24 | +| n_updates | 11230 | +| policy_gradient_loss | 0.0336 | +| value_loss | 5.3 | +----------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -203 | +| time/ | | +| fps | 344 | +| iterations | 1125 | +| time_elapsed | 11692 | +| total_timesteps | 4032000 | +| train/ | | +| approx_kl | 0.1519491 | +| clip_fraction | 0.425 | +| clip_range | 0.155 | +| entropy_loss | -5.58 | +| explained_variance | 0.275 | +| learning_rate | 6e-05 | +| loss | 1.83 | +| n_updates | 11240 | +| policy_gradient_loss | 0.038 | +| value_loss | 7.05 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -204 | +| time/ | | +| fps | 344 | +| iterations | 1126 | +| time_elapsed | 11704 | +| total_timesteps | 4035584 | +| train/ | | +| approx_kl | 0.22867821 | +| clip_fraction | 0.188 | +| clip_range | 0.155 | +| entropy_loss | -2.02 | +| explained_variance | 0.639 | +| learning_rate | 6e-05 | +| loss | 15.5 | +| n_updates | 11250 | +| policy_gradient_loss | 0.0146 | +| value_loss | 25.8 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -204 | +| time/ | | +| fps | 344 | +| iterations | 1127 | +| time_elapsed | 11714 | +| total_timesteps | 4039168 | +| train/ | | +| approx_kl | 0.06885595 | +| clip_fraction | 0.39 | +| clip_range | 0.155 | +| entropy_loss | -4.19 | +| explained_variance | 0.442 | +| learning_rate | 6e-05 | +| loss | 125 | +| n_updates | 11260 | +| policy_gradient_loss | 0.0356 | +| value_loss | 15.3 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -205 | +| time/ | | +| fps | 344 | +| iterations | 1128 | +| time_elapsed | 11724 | +| total_timesteps | 4042752 | +| train/ | | +| approx_kl | 0.07331877 | +| clip_fraction | 0.372 | +| clip_range | 0.155 | +| entropy_loss | -5.71 | +| explained_variance | 0.189 | +| learning_rate | 6e-05 | +| loss | 5.43 | +| n_updates | 11270 | +| policy_gradient_loss | 0.0352 | +| value_loss | 4.25 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -205 | +| time/ | | +| fps | 344 | +| iterations | 1129 | +| time_elapsed | 11734 | +| total_timesteps | 4046336 | +| train/ | | +| approx_kl | 0.08768354 | +| clip_fraction | 0.216 | +| clip_range | 0.155 | +| entropy_loss | -2.5 | +| explained_variance | 0.499 | +| learning_rate | 6e-05 | +| loss | 5.16 | +| n_updates | 11280 | +| policy_gradient_loss | 0.0169 | +| value_loss | 39.5 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -207 | +| time/ | | +| fps | 344 | +| iterations | 1130 | +| time_elapsed | 11745 | +| total_timesteps | 4049920 | +| train/ | | +| approx_kl | 0.06827061 | +| clip_fraction | 0.237 | +| clip_range | 0.155 | +| entropy_loss | -1.77 | +| explained_variance | 0.639 | +| learning_rate | 6e-05 | +| loss | 2.16 | +| n_updates | 11290 | +| policy_gradient_loss | 0.00992 | +| value_loss | 24.7 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -205 | +| time/ | | +| fps | 344 | +| iterations | 1131 | +| time_elapsed | 11756 | +| total_timesteps | 4053504 | +| train/ | | +| approx_kl | 0.03899594 | +| clip_fraction | 0.243 | +| clip_range | 0.155 | +| entropy_loss | -2.81 | +| explained_variance | 0.606 | +| learning_rate | 6e-05 | +| loss | 0.895 | +| n_updates | 11300 | +| policy_gradient_loss | 0.00913 | +| value_loss | 11.9 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -202 | +| time/ | | +| fps | 344 | +| iterations | 1132 | +| time_elapsed | 11767 | +| total_timesteps | 4057088 | +| train/ | | +| approx_kl | 0.12778908 | +| clip_fraction | 0.278 | +| clip_range | 0.155 | +| entropy_loss | -2.7 | +| explained_variance | 0.61 | +| learning_rate | 6e-05 | +| loss | 1.34 | +| n_updates | 11310 | +| policy_gradient_loss | 0.0526 | +| value_loss | 18.4 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -202 | +| time/ | | +| fps | 344 | +| iterations | 1133 | +| time_elapsed | 11777 | +| total_timesteps | 4060672 | +| train/ | | +| approx_kl | 0.0393003 | +| clip_fraction | 0.235 | +| clip_range | 0.155 | +| entropy_loss | -3.11 | +| explained_variance | 0.458 | +| learning_rate | 6e-05 | +| loss | 0.186 | +| n_updates | 11320 | +| policy_gradient_loss | -0.00107 | +| value_loss | 3.16 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -202 | +| time/ | | +| fps | 344 | +| iterations | 1134 | +| time_elapsed | 11786 | +| total_timesteps | 4064256 | +| train/ | | +| approx_kl | 0.030958274 | +| clip_fraction | 0.207 | +| clip_range | 0.155 | +| entropy_loss | -3.04 | +| explained_variance | 0.382 | +| learning_rate | 6e-05 | +| loss | 0.0838 | +| n_updates | 11330 | +| policy_gradient_loss | 0.00258 | +| value_loss | 4.87 | +----------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -203 | +| time/ | | +| fps | 344 | +| iterations | 1135 | +| time_elapsed | 11796 | +| total_timesteps | 4067840 | +| train/ | | +| approx_kl | 0.03918045 | +| clip_fraction | 0.234 | +| clip_range | 0.155 | +| entropy_loss | -3.32 | +| explained_variance | 0.439 | +| learning_rate | 6e-05 | +| loss | 3.34 | +| n_updates | 11340 | +| policy_gradient_loss | 0.00638 | +| value_loss | 2.82 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.23e+03 | +| ep_rew_mean | -203 | +| time/ | | +| fps | 344 | +| iterations | 1136 | +| time_elapsed | 11807 | +| total_timesteps | 4071424 | +| train/ | | +| approx_kl | 0.26537403 | +| clip_fraction | 0.397 | +| clip_range | 0.155 | +| entropy_loss | -5.24 | +| explained_variance | 0.178 | +| learning_rate | 6e-05 | +| loss | 0.801 | +| n_updates | 11350 | +| policy_gradient_loss | 0.0215 | +| value_loss | 8.11 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -205 | +| time/ | | +| fps | 344 | +| iterations | 1137 | +| time_elapsed | 11818 | +| total_timesteps | 4075008 | +| train/ | | +| approx_kl | 0.07161914 | +| clip_fraction | 0.339 | +| clip_range | 0.155 | +| entropy_loss | -3.69 | +| explained_variance | 0.0965 | +| learning_rate | 6e-05 | +| loss | 0.566 | +| n_updates | 11360 | +| policy_gradient_loss | 0.0239 | +| value_loss | 16 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -205 | +| time/ | | +| fps | 344 | +| iterations | 1138 | +| time_elapsed | 11829 | +| total_timesteps | 4078592 | +| train/ | | +| approx_kl | 0.38427177 | +| clip_fraction | 0.246 | +| clip_range | 0.155 | +| entropy_loss | -2.3 | +| explained_variance | 0.658 | +| learning_rate | 6e-05 | +| loss | 11.8 | +| n_updates | 11370 | +| policy_gradient_loss | 0.0141 | +| value_loss | 18.4 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -174 | +| time/ | | +| fps | 344 | +| iterations | 1139 | +| time_elapsed | 11839 | +| total_timesteps | 4082176 | +| train/ | | +| approx_kl | 0.11429783 | +| clip_fraction | 0.282 | +| clip_range | 0.155 | +| entropy_loss | -2 | +| explained_variance | -0.0115 | +| learning_rate | 6e-05 | +| loss | 6.74 | +| n_updates | 11380 | +| policy_gradient_loss | 0.0664 | +| value_loss | 3.34e+03 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -172 | +| time/ | | +| fps | 344 | +| iterations | 1140 | +| time_elapsed | 11849 | +| total_timesteps | 4085760 | +| train/ | | +| approx_kl | 0.32119083 | +| clip_fraction | 0.358 | +| clip_range | 0.155 | +| entropy_loss | -3.68 | +| explained_variance | 0.542 | +| learning_rate | 6e-05 | +| loss | 0.736 | +| n_updates | 11390 | +| policy_gradient_loss | 0.0489 | +| value_loss | 20.2 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -172 | +| time/ | | +| fps | 344 | +| iterations | 1141 | +| time_elapsed | 11860 | +| total_timesteps | 4089344 | +| train/ | | +| approx_kl | 0.26375866 | +| clip_fraction | 0.586 | +| clip_range | 0.155 | +| entropy_loss | -4.21 | +| explained_variance | 0.41 | +| learning_rate | 6e-05 | +| loss | 5.63 | +| n_updates | 11400 | +| policy_gradient_loss | 0.0758 | +| value_loss | 15.7 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -173 | +| time/ | | +| fps | 344 | +| iterations | 1142 | +| time_elapsed | 11871 | +| total_timesteps | 4092928 | +| train/ | | +| approx_kl | 0.2165912 | +| clip_fraction | 0.432 | +| clip_range | 0.155 | +| entropy_loss | -3.74 | +| explained_variance | 0.695 | +| learning_rate | 6e-05 | +| loss | 13.2 | +| n_updates | 11410 | +| policy_gradient_loss | 0.0509 | +| value_loss | 8.28 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -175 | +| time/ | | +| fps | 344 | +| iterations | 1143 | +| time_elapsed | 11882 | +| total_timesteps | 4096512 | +| train/ | | +| approx_kl | 0.13008325 | +| clip_fraction | 0.383 | +| clip_range | 0.155 | +| entropy_loss | -3.24 | +| explained_variance | 0.514 | +| learning_rate | 6e-05 | +| loss | 1.54 | +| n_updates | 11420 | +| policy_gradient_loss | 0.0329 | +| value_loss | 25.7 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -172 | +| time/ | | +| fps | 344 | +| iterations | 1144 | +| time_elapsed | 11892 | +| total_timesteps | 4100096 | +| train/ | | +| approx_kl | 0.2851152 | +| clip_fraction | 0.339 | +| clip_range | 0.155 | +| entropy_loss | -3.48 | +| explained_variance | 0.464 | +| learning_rate | 6e-05 | +| loss | 0.938 | +| n_updates | 11430 | +| policy_gradient_loss | 0.0226 | +| value_loss | 17 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -171 | +| time/ | | +| fps | 344 | +| iterations | 1145 | +| time_elapsed | 11902 | +| total_timesteps | 4103680 | +| train/ | | +| approx_kl | 0.03017726 | +| clip_fraction | 0.23 | +| clip_range | 0.155 | +| entropy_loss | -2.78 | +| explained_variance | 0.405 | +| learning_rate | 6e-05 | +| loss | 3.84 | +| n_updates | 11440 | +| policy_gradient_loss | 0.00631 | +| value_loss | 7.27 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 344 | +| iterations | 1146 | +| time_elapsed | 11912 | +| total_timesteps | 4107264 | +| train/ | | +| approx_kl | 0.16293119 | +| clip_fraction | 0.347 | +| clip_range | 0.155 | +| entropy_loss | -2.57 | +| explained_variance | 0.447 | +| learning_rate | 6e-05 | +| loss | 0.74 | +| n_updates | 11450 | +| policy_gradient_loss | 0.0427 | +| value_loss | 11.2 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 344 | +| iterations | 1147 | +| time_elapsed | 11922 | +| total_timesteps | 4110848 | +| train/ | | +| approx_kl | 0.06228005 | +| clip_fraction | 0.244 | +| clip_range | 0.155 | +| entropy_loss | -2.32 | +| explained_variance | 0.693 | +| learning_rate | 6e-05 | +| loss | 4.8 | +| n_updates | 11460 | +| policy_gradient_loss | 0.0115 | +| value_loss | 8.44 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1148 | +| time_elapsed | 11934 | +| total_timesteps | 4114432 | +| train/ | | +| approx_kl | 0.07964387 | +| clip_fraction | 0.315 | +| clip_range | 0.155 | +| entropy_loss | -2.39 | +| explained_variance | 0.488 | +| learning_rate | 6e-05 | +| loss | 3.75 | +| n_updates | 11470 | +| policy_gradient_loss | 0.0235 | +| value_loss | 15.2 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1149 | +| time_elapsed | 11945 | +| total_timesteps | 4118016 | +| train/ | | +| approx_kl | 0.06479435 | +| clip_fraction | 0.23 | +| clip_range | 0.155 | +| entropy_loss | -2.44 | +| explained_variance | 0.783 | +| learning_rate | 6e-05 | +| loss | 1.19 | +| n_updates | 11480 | +| policy_gradient_loss | 0.00678 | +| value_loss | 10.6 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 344 | +| iterations | 1150 | +| time_elapsed | 11955 | +| total_timesteps | 4121600 | +| train/ | | +| approx_kl | 0.05495425 | +| clip_fraction | 0.235 | +| clip_range | 0.155 | +| entropy_loss | -2.56 | +| explained_variance | 0.732 | +| learning_rate | 6e-05 | +| loss | 1.59 | +| n_updates | 11490 | +| policy_gradient_loss | 0.00546 | +| value_loss | 24.4 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1151 | +| time_elapsed | 11965 | +| total_timesteps | 4125184 | +| train/ | | +| approx_kl | 0.24103305 | +| clip_fraction | 0.484 | +| clip_range | 0.155 | +| entropy_loss | -4.44 | +| explained_variance | 0.549 | +| learning_rate | 6e-05 | +| loss | 1.03 | +| n_updates | 11500 | +| policy_gradient_loss | 0.036 | +| value_loss | 18.2 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1152 | +| time_elapsed | 11975 | +| total_timesteps | 4128768 | +| train/ | | +| approx_kl | 0.25966242 | +| clip_fraction | 0.498 | +| clip_range | 0.155 | +| entropy_loss | -5.5 | +| explained_variance | 0.356 | +| learning_rate | 6e-05 | +| loss | 0.904 | +| n_updates | 11510 | +| policy_gradient_loss | 0.0475 | +| value_loss | 16.5 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1153 | +| time_elapsed | 11986 | +| total_timesteps | 4132352 | +| train/ | | +| approx_kl | 0.1660142 | +| clip_fraction | 0.41 | +| clip_range | 0.155 | +| entropy_loss | -6.09 | +| explained_variance | 0.171 | +| learning_rate | 6e-05 | +| loss | 1.5 | +| n_updates | 11520 | +| policy_gradient_loss | 0.0553 | +| value_loss | 12.8 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -158 | +| time/ | | +| fps | 344 | +| iterations | 1154 | +| time_elapsed | 11997 | +| total_timesteps | 4135936 | +| train/ | | +| approx_kl | 0.34227842 | +| clip_fraction | 0.342 | +| clip_range | 0.155 | +| entropy_loss | -4.13 | +| explained_variance | 0.25 | +| learning_rate | 6e-05 | +| loss | 14.3 | +| n_updates | 11530 | +| policy_gradient_loss | 0.023 | +| value_loss | 11.8 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -157 | +| time/ | | +| fps | 344 | +| iterations | 1155 | +| time_elapsed | 12008 | +| total_timesteps | 4139520 | +| train/ | | +| approx_kl | 0.2117643 | +| clip_fraction | 0.346 | +| clip_range | 0.155 | +| entropy_loss | -3.23 | +| explained_variance | 0.359 | +| learning_rate | 6e-05 | +| loss | 5.32 | +| n_updates | 11540 | +| policy_gradient_loss | 0.0381 | +| value_loss | 7.39 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -156 | +| time/ | | +| fps | 344 | +| iterations | 1156 | +| time_elapsed | 12018 | +| total_timesteps | 4143104 | +| train/ | | +| approx_kl | 0.12219299 | +| clip_fraction | 0.308 | +| clip_range | 0.155 | +| entropy_loss | -3.44 | +| explained_variance | 0.619 | +| learning_rate | 6e-05 | +| loss | 2.81 | +| n_updates | 11550 | +| policy_gradient_loss | 0.0172 | +| value_loss | 7.79 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -155 | +| time/ | | +| fps | 344 | +| iterations | 1157 | +| time_elapsed | 12028 | +| total_timesteps | 4146688 | +| train/ | | +| approx_kl | 0.24397667 | +| clip_fraction | 0.585 | +| clip_range | 0.155 | +| entropy_loss | -4.76 | +| explained_variance | 0.585 | +| learning_rate | 6e-05 | +| loss | 0.6 | +| n_updates | 11560 | +| policy_gradient_loss | 0.087 | +| value_loss | 6.28 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.36e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 344 | +| iterations | 1158 | +| time_elapsed | 12037 | +| total_timesteps | 4150272 | +| train/ | | +| approx_kl | 0.10254913 | +| clip_fraction | 0.403 | +| clip_range | 0.155 | +| entropy_loss | -2.97 | +| explained_variance | 0.619 | +| learning_rate | 6e-05 | +| loss | 19.8 | +| n_updates | 11570 | +| policy_gradient_loss | 0.0558 | +| value_loss | 9.06 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -149 | +| time/ | | +| fps | 344 | +| iterations | 1159 | +| time_elapsed | 12049 | +| total_timesteps | 4153856 | +| train/ | | +| approx_kl | 0.10107447 | +| clip_fraction | 0.357 | +| clip_range | 0.155 | +| entropy_loss | -4.54 | +| explained_variance | 0.228 | +| learning_rate | 6e-05 | +| loss | 0.361 | +| n_updates | 11580 | +| policy_gradient_loss | 0.0207 | +| value_loss | 8.75 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 344 | +| iterations | 1160 | +| time_elapsed | 12060 | +| total_timesteps | 4157440 | +| train/ | | +| approx_kl | 0.17339785 | +| clip_fraction | 0.289 | +| clip_range | 0.155 | +| entropy_loss | -3.87 | +| explained_variance | 0.0439 | +| learning_rate | 6e-05 | +| loss | 1.48 | +| n_updates | 11590 | +| policy_gradient_loss | 0.0358 | +| value_loss | 10.9 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.36e+03 | +| ep_rew_mean | -149 | +| time/ | | +| fps | 344 | +| iterations | 1161 | +| time_elapsed | 12070 | +| total_timesteps | 4161024 | +| train/ | | +| approx_kl | 0.08044513 | +| clip_fraction | 0.304 | +| clip_range | 0.155 | +| entropy_loss | -4.96 | +| explained_variance | 0.162 | +| learning_rate | 6e-05 | +| loss | 1.49 | +| n_updates | 11600 | +| policy_gradient_loss | 0.0197 | +| value_loss | 7.16 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1162 | +| time_elapsed | 12080 | +| total_timesteps | 4164608 | +| train/ | | +| approx_kl | 0.25109667 | +| clip_fraction | 0.336 | +| clip_range | 0.155 | +| entropy_loss | -5.27 | +| explained_variance | 0.625 | +| learning_rate | 6e-05 | +| loss | 3.23 | +| n_updates | 11610 | +| policy_gradient_loss | 0.0184 | +| value_loss | 29.5 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 344 | +| iterations | 1163 | +| time_elapsed | 12090 | +| total_timesteps | 4168192 | +| train/ | | +| approx_kl | 0.17442669 | +| clip_fraction | 0.299 | +| clip_range | 0.155 | +| entropy_loss | -2.98 | +| explained_variance | 0.686 | +| learning_rate | 6e-05 | +| loss | 9.59 | +| n_updates | 11620 | +| policy_gradient_loss | 0.0274 | +| value_loss | 16 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 344 | +| iterations | 1164 | +| time_elapsed | 12101 | +| total_timesteps | 4171776 | +| train/ | | +| approx_kl | 0.4997339 | +| clip_fraction | 0.327 | +| clip_range | 0.155 | +| entropy_loss | -2.29 | +| explained_variance | 0.763 | +| learning_rate | 6e-05 | +| loss | 2.45 | +| n_updates | 11630 | +| policy_gradient_loss | 0.0239 | +| value_loss | 26.3 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -151 | +| time/ | | +| fps | 344 | +| iterations | 1165 | +| time_elapsed | 12112 | +| total_timesteps | 4175360 | +| train/ | | +| approx_kl | 0.1510102 | +| clip_fraction | 0.369 | +| clip_range | 0.155 | +| entropy_loss | -5.4 | +| explained_variance | 0.33 | +| learning_rate | 6e-05 | +| loss | 3.97 | +| n_updates | 11640 | +| policy_gradient_loss | 0.037 | +| value_loss | 16.5 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 344 | +| iterations | 1166 | +| time_elapsed | 12123 | +| total_timesteps | 4178944 | +| train/ | | +| approx_kl | 0.22221276 | +| clip_fraction | 0.402 | +| clip_range | 0.155 | +| entropy_loss | -4.91 | +| explained_variance | 0.204 | +| learning_rate | 6e-05 | +| loss | 0.998 | +| n_updates | 11650 | +| policy_gradient_loss | 0.0336 | +| value_loss | 12.6 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 344 | +| iterations | 1167 | +| time_elapsed | 12132 | +| total_timesteps | 4182528 | +| train/ | | +| approx_kl | 0.097121276 | +| clip_fraction | 0.283 | +| clip_range | 0.155 | +| entropy_loss | -3.5 | +| explained_variance | 0.626 | +| learning_rate | 6e-05 | +| loss | 1.42 | +| n_updates | 11660 | +| policy_gradient_loss | 0.00813 | +| value_loss | 21.1 | +----------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.31e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 344 | +| iterations | 1168 | +| time_elapsed | 12142 | +| total_timesteps | 4186112 | +| train/ | | +| approx_kl | 0.14011608 | +| clip_fraction | 0.313 | +| clip_range | 0.155 | +| entropy_loss | -4.02 | +| explained_variance | 0.752 | +| learning_rate | 6e-05 | +| loss | 0.433 | +| n_updates | 11670 | +| policy_gradient_loss | 0.0284 | +| value_loss | 9.61 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1169 | +| time_elapsed | 12152 | +| total_timesteps | 4189696 | +| train/ | | +| approx_kl | 0.095382966 | +| clip_fraction | 0.204 | +| clip_range | 0.155 | +| entropy_loss | -1.97 | +| explained_variance | 0.669 | +| learning_rate | 6e-05 | +| loss | 4.48 | +| n_updates | 11680 | +| policy_gradient_loss | 0.0182 | +| value_loss | 27.4 | +----------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 344 | +| iterations | 1170 | +| time_elapsed | 12163 | +| total_timesteps | 4193280 | +| train/ | | +| approx_kl | 0.37714094 | +| clip_fraction | 0.411 | +| clip_range | 0.155 | +| entropy_loss | -6.66 | +| explained_variance | 0.723 | +| learning_rate | 6e-05 | +| loss | 6.25 | +| n_updates | 11690 | +| policy_gradient_loss | 0.0274 | +| value_loss | 18.4 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -151 | +| time/ | | +| fps | 344 | +| iterations | 1171 | +| time_elapsed | 12174 | +| total_timesteps | 4196864 | +| train/ | | +| approx_kl | 0.5537872 | +| clip_fraction | 0.362 | +| clip_range | 0.155 | +| entropy_loss | -7.26 | +| explained_variance | 0.0433 | +| learning_rate | 6e-05 | +| loss | 65.7 | +| n_updates | 11700 | +| policy_gradient_loss | 0.0462 | +| value_loss | 34.8 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 344 | +| iterations | 1172 | +| time_elapsed | 12185 | +| total_timesteps | 4200448 | +| train/ | | +| approx_kl | 0.5549347 | +| clip_fraction | 0.31 | +| clip_range | 0.155 | +| entropy_loss | -6.68 | +| explained_variance | 0.102 | +| learning_rate | 6e-05 | +| loss | 14.2 | +| n_updates | 11710 | +| policy_gradient_loss | 0.0568 | +| value_loss | 7.64 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 344 | +| iterations | 1173 | +| time_elapsed | 12195 | +| total_timesteps | 4204032 | +| train/ | | +| approx_kl | 0.080458745 | +| clip_fraction | 0.235 | +| clip_range | 0.155 | +| entropy_loss | -3.77 | +| explained_variance | 0.389 | +| learning_rate | 6e-05 | +| loss | 15.1 | +| n_updates | 11720 | +| policy_gradient_loss | 0.0123 | +| value_loss | 14.5 | +----------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 344 | +| iterations | 1174 | +| time_elapsed | 12205 | +| total_timesteps | 4207616 | +| train/ | | +| approx_kl | 0.06477227 | +| clip_fraction | 0.203 | +| clip_range | 0.155 | +| entropy_loss | -2.89 | +| explained_variance | 0.379 | +| learning_rate | 6e-05 | +| loss | 5.68 | +| n_updates | 11730 | +| policy_gradient_loss | 0.016 | +| value_loss | 14.2 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 344 | +| iterations | 1175 | +| time_elapsed | 12215 | +| total_timesteps | 4211200 | +| train/ | | +| approx_kl | 0.12941422 | +| clip_fraction | 0.287 | +| clip_range | 0.155 | +| entropy_loss | -3.44 | +| explained_variance | 0.531 | +| learning_rate | 6e-05 | +| loss | 2.46 | +| n_updates | 11740 | +| policy_gradient_loss | 0.0147 | +| value_loss | 21.9 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.31e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 344 | +| iterations | 1176 | +| time_elapsed | 12226 | +| total_timesteps | 4214784 | +| train/ | | +| approx_kl | 0.10784393 | +| clip_fraction | 0.262 | +| clip_range | 0.155 | +| entropy_loss | -4.04 | +| explained_variance | 0.346 | +| learning_rate | 6e-05 | +| loss | 4.09 | +| n_updates | 11750 | +| policy_gradient_loss | 0.0131 | +| value_loss | 32.3 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 344 | +| iterations | 1177 | +| time_elapsed | 12237 | +| total_timesteps | 4218368 | +| train/ | | +| approx_kl | 0.09113222 | +| clip_fraction | 0.229 | +| clip_range | 0.155 | +| entropy_loss | -3.51 | +| explained_variance | 0.545 | +| learning_rate | 6e-05 | +| loss | 0.881 | +| n_updates | 11760 | +| policy_gradient_loss | 0.0132 | +| value_loss | 9.06 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 344 | +| iterations | 1178 | +| time_elapsed | 12249 | +| total_timesteps | 4221952 | +| train/ | | +| approx_kl | 0.17451833 | +| clip_fraction | 0.256 | +| clip_range | 0.155 | +| entropy_loss | -2.37 | +| explained_variance | 0.734 | +| learning_rate | 6e-05 | +| loss | 2.19 | +| n_updates | 11770 | +| policy_gradient_loss | 0.0208 | +| value_loss | 27.6 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.23e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 344 | +| iterations | 1179 | +| time_elapsed | 12258 | +| total_timesteps | 4225536 | +| train/ | | +| approx_kl | 0.11252836 | +| clip_fraction | 0.275 | +| clip_range | 0.155 | +| entropy_loss | -4.69 | +| explained_variance | 0.692 | +| learning_rate | 6e-05 | +| loss | 4.53 | +| n_updates | 11780 | +| policy_gradient_loss | 0.0274 | +| value_loss | 7.54 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 344 | +| iterations | 1180 | +| time_elapsed | 12268 | +| total_timesteps | 4229120 | +| train/ | | +| approx_kl | 0.38960108 | +| clip_fraction | 0.337 | +| clip_range | 0.155 | +| entropy_loss | -4.46 | +| explained_variance | 0.296 | +| learning_rate | 6e-05 | +| loss | 2.89 | +| n_updates | 11790 | +| policy_gradient_loss | 0.0366 | +| value_loss | 40.9 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1181 | +| time_elapsed | 12278 | +| total_timesteps | 4232704 | +| train/ | | +| approx_kl | 0.25895402 | +| clip_fraction | 0.319 | +| clip_range | 0.155 | +| entropy_loss | -3.77 | +| explained_variance | 0.295 | +| learning_rate | 6e-05 | +| loss | 129 | +| n_updates | 11800 | +| policy_gradient_loss | 0.029 | +| value_loss | 23.8 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.09e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1182 | +| time_elapsed | 12289 | +| total_timesteps | 4236288 | +| train/ | | +| approx_kl | 0.12826337 | +| clip_fraction | 0.291 | +| clip_range | 0.155 | +| entropy_loss | -3.71 | +| explained_variance | 0.393 | +| learning_rate | 6e-05 | +| loss | 1.23 | +| n_updates | 11810 | +| policy_gradient_loss | 0.0189 | +| value_loss | 9.64 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.08e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 344 | +| iterations | 1183 | +| time_elapsed | 12300 | +| total_timesteps | 4239872 | +| train/ | | +| approx_kl | 0.17975505 | +| clip_fraction | 0.237 | +| clip_range | 0.155 | +| entropy_loss | -3.21 | +| explained_variance | 0.86 | +| learning_rate | 6e-05 | +| loss | 3.93 | +| n_updates | 11820 | +| policy_gradient_loss | 0.0173 | +| value_loss | 16.4 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1184 | +| time_elapsed | 12311 | +| total_timesteps | 4243456 | +| train/ | | +| approx_kl | 0.11089786 | +| clip_fraction | 0.284 | +| clip_range | 0.155 | +| entropy_loss | -4.02 | +| explained_variance | 0.798 | +| learning_rate | 6e-05 | +| loss | 2.9 | +| n_updates | 11830 | +| policy_gradient_loss | 0.0183 | +| value_loss | 16.2 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 344 | +| iterations | 1185 | +| time_elapsed | 12321 | +| total_timesteps | 4247040 | +| train/ | | +| approx_kl | 0.19779594 | +| clip_fraction | 0.237 | +| clip_range | 0.155 | +| entropy_loss | -6.09 | +| explained_variance | 0.623 | +| learning_rate | 6e-05 | +| loss | 0.519 | +| n_updates | 11840 | +| policy_gradient_loss | 0.0317 | +| value_loss | 11 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 344 | +| iterations | 1186 | +| time_elapsed | 12331 | +| total_timesteps | 4250624 | +| train/ | | +| approx_kl | 0.43758675 | +| clip_fraction | 0.256 | +| clip_range | 0.155 | +| entropy_loss | -6 | +| explained_variance | 0.279 | +| learning_rate | 6e-05 | +| loss | 2.12 | +| n_updates | 11850 | +| policy_gradient_loss | 0.0454 | +| value_loss | 22.3 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.07e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 344 | +| iterations | 1187 | +| time_elapsed | 12342 | +| total_timesteps | 4254208 | +| train/ | | +| approx_kl | 0.4023052 | +| clip_fraction | 0.188 | +| clip_range | 0.155 | +| entropy_loss | -6.53 | +| explained_variance | 0.394 | +| learning_rate | 6e-05 | +| loss | 3.86 | +| n_updates | 11860 | +| policy_gradient_loss | 0.0225 | +| value_loss | 17.8 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.07e+03 | +| ep_rew_mean | -142 | +| time/ | | +| fps | 344 | +| iterations | 1188 | +| time_elapsed | 12353 | +| total_timesteps | 4257792 | +| train/ | | +| approx_kl | 0.21985742 | +| clip_fraction | 0.165 | +| clip_range | 0.155 | +| entropy_loss | -7.61 | +| explained_variance | 0.22 | +| learning_rate | 6e-05 | +| loss | 4.61 | +| n_updates | 11870 | +| policy_gradient_loss | 0.0323 | +| value_loss | 10.3 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.07e+03 | +| ep_rew_mean | -141 | +| time/ | | +| fps | 344 | +| iterations | 1189 | +| time_elapsed | 12364 | +| total_timesteps | 4261376 | +| train/ | | +| approx_kl | 0.24966078 | +| clip_fraction | 0.227 | +| clip_range | 0.155 | +| entropy_loss | -7.44 | +| explained_variance | 0.0709 | +| learning_rate | 6e-05 | +| loss | 2.41 | +| n_updates | 11880 | +| policy_gradient_loss | 0.054 | +| value_loss | 11 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.08e+03 | +| ep_rew_mean | -142 | +| time/ | | +| fps | 344 | +| iterations | 1190 | +| time_elapsed | 12374 | +| total_timesteps | 4264960 | +| train/ | | +| approx_kl | 0.5366675 | +| clip_fraction | 0.216 | +| clip_range | 0.155 | +| entropy_loss | -7.22 | +| explained_variance | 0.332 | +| learning_rate | 6e-05 | +| loss | 0.0653 | +| n_updates | 11890 | +| policy_gradient_loss | 0.0618 | +| value_loss | 5.71 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.98e+03 | +| ep_rew_mean | -137 | +| time/ | | +| fps | 344 | +| iterations | 1191 | +| time_elapsed | 12384 | +| total_timesteps | 4268544 | +| train/ | | +| approx_kl | 0.37734753 | +| clip_fraction | 0.374 | +| clip_range | 0.155 | +| entropy_loss | -4.93 | +| explained_variance | 0.588 | +| learning_rate | 6e-05 | +| loss | 0.724 | +| n_updates | 11900 | +| policy_gradient_loss | 0.0621 | +| value_loss | 9.91 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.98e+03 | +| ep_rew_mean | -135 | +| time/ | | +| fps | 344 | +| iterations | 1192 | +| time_elapsed | 12393 | +| total_timesteps | 4272128 | +| train/ | | +| approx_kl | 0.46598336 | +| clip_fraction | 0.332 | +| clip_range | 0.155 | +| entropy_loss | -6.3 | +| explained_variance | 0.102 | +| learning_rate | 6e-05 | +| loss | 39.5 | +| n_updates | 11910 | +| policy_gradient_loss | 0.0687 | +| value_loss | 12.9 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 344 | +| iterations | 1193 | +| time_elapsed | 12405 | +| total_timesteps | 4275712 | +| train/ | | +| approx_kl | 0.31063503 | +| clip_fraction | 0.356 | +| clip_range | 0.155 | +| entropy_loss | -5.36 | +| explained_variance | 0.338 | +| learning_rate | 6e-05 | +| loss | 0.436 | +| n_updates | 11920 | +| policy_gradient_loss | 0.0393 | +| value_loss | 15.1 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1194 | +| time_elapsed | 12416 | +| total_timesteps | 4279296 | +| train/ | | +| approx_kl | 0.3023428 | +| clip_fraction | 0.273 | +| clip_range | 0.155 | +| entropy_loss | -5.78 | +| explained_variance | 0.674 | +| learning_rate | 6e-05 | +| loss | 0.618 | +| n_updates | 11930 | +| policy_gradient_loss | 0.0377 | +| value_loss | 9.59 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 344 | +| iterations | 1195 | +| time_elapsed | 12428 | +| total_timesteps | 4282880 | +| train/ | | +| approx_kl | 0.29946795 | +| clip_fraction | 0.361 | +| clip_range | 0.155 | +| entropy_loss | -4.25 | +| explained_variance | 0.292 | +| learning_rate | 6e-05 | +| loss | 6.48 | +| n_updates | 11940 | +| policy_gradient_loss | 0.0476 | +| value_loss | 17 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 344 | +| iterations | 1196 | +| time_elapsed | 12438 | +| total_timesteps | 4286464 | +| train/ | | +| approx_kl | 0.6271512 | +| clip_fraction | 0.25 | +| clip_range | 0.155 | +| entropy_loss | -4.66 | +| explained_variance | 0.782 | +| learning_rate | 6e-05 | +| loss | 1.41 | +| n_updates | 11950 | +| policy_gradient_loss | 0.0212 | +| value_loss | 16.6 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1197 | +| time_elapsed | 12448 | +| total_timesteps | 4290048 | +| train/ | | +| approx_kl | 0.2086886 | +| clip_fraction | 0.304 | +| clip_range | 0.155 | +| entropy_loss | -4.58 | +| explained_variance | 0.497 | +| learning_rate | 6e-05 | +| loss | 18.8 | +| n_updates | 11960 | +| policy_gradient_loss | 0.0345 | +| value_loss | 15.7 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1198 | +| time_elapsed | 12458 | +| total_timesteps | 4293632 | +| train/ | | +| approx_kl | 0.22079955 | +| clip_fraction | 0.287 | +| clip_range | 0.155 | +| entropy_loss | -5.98 | +| explained_variance | 0.296 | +| learning_rate | 6e-05 | +| loss | 0.332 | +| n_updates | 11970 | +| policy_gradient_loss | 0.0417 | +| value_loss | 7.63 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 344 | +| iterations | 1199 | +| time_elapsed | 12468 | +| total_timesteps | 4297216 | +| train/ | | +| approx_kl | 0.16933452 | +| clip_fraction | 0.324 | +| clip_range | 0.155 | +| entropy_loss | -5.96 | +| explained_variance | 0.259 | +| learning_rate | 6e-05 | +| loss | 0.43 | +| n_updates | 11980 | +| policy_gradient_loss | 0.0503 | +| value_loss | 3.76 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 344 | +| iterations | 1200 | +| time_elapsed | 12479 | +| total_timesteps | 4300800 | +| train/ | | +| approx_kl | 0.58306664 | +| clip_fraction | 0.369 | +| clip_range | 0.155 | +| entropy_loss | -5.52 | +| explained_variance | 0.606 | +| learning_rate | 6e-05 | +| loss | 5.66 | +| n_updates | 11990 | +| policy_gradient_loss | 0.0421 | +| value_loss | 26 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 344 | +| iterations | 1201 | +| time_elapsed | 12490 | +| total_timesteps | 4304384 | +| train/ | | +| approx_kl | 0.42173138 | +| clip_fraction | 0.306 | +| clip_range | 0.155 | +| entropy_loss | -3.68 | +| explained_variance | 0.716 | +| learning_rate | 6e-05 | +| loss | 1.69 | +| n_updates | 12000 | +| policy_gradient_loss | 0.0358 | +| value_loss | 18 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 344 | +| iterations | 1202 | +| time_elapsed | 12500 | +| total_timesteps | 4307968 | +| train/ | | +| approx_kl | 0.22598174 | +| clip_fraction | 0.356 | +| clip_range | 0.155 | +| entropy_loss | -4.15 | +| explained_variance | 0.307 | +| learning_rate | 6e-05 | +| loss | 3.38 | +| n_updates | 12010 | +| policy_gradient_loss | 0.0236 | +| value_loss | 19.4 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1203 | +| time_elapsed | 12509 | +| total_timesteps | 4311552 | +| train/ | | +| approx_kl | 0.5135764 | +| clip_fraction | 0.198 | +| clip_range | 0.155 | +| entropy_loss | -6.1 | +| explained_variance | 0.217 | +| learning_rate | 6e-05 | +| loss | 3.04 | +| n_updates | 12020 | +| policy_gradient_loss | 0.0163 | +| value_loss | 19.8 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1204 | +| time_elapsed | 12520 | +| total_timesteps | 4315136 | +| train/ | | +| approx_kl | 0.23232244 | +| clip_fraction | 0.107 | +| clip_range | 0.155 | +| entropy_loss | -7.67 | +| explained_variance | 0.088 | +| learning_rate | 6e-05 | +| loss | 0.101 | +| n_updates | 12030 | +| policy_gradient_loss | 0.105 | +| value_loss | 23.3 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -163 | +| time/ | | +| fps | 344 | +| iterations | 1205 | +| time_elapsed | 12531 | +| total_timesteps | 4318720 | +| train/ | | +| approx_kl | 0.25884727 | +| clip_fraction | 0.188 | +| clip_range | 0.155 | +| entropy_loss | -3.28 | +| explained_variance | 0.626 | +| learning_rate | 6e-05 | +| loss | 1.93 | +| n_updates | 12040 | +| policy_gradient_loss | 0.0137 | +| value_loss | 28.6 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1206 | +| time_elapsed | 12542 | +| total_timesteps | 4322304 | +| train/ | | +| approx_kl | 0.32225972 | +| clip_fraction | 0.234 | +| clip_range | 0.155 | +| entropy_loss | -5.08 | +| explained_variance | 0.394 | +| learning_rate | 6e-05 | +| loss | 2.84 | +| n_updates | 12050 | +| policy_gradient_loss | 0.0335 | +| value_loss | 10.1 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -160 | +| time/ | | +| fps | 344 | +| iterations | 1207 | +| time_elapsed | 12552 | +| total_timesteps | 4325888 | +| train/ | | +| approx_kl | 0.58576244 | +| clip_fraction | 0.397 | +| clip_range | 0.155 | +| entropy_loss | -5.47 | +| explained_variance | 0.764 | +| learning_rate | 6e-05 | +| loss | 1.62 | +| n_updates | 12060 | +| policy_gradient_loss | 0.0765 | +| value_loss | 11.4 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.82e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1208 | +| time_elapsed | 12562 | +| total_timesteps | 4329472 | +| train/ | | +| approx_kl | 0.24983458 | +| clip_fraction | 0.23 | +| clip_range | 0.155 | +| entropy_loss | -3.31 | +| explained_variance | 0.662 | +| learning_rate | 6e-05 | +| loss | 4.52 | +| n_updates | 12070 | +| policy_gradient_loss | 0.0262 | +| value_loss | 10.2 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -160 | +| time/ | | +| fps | 344 | +| iterations | 1209 | +| time_elapsed | 12572 | +| total_timesteps | 4333056 | +| train/ | | +| approx_kl | 0.26718673 | +| clip_fraction | 0.337 | +| clip_range | 0.155 | +| entropy_loss | -3.92 | +| explained_variance | 0.315 | +| learning_rate | 6e-05 | +| loss | 4.03 | +| n_updates | 12080 | +| policy_gradient_loss | 0.0424 | +| value_loss | 8.02 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.81e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1210 | +| time_elapsed | 12584 | +| total_timesteps | 4336640 | +| train/ | | +| approx_kl | 0.32697436 | +| clip_fraction | 0.268 | +| clip_range | 0.155 | +| entropy_loss | -4.37 | +| explained_variance | 0.534 | +| learning_rate | 6e-05 | +| loss | 1.64 | +| n_updates | 12090 | +| policy_gradient_loss | 0.0351 | +| value_loss | 7.73 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.81e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1211 | +| time_elapsed | 12595 | +| total_timesteps | 4340224 | +| train/ | | +| approx_kl | 0.117669225 | +| clip_fraction | 0.262 | +| clip_range | 0.155 | +| entropy_loss | -2.99 | +| explained_variance | 0.318 | +| learning_rate | 6e-05 | +| loss | 1.6 | +| n_updates | 12100 | +| policy_gradient_loss | 0.0238 | +| value_loss | 19.5 | +----------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -158 | +| time/ | | +| fps | 344 | +| iterations | 1212 | +| time_elapsed | 12606 | +| total_timesteps | 4343808 | +| train/ | | +| approx_kl | 0.4422379 | +| clip_fraction | 0.168 | +| clip_range | 0.155 | +| entropy_loss | -5.05 | +| explained_variance | 0.272 | +| learning_rate | 6e-05 | +| loss | 7.23 | +| n_updates | 12110 | +| policy_gradient_loss | 0.0139 | +| value_loss | 9.72 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -160 | +| time/ | | +| fps | 344 | +| iterations | 1213 | +| time_elapsed | 12616 | +| total_timesteps | 4347392 | +| train/ | | +| approx_kl | 0.28994533 | +| clip_fraction | 0.171 | +| clip_range | 0.155 | +| entropy_loss | -4.29 | +| explained_variance | 0.556 | +| learning_rate | 6e-05 | +| loss | 3.06 | +| n_updates | 12120 | +| policy_gradient_loss | 0.0189 | +| value_loss | 10.9 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1214 | +| time_elapsed | 12626 | +| total_timesteps | 4350976 | +| train/ | | +| approx_kl | 0.48653618 | +| clip_fraction | 0.237 | +| clip_range | 0.155 | +| entropy_loss | -5.84 | +| explained_variance | 0.149 | +| learning_rate | 6e-05 | +| loss | 29.4 | +| n_updates | 12130 | +| policy_gradient_loss | 0.023 | +| value_loss | 36.6 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -158 | +| time/ | | +| fps | 344 | +| iterations | 1215 | +| time_elapsed | 12636 | +| total_timesteps | 4354560 | +| train/ | | +| approx_kl | 0.47821397 | +| clip_fraction | 0.264 | +| clip_range | 0.155 | +| entropy_loss | -6.35 | +| explained_variance | 0.124 | +| learning_rate | 6e-05 | +| loss | 0.165 | +| n_updates | 12140 | +| policy_gradient_loss | 0.0337 | +| value_loss | 22.7 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -158 | +| time/ | | +| fps | 344 | +| iterations | 1216 | +| time_elapsed | 12647 | +| total_timesteps | 4358144 | +| train/ | | +| approx_kl | 0.13033058 | +| clip_fraction | 0.134 | +| clip_range | 0.155 | +| entropy_loss | -7.28 | +| explained_variance | 0.0783 | +| learning_rate | 6e-05 | +| loss | 20.8 | +| n_updates | 12150 | +| policy_gradient_loss | 0.0226 | +| value_loss | 17.4 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -155 | +| time/ | | +| fps | 344 | +| iterations | 1217 | +| time_elapsed | 12657 | +| total_timesteps | 4361728 | +| train/ | | +| approx_kl | 0.21152043 | +| clip_fraction | 0.177 | +| clip_range | 0.155 | +| entropy_loss | -6.95 | +| explained_variance | 0.0506 | +| learning_rate | 6e-05 | +| loss | 2.73 | +| n_updates | 12160 | +| policy_gradient_loss | 0.0584 | +| value_loss | 16.6 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 344 | +| iterations | 1218 | +| time_elapsed | 12668 | +| total_timesteps | 4365312 | +| train/ | | +| approx_kl | 0.11319224 | +| clip_fraction | 0.0936 | +| clip_range | 0.155 | +| entropy_loss | -7.51 | +| explained_variance | 0.19 | +| learning_rate | 6e-05 | +| loss | 130 | +| n_updates | 12170 | +| policy_gradient_loss | 0.0266 | +| value_loss | 21 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 344 | +| iterations | 1219 | +| time_elapsed | 12678 | +| total_timesteps | 4368896 | +| train/ | | +| approx_kl | 0.19908898 | +| clip_fraction | 0.27 | +| clip_range | 0.155 | +| entropy_loss | -3.44 | +| explained_variance | 0.307 | +| learning_rate | 6e-05 | +| loss | 6.3 | +| n_updates | 12180 | +| policy_gradient_loss | 0.0243 | +| value_loss | 13.2 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 344 | +| iterations | 1220 | +| time_elapsed | 12688 | +| total_timesteps | 4372480 | +| train/ | | +| approx_kl | 0.47072077 | +| clip_fraction | 0.188 | +| clip_range | 0.155 | +| entropy_loss | -6.75 | +| explained_variance | 0.131 | +| learning_rate | 6e-05 | +| loss | 2.84 | +| n_updates | 12190 | +| policy_gradient_loss | 0.0288 | +| value_loss | 12.8 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 344 | +| iterations | 1221 | +| time_elapsed | 12698 | +| total_timesteps | 4376064 | +| train/ | | +| approx_kl | 0.43204793 | +| clip_fraction | 0.239 | +| clip_range | 0.155 | +| entropy_loss | -4.49 | +| explained_variance | 0.19 | +| learning_rate | 6e-05 | +| loss | 6.68 | +| n_updates | 12200 | +| policy_gradient_loss | 0.0352 | +| value_loss | 13.9 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -133 | +| time/ | | +| fps | 344 | +| iterations | 1222 | +| time_elapsed | 12708 | +| total_timesteps | 4379648 | +| train/ | | +| approx_kl | 0.38301852 | +| clip_fraction | 0.336 | +| clip_range | 0.155 | +| entropy_loss | -4.59 | +| explained_variance | 0.202 | +| learning_rate | 6e-05 | +| loss | 7.26 | +| n_updates | 12210 | +| policy_gradient_loss | 0.0447 | +| value_loss | 12.4 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -134 | +| time/ | | +| fps | 344 | +| iterations | 1223 | +| time_elapsed | 12718 | +| total_timesteps | 4383232 | +| train/ | | +| approx_kl | 0.49113765 | +| clip_fraction | 0.197 | +| clip_range | 0.155 | +| entropy_loss | -6.32 | +| explained_variance | 0.363 | +| learning_rate | 6e-05 | +| loss | 1.65 | +| n_updates | 12220 | +| policy_gradient_loss | 0.0285 | +| value_loss | 13.9 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 344 | +| iterations | 1224 | +| time_elapsed | 12728 | +| total_timesteps | 4386816 | +| train/ | | +| approx_kl | 0.73387855 | +| clip_fraction | 0.219 | +| clip_range | 0.155 | +| entropy_loss | -5.29 | +| explained_variance | 0.156 | +| learning_rate | 6e-05 | +| loss | 3.25 | +| n_updates | 12230 | +| policy_gradient_loss | 0.0276 | +| value_loss | 23.1 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 344 | +| iterations | 1225 | +| time_elapsed | 12738 | +| total_timesteps | 4390400 | +| train/ | | +| approx_kl | 1.0469902 | +| clip_fraction | 0.177 | +| clip_range | 0.155 | +| entropy_loss | -6.25 | +| explained_variance | 0.185 | +| learning_rate | 6e-05 | +| loss | 3.63 | +| n_updates | 12240 | +| policy_gradient_loss | 0.0383 | +| value_loss | 11.6 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 344 | +| iterations | 1226 | +| time_elapsed | 12748 | +| total_timesteps | 4393984 | +| train/ | | +| approx_kl | 0.69326895 | +| clip_fraction | 0.191 | +| clip_range | 0.155 | +| entropy_loss | -6.64 | +| explained_variance | 0.387 | +| learning_rate | 6e-05 | +| loss | 6.32 | +| n_updates | 12250 | +| policy_gradient_loss | 0.0138 | +| value_loss | 16.8 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -136 | +| time/ | | +| fps | 344 | +| iterations | 1227 | +| time_elapsed | 12758 | +| total_timesteps | 4397568 | +| train/ | | +| approx_kl | 0.31186438 | +| clip_fraction | 0.281 | +| clip_range | 0.155 | +| entropy_loss | -3.65 | +| explained_variance | 0.813 | +| learning_rate | 6e-05 | +| loss | 10 | +| n_updates | 12260 | +| policy_gradient_loss | 0.0297 | +| value_loss | 25.6 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -136 | +| time/ | | +| fps | 344 | +| iterations | 1228 | +| time_elapsed | 12769 | +| total_timesteps | 4401152 | +| train/ | | +| approx_kl | 0.32185432 | +| clip_fraction | 0.173 | +| clip_range | 0.155 | +| entropy_loss | -6.32 | +| explained_variance | 0.278 | +| learning_rate | 6e-05 | +| loss | 3.22 | +| n_updates | 12270 | +| policy_gradient_loss | 0.0834 | +| value_loss | 4.72 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -133 | +| time/ | | +| fps | 344 | +| iterations | 1229 | +| time_elapsed | 12779 | +| total_timesteps | 4404736 | +| train/ | | +| approx_kl | 0.24009399 | +| clip_fraction | 0.218 | +| clip_range | 0.155 | +| entropy_loss | -6.81 | +| explained_variance | 0.233 | +| learning_rate | 6e-05 | +| loss | 0.0105 | +| n_updates | 12280 | +| policy_gradient_loss | 0.0557 | +| value_loss | 5.01 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -135 | +| time/ | | +| fps | 344 | +| iterations | 1230 | +| time_elapsed | 12790 | +| total_timesteps | 4408320 | +| train/ | | +| approx_kl | 0.3038121 | +| clip_fraction | 0.167 | +| clip_range | 0.155 | +| entropy_loss | -5.01 | +| explained_variance | 0.192 | +| learning_rate | 6e-05 | +| loss | 6.94 | +| n_updates | 12290 | +| policy_gradient_loss | 0.0374 | +| value_loss | 6.21 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 344 | +| iterations | 1231 | +| time_elapsed | 12800 | +| total_timesteps | 4411904 | +| train/ | | +| approx_kl | 0.6947231 | +| clip_fraction | 0.164 | +| clip_range | 0.155 | +| entropy_loss | -3.67 | +| explained_variance | 0.197 | +| learning_rate | 6e-05 | +| loss | 0.483 | +| n_updates | 12300 | +| policy_gradient_loss | 0.0243 | +| value_loss | 27.1 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 344 | +| iterations | 1232 | +| time_elapsed | 12810 | +| total_timesteps | 4415488 | +| train/ | | +| approx_kl | 0.075395174 | +| clip_fraction | 0.164 | +| clip_range | 0.155 | +| entropy_loss | -1.77 | +| explained_variance | 0.543 | +| learning_rate | 6e-05 | +| loss | 4.65 | +| n_updates | 12310 | +| policy_gradient_loss | 0.0158 | +| value_loss | 26.4 | +----------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -121 | +| time/ | | +| fps | 344 | +| iterations | 1233 | +| time_elapsed | 12820 | +| total_timesteps | 4419072 | +| train/ | | +| approx_kl | 0.42016888 | +| clip_fraction | 0.276 | +| clip_range | 0.155 | +| entropy_loss | -3.78 | +| explained_variance | 0.21 | +| learning_rate | 6e-05 | +| loss | 0.447 | +| n_updates | 12320 | +| policy_gradient_loss | 0.0494 | +| value_loss | 5.54 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 344 | +| iterations | 1234 | +| time_elapsed | 12830 | +| total_timesteps | 4422656 | +| train/ | | +| approx_kl | 0.46973187 | +| clip_fraction | 0.325 | +| clip_range | 0.155 | +| entropy_loss | -4.67 | +| explained_variance | 0.703 | +| learning_rate | 6e-05 | +| loss | 0.75 | +| n_updates | 12330 | +| policy_gradient_loss | 0.0489 | +| value_loss | 10.5 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -121 | +| time/ | | +| fps | 344 | +| iterations | 1235 | +| time_elapsed | 12840 | +| total_timesteps | 4426240 | +| train/ | | +| approx_kl | 0.78903717 | +| clip_fraction | 0.245 | +| clip_range | 0.155 | +| entropy_loss | -3.18 | +| explained_variance | 0.668 | +| learning_rate | 6e-05 | +| loss | 19.7 | +| n_updates | 12340 | +| policy_gradient_loss | 0.0223 | +| value_loss | 32.1 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -120 | +| time/ | | +| fps | 344 | +| iterations | 1236 | +| time_elapsed | 12849 | +| total_timesteps | 4429824 | +| train/ | | +| approx_kl | 1.0301054 | +| clip_fraction | 0.281 | +| clip_range | 0.155 | +| entropy_loss | -4.01 | +| explained_variance | 0.624 | +| learning_rate | 6e-05 | +| loss | 0.786 | +| n_updates | 12350 | +| policy_gradient_loss | 0.051 | +| value_loss | 9.51 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -121 | +| time/ | | +| fps | 344 | +| iterations | 1237 | +| time_elapsed | 12859 | +| total_timesteps | 4433408 | +| train/ | | +| approx_kl | 0.2772389 | +| clip_fraction | 0.118 | +| clip_range | 0.155 | +| entropy_loss | -7.95 | +| explained_variance | 0.0255 | +| learning_rate | 6e-05 | +| loss | 0.0498 | +| n_updates | 12360 | +| policy_gradient_loss | 0.0534 | +| value_loss | 8.85 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 344 | +| iterations | 1238 | +| time_elapsed | 12869 | +| total_timesteps | 4436992 | +| train/ | | +| approx_kl | 0.39072683 | +| clip_fraction | 0.28 | +| clip_range | 0.155 | +| entropy_loss | -4.98 | +| explained_variance | 0.14 | +| learning_rate | 6e-05 | +| loss | 18.4 | +| n_updates | 12370 | +| policy_gradient_loss | 0.0494 | +| value_loss | 18.3 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.03e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 344 | +| iterations | 1239 | +| time_elapsed | 12879 | +| total_timesteps | 4440576 | +| train/ | | +| approx_kl | 0.31544542 | +| clip_fraction | 0.156 | +| clip_range | 0.155 | +| entropy_loss | -6.93 | +| explained_variance | 0.327 | +| learning_rate | 6e-05 | +| loss | 0.0191 | +| n_updates | 12380 | +| policy_gradient_loss | 0.0255 | +| value_loss | 4.89 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 344 | +| iterations | 1240 | +| time_elapsed | 12890 | +| total_timesteps | 4444160 | +| train/ | | +| approx_kl | 0.36390835 | +| clip_fraction | 0.209 | +| clip_range | 0.155 | +| entropy_loss | -7.64 | +| explained_variance | -0.0181 | +| learning_rate | 6e-05 | +| loss | 0.883 | +| n_updates | 12390 | +| policy_gradient_loss | 0.044 | +| value_loss | 6.61 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -113 | +| time/ | | +| fps | 344 | +| iterations | 1241 | +| time_elapsed | 12902 | +| total_timesteps | 4447744 | +| train/ | | +| approx_kl | 0.7988187 | +| clip_fraction | 0.297 | +| clip_range | 0.155 | +| entropy_loss | -5.14 | +| explained_variance | 0.323 | +| learning_rate | 6e-05 | +| loss | 5.93 | +| n_updates | 12400 | +| policy_gradient_loss | 0.0472 | +| value_loss | 10.7 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -112 | +| time/ | | +| fps | 344 | +| iterations | 1242 | +| time_elapsed | 12912 | +| total_timesteps | 4451328 | +| train/ | | +| approx_kl | 0.31049347 | +| clip_fraction | 0.297 | +| clip_range | 0.155 | +| entropy_loss | -2.9 | +| explained_variance | 0.302 | +| learning_rate | 6e-05 | +| loss | 2.68 | +| n_updates | 12410 | +| policy_gradient_loss | 0.0424 | +| value_loss | 8.02 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -109 | +| time/ | | +| fps | 344 | +| iterations | 1243 | +| time_elapsed | 12922 | +| total_timesteps | 4454912 | +| train/ | | +| approx_kl | 0.5159423 | +| clip_fraction | 0.288 | +| clip_range | 0.155 | +| entropy_loss | -6.56 | +| explained_variance | 0.139 | +| learning_rate | 6e-05 | +| loss | 0.602 | +| n_updates | 12420 | +| policy_gradient_loss | 0.0673 | +| value_loss | 7.36 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -105 | +| time/ | | +| fps | 344 | +| iterations | 1244 | +| time_elapsed | 12933 | +| total_timesteps | 4458496 | +| train/ | | +| approx_kl | 1.1260291 | +| clip_fraction | 0.193 | +| clip_range | 0.155 | +| entropy_loss | -7.3 | +| explained_variance | -0.0433 | +| learning_rate | 6e-05 | +| loss | 8.05 | +| n_updates | 12430 | +| policy_gradient_loss | 0.0445 | +| value_loss | 9.3 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -105 | +| time/ | | +| fps | 344 | +| iterations | 1245 | +| time_elapsed | 12943 | +| total_timesteps | 4462080 | +| train/ | | +| approx_kl | 0.8614569 | +| clip_fraction | 0.319 | +| clip_range | 0.155 | +| entropy_loss | -5.23 | +| explained_variance | 0.233 | +| learning_rate | 6e-05 | +| loss | 24.2 | +| n_updates | 12440 | +| policy_gradient_loss | 0.062 | +| value_loss | 16.9 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 344 | +| iterations | 1246 | +| time_elapsed | 12954 | +| total_timesteps | 4465664 | +| train/ | | +| approx_kl | 0.13984755 | +| clip_fraction | 0.157 | +| clip_range | 0.155 | +| entropy_loss | -1.58 | +| explained_variance | 0.256 | +| learning_rate | 6e-05 | +| loss | 0.391 | +| n_updates | 12450 | +| policy_gradient_loss | 0.02 | +| value_loss | 5.85 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.02e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 344 | +| iterations | 1247 | +| time_elapsed | 12965 | +| total_timesteps | 4469248 | +| train/ | | +| approx_kl | 2.1635077 | +| clip_fraction | 0.362 | +| clip_range | 0.155 | +| entropy_loss | -5.13 | +| explained_variance | 0.212 | +| learning_rate | 6e-05 | +| loss | 0.524 | +| n_updates | 12460 | +| policy_gradient_loss | 0.0576 | +| value_loss | 13.7 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 344 | +| iterations | 1248 | +| time_elapsed | 12975 | +| total_timesteps | 4472832 | +| train/ | | +| approx_kl | 0.095714055 | +| clip_fraction | 0.145 | +| clip_range | 0.155 | +| entropy_loss | -7.92 | +| explained_variance | -0.0454 | +| learning_rate | 6e-05 | +| loss | 2.55 | +| n_updates | 12470 | +| policy_gradient_loss | 0.0325 | +| value_loss | 7.61 | +----------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -102 | +| time/ | | +| fps | 344 | +| iterations | 1249 | +| time_elapsed | 12985 | +| total_timesteps | 4476416 | +| train/ | | +| approx_kl | 0.77635044 | +| clip_fraction | 0.121 | +| clip_range | 0.155 | +| entropy_loss | -7.9 | +| explained_variance | 0.0272 | +| learning_rate | 6e-05 | +| loss | 3.9 | +| n_updates | 12480 | +| policy_gradient_loss | 0.0596 | +| value_loss | 7.14 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 344 | +| iterations | 1250 | +| time_elapsed | 12995 | +| total_timesteps | 4480000 | +| train/ | | +| approx_kl | 0.45620853 | +| clip_fraction | 0.0705 | +| clip_range | 0.155 | +| entropy_loss | -7.7 | +| explained_variance | 0.0135 | +| learning_rate | 6e-05 | +| loss | 1.34 | +| n_updates | 12490 | +| policy_gradient_loss | 0.0158 | +| value_loss | 6.88 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -102 | +| time/ | | +| fps | 344 | +| iterations | 1251 | +| time_elapsed | 13006 | +| total_timesteps | 4483584 | +| train/ | | +| approx_kl | 0.16104047 | +| clip_fraction | 0.0568 | +| clip_range | 0.155 | +| entropy_loss | -8.06 | +| explained_variance | 0.143 | +| learning_rate | 6e-05 | +| loss | 3.26 | +| n_updates | 12500 | +| policy_gradient_loss | 0.0254 | +| value_loss | 11.2 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.06e+03 | +| ep_rew_mean | -103 | +| time/ | | +| fps | 344 | +| iterations | 1252 | +| time_elapsed | 13016 | +| total_timesteps | 4487168 | +| train/ | | +| approx_kl | 0.13989703 | +| clip_fraction | 0.0666 | +| clip_range | 0.155 | +| entropy_loss | -7.06 | +| explained_variance | 0.293 | +| learning_rate | 6e-05 | +| loss | 13.6 | +| n_updates | 12510 | +| policy_gradient_loss | 0.0204 | +| value_loss | 21.8 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.09e+03 | +| ep_rew_mean | -98 | +| time/ | | +| fps | 344 | +| iterations | 1253 | +| time_elapsed | 13027 | +| total_timesteps | 4490752 | +| train/ | | +| approx_kl | 0.16489413 | +| clip_fraction | 0.0734 | +| clip_range | 0.155 | +| entropy_loss | -7.05 | +| explained_variance | 0.684 | +| learning_rate | 6e-05 | +| loss | 1.14 | +| n_updates | 12520 | +| policy_gradient_loss | 0.033 | +| value_loss | 8.26 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.11e+03 | +| ep_rew_mean | -95.2 | +| time/ | | +| fps | 344 | +| iterations | 1254 | +| time_elapsed | 13037 | +| total_timesteps | 4494336 | +| train/ | | +| approx_kl | 0.42327186 | +| clip_fraction | 0.0754 | +| clip_range | 0.155 | +| entropy_loss | -7.95 | +| explained_variance | -0.0265 | +| learning_rate | 6e-05 | +| loss | 4.3 | +| n_updates | 12530 | +| policy_gradient_loss | 0.0624 | +| value_loss | 8.44 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -93.4 | +| time/ | | +| fps | 344 | +| iterations | 1255 | +| time_elapsed | 13047 | +| total_timesteps | 4497920 | +| train/ | | +| approx_kl | 0.7492663 | +| clip_fraction | 0.168 | +| clip_range | 0.155 | +| entropy_loss | -5.65 | +| explained_variance | 0.329 | +| learning_rate | 6e-05 | +| loss | 12.1 | +| n_updates | 12540 | +| policy_gradient_loss | 0.0276 | +| value_loss | 5.83 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -94.1 | +| time/ | | +| fps | 344 | +| iterations | 1256 | +| time_elapsed | 13057 | +| total_timesteps | 4501504 | +| train/ | | +| approx_kl | 1.2825361 | +| clip_fraction | 0.346 | +| clip_range | 0.155 | +| entropy_loss | -3.3 | +| explained_variance | 0.653 | +| learning_rate | 6e-05 | +| loss | 1.33 | +| n_updates | 12550 | +| policy_gradient_loss | 0.038 | +| value_loss | 14.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.09e+03 | +| ep_rew_mean | -92.3 | +| time/ | | +| fps | 344 | +| iterations | 1257 | +| time_elapsed | 13067 | +| total_timesteps | 4505088 | +| train/ | | +| approx_kl | 0.72400326 | +| clip_fraction | 0.208 | +| clip_range | 0.155 | +| entropy_loss | -5.19 | +| explained_variance | 0.391 | +| learning_rate | 6e-05 | +| loss | 1.56 | +| n_updates | 12560 | +| policy_gradient_loss | 0.0271 | +| value_loss | 10.1 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.1e+03 | +| ep_rew_mean | -92.3 | +| time/ | | +| fps | 344 | +| iterations | 1258 | +| time_elapsed | 13077 | +| total_timesteps | 4508672 | +| train/ | | +| approx_kl | 0.92736435 | +| clip_fraction | 0.125 | +| clip_range | 0.155 | +| entropy_loss | -7.62 | +| explained_variance | 0.000484 | +| learning_rate | 6e-05 | +| loss | 55.2 | +| n_updates | 12570 | +| policy_gradient_loss | 0.0289 | +| value_loss | 18.9 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.11e+03 | +| ep_rew_mean | -97.3 | +| time/ | | +| fps | 344 | +| iterations | 1259 | +| time_elapsed | 13087 | +| total_timesteps | 4512256 | +| train/ | | +| approx_kl | 3.5470617 | +| clip_fraction | 0.213 | +| clip_range | 0.155 | +| entropy_loss | -5.61 | +| explained_variance | 0.299 | +| learning_rate | 6e-05 | +| loss | 0.45 | +| n_updates | 12580 | +| policy_gradient_loss | 0.024 | +| value_loss | 31.4 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -96 | +| time/ | | +| fps | 344 | +| iterations | 1260 | +| time_elapsed | 13097 | +| total_timesteps | 4515840 | +| train/ | | +| approx_kl | 0.23432596 | +| clip_fraction | 0.238 | +| clip_range | 0.155 | +| entropy_loss | -5.37 | +| explained_variance | 0.554 | +| learning_rate | 6e-05 | +| loss | 0.353 | +| n_updates | 12590 | +| policy_gradient_loss | 0.0276 | +| value_loss | 13.6 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -97.1 | +| time/ | | +| fps | 344 | +| iterations | 1261 | +| time_elapsed | 13107 | +| total_timesteps | 4519424 | +| train/ | | +| approx_kl | 0.3578764 | +| clip_fraction | 0.178 | +| clip_range | 0.155 | +| entropy_loss | -4.85 | +| explained_variance | 0.322 | +| learning_rate | 6e-05 | +| loss | 0.285 | +| n_updates | 12600 | +| policy_gradient_loss | 0.0533 | +| value_loss | 10.3 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -94.7 | +| time/ | | +| fps | 344 | +| iterations | 1262 | +| time_elapsed | 13117 | +| total_timesteps | 4523008 | +| train/ | | +| approx_kl | 1.75117 | +| clip_fraction | 0.268 | +| clip_range | 0.155 | +| entropy_loss | -4.33 | +| explained_variance | 0.142 | +| learning_rate | 6e-05 | +| loss | 3.43 | +| n_updates | 12610 | +| policy_gradient_loss | 0.0415 | +| value_loss | 19.4 | +-------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -93.4 | +| time/ | | +| fps | 344 | +| iterations | 1263 | +| time_elapsed | 13128 | +| total_timesteps | 4526592 | +| train/ | | +| approx_kl | 0.043092635 | +| clip_fraction | 0.0353 | +| clip_range | 0.155 | +| entropy_loss | -7.45 | +| explained_variance | 0.46 | +| learning_rate | 6e-05 | +| loss | 0.383 | +| n_updates | 12620 | +| policy_gradient_loss | 0.00995 | +| value_loss | 10.2 | +----------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.15e+03 | +| ep_rew_mean | -96.5 | +| time/ | | +| fps | 344 | +| iterations | 1264 | +| time_elapsed | 13138 | +| total_timesteps | 4530176 | +| train/ | | +| approx_kl | 0.66940606 | +| clip_fraction | 0.102 | +| clip_range | 0.155 | +| entropy_loss | -7.71 | +| explained_variance | 0.0204 | +| learning_rate | 6e-05 | +| loss | 7.59 | +| n_updates | 12630 | +| policy_gradient_loss | 0.0241 | +| value_loss | 8.01 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -97.5 | +| time/ | | +| fps | 344 | +| iterations | 1265 | +| time_elapsed | 13149 | +| total_timesteps | 4533760 | +| train/ | | +| approx_kl | 0.9533757 | +| clip_fraction | 0.225 | +| clip_range | 0.155 | +| entropy_loss | -6.25 | +| explained_variance | 0.145 | +| learning_rate | 6e-05 | +| loss | 16.4 | +| n_updates | 12640 | +| policy_gradient_loss | 0.0319 | +| value_loss | 11.5 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -96.3 | +| time/ | | +| fps | 344 | +| iterations | 1266 | +| time_elapsed | 13158 | +| total_timesteps | 4537344 | +| train/ | | +| approx_kl | 1.2446054 | +| clip_fraction | 0.132 | +| clip_range | 0.155 | +| entropy_loss | -7.43 | +| explained_variance | 0.154 | +| learning_rate | 6e-05 | +| loss | 3.89 | +| n_updates | 12650 | +| policy_gradient_loss | 0.0214 | +| value_loss | 6.79 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -96.3 | +| time/ | | +| fps | 344 | +| iterations | 1267 | +| time_elapsed | 13168 | +| total_timesteps | 4540928 | +| train/ | | +| approx_kl | 0.4820626 | +| clip_fraction | 0.147 | +| clip_range | 0.155 | +| entropy_loss | -6.72 | +| explained_variance | 0.107 | +| learning_rate | 6e-05 | +| loss | 3.81 | +| n_updates | 12660 | +| policy_gradient_loss | 0.0274 | +| value_loss | 7.47 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -96.2 | +| time/ | | +| fps | 344 | +| iterations | 1268 | +| time_elapsed | 13178 | +| total_timesteps | 4544512 | +| train/ | | +| approx_kl | 0.3293403 | +| clip_fraction | 0.107 | +| clip_range | 0.155 | +| entropy_loss | -7.88 | +| explained_variance | 0.055 | +| learning_rate | 6e-05 | +| loss | 8.63 | +| n_updates | 12670 | +| policy_gradient_loss | 0.025 | +| value_loss | 5.33 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -96.3 | +| time/ | | +| fps | 344 | +| iterations | 1269 | +| time_elapsed | 13188 | +| total_timesteps | 4548096 | +| train/ | | +| approx_kl | 0.6004734 | +| clip_fraction | 0.0823 | +| clip_range | 0.155 | +| entropy_loss | -7.72 | +| explained_variance | 0.0872 | +| learning_rate | 6e-05 | +| loss | 0.408 | +| n_updates | 12680 | +| policy_gradient_loss | 0.0188 | +| value_loss | 4.46 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -100 | +| time/ | | +| fps | 344 | +| iterations | 1270 | +| time_elapsed | 13198 | +| total_timesteps | 4551680 | +| train/ | | +| approx_kl | 0.31535926 | +| clip_fraction | 0.12 | +| clip_range | 0.155 | +| entropy_loss | -6.07 | +| explained_variance | 0.179 | +| learning_rate | 6e-05 | +| loss | 5.99 | +| n_updates | 12690 | +| policy_gradient_loss | 0.0174 | +| value_loss | 12.3 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.2e+03 | +| ep_rew_mean | -95.5 | +| time/ | | +| fps | 344 | +| iterations | 1271 | +| time_elapsed | 13208 | +| total_timesteps | 4555264 | +| train/ | | +| approx_kl | 1.1247593 | +| clip_fraction | 0.223 | +| clip_range | 0.155 | +| entropy_loss | -5.04 | +| explained_variance | 0.173 | +| learning_rate | 6e-05 | +| loss | 29.7 | +| n_updates | 12700 | +| policy_gradient_loss | 0.0218 | +| value_loss | 16.3 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.2e+03 | +| ep_rew_mean | -97 | +| time/ | | +| fps | 344 | +| iterations | 1272 | +| time_elapsed | 13218 | +| total_timesteps | 4558848 | +| train/ | | +| approx_kl | 1.4492542 | +| clip_fraction | 0.273 | +| clip_range | 0.155 | +| entropy_loss | -5.36 | +| explained_variance | 0.388 | +| learning_rate | 6e-05 | +| loss | 3.17 | +| n_updates | 12710 | +| policy_gradient_loss | 0.0308 | +| value_loss | 12.5 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -96.6 | +| time/ | | +| fps | 344 | +| iterations | 1273 | +| time_elapsed | 13228 | +| total_timesteps | 4562432 | +| train/ | | +| approx_kl | 1.083204 | +| clip_fraction | 0.162 | +| clip_range | 0.155 | +| entropy_loss | -5.94 | +| explained_variance | 0.107 | +| learning_rate | 6e-05 | +| loss | 2.88 | +| n_updates | 12720 | +| policy_gradient_loss | 0.0128 | +| value_loss | 19.3 | +-------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -93.4 | +| time/ | | +| fps | 344 | +| iterations | 1274 | +| time_elapsed | 13238 | +| total_timesteps | 4566016 | +| train/ | | +| approx_kl | 1.088323 | +| clip_fraction | 0.189 | +| clip_range | 0.155 | +| entropy_loss | -5.76 | +| explained_variance | 0.145 | +| learning_rate | 6e-05 | +| loss | 1.66 | +| n_updates | 12730 | +| policy_gradient_loss | 0.0317 | +| value_loss | 11.5 | +-------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -87.5 | +| time/ | | +| fps | 344 | +| iterations | 1275 | +| time_elapsed | 13249 | +| total_timesteps | 4569600 | +| train/ | | +| approx_kl | 1.5441859 | +| clip_fraction | 0.18 | +| clip_range | 0.155 | +| entropy_loss | -5.64 | +| explained_variance | 0.0835 | +| learning_rate | 6e-05 | +| loss | 1.74 | +| n_updates | 12740 | +| policy_gradient_loss | 0.0248 | +| value_loss | 14.3 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -87.7 | +| time/ | | +| fps | 344 | +| iterations | 1276 | +| time_elapsed | 13260 | +| total_timesteps | 4573184 | +| train/ | | +| approx_kl | 0.7491503 | +| clip_fraction | 0.164 | +| clip_range | 0.155 | +| entropy_loss | -6.57 | +| explained_variance | 0.425 | +| learning_rate | 6e-05 | +| loss | 0.495 | +| n_updates | 12750 | +| policy_gradient_loss | 0.0281 | +| value_loss | 8.94 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -88.6 | +| time/ | | +| fps | 344 | +| iterations | 1277 | +| time_elapsed | 13270 | +| total_timesteps | 4576768 | +| train/ | | +| approx_kl | 0.68623257 | +| clip_fraction | 0.0834 | +| clip_range | 0.155 | +| entropy_loss | -5.19 | +| explained_variance | 0.122 | +| learning_rate | 6e-05 | +| loss | 14.4 | +| n_updates | 12760 | +| policy_gradient_loss | 0.0141 | +| value_loss | 28.2 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -87.7 | +| time/ | | +| fps | 344 | +| iterations | 1278 | +| time_elapsed | 13281 | +| total_timesteps | 4580352 | +| train/ | | +| approx_kl | 0.9943814 | +| clip_fraction | 0.16 | +| clip_range | 0.155 | +| entropy_loss | -6.89 | +| explained_variance | 0.549 | +| learning_rate | 6e-05 | +| loss | 1.73 | +| n_updates | 12770 | +| policy_gradient_loss | 0.0205 | +| value_loss | 16.6 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -87.7 | +| time/ | | +| fps | 344 | +| iterations | 1279 | +| time_elapsed | 13291 | +| total_timesteps | 4583936 | +| train/ | | +| approx_kl | 0.535005 | +| clip_fraction | 0.138 | +| clip_range | 0.155 | +| entropy_loss | -6.85 | +| explained_variance | 0.0629 | +| learning_rate | 6e-05 | +| loss | 0.0739 | +| n_updates | 12780 | +| policy_gradient_loss | 0.0239 | +| value_loss | 10.6 | +-------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -90.8 | +| time/ | | +| fps | 344 | +| iterations | 1280 | +| time_elapsed | 13302 | +| total_timesteps | 4587520 | +| train/ | | +| approx_kl | 0.6247336 | +| clip_fraction | 0.113 | +| clip_range | 0.155 | +| entropy_loss | -6.98 | +| explained_variance | 0.0851 | +| learning_rate | 6e-05 | +| loss | 9.49 | +| n_updates | 12790 | +| policy_gradient_loss | 0.0345 | +| value_loss | 5.17 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -91.6 | +| time/ | | +| fps | 344 | +| iterations | 1281 | +| time_elapsed | 13313 | +| total_timesteps | 4591104 | +| train/ | | +| approx_kl | 2.1533842 | +| clip_fraction | 0.156 | +| clip_range | 0.155 | +| entropy_loss | -6.2 | +| explained_variance | 0.0833 | +| learning_rate | 6e-05 | +| loss | 0.119 | +| n_updates | 12800 | +| policy_gradient_loss | 0.0241 | +| value_loss | 14.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -90 | +| time/ | | +| fps | 344 | +| iterations | 1282 | +| time_elapsed | 13324 | +| total_timesteps | 4594688 | +| train/ | | +| approx_kl | 0.7510583 | +| clip_fraction | 0.176 | +| clip_range | 0.155 | +| entropy_loss | -6.44 | +| explained_variance | 0.138 | +| learning_rate | 6e-05 | +| loss | 20.2 | +| n_updates | 12810 | +| policy_gradient_loss | 0.0402 | +| value_loss | 16.7 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -101 | +| time/ | | +| fps | 344 | +| iterations | 1283 | +| time_elapsed | 13334 | +| total_timesteps | 4598272 | +| train/ | | +| approx_kl | 0.87430996 | +| clip_fraction | 0.156 | +| clip_range | 0.155 | +| entropy_loss | -6.02 | +| explained_variance | 0.147 | +| learning_rate | 6e-05 | +| loss | 0.262 | +| n_updates | 12820 | +| policy_gradient_loss | 0.033 | +| value_loss | 8.21 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 344 | +| iterations | 1284 | +| time_elapsed | 13344 | +| total_timesteps | 4601856 | +| train/ | | +| approx_kl | 3.0897548 | +| clip_fraction | 0.13 | +| clip_range | 0.155 | +| entropy_loss | -4.91 | +| explained_variance | 0.24 | +| learning_rate | 6e-05 | +| loss | 11.3 | +| n_updates | 12830 | +| policy_gradient_loss | 0.0149 | +| value_loss | 27.7 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 344 | +| iterations | 1285 | +| time_elapsed | 13354 | +| total_timesteps | 4605440 | +| train/ | | +| approx_kl | 0.30760098 | +| clip_fraction | 0.0668 | +| clip_range | 0.155 | +| entropy_loss | -6.86 | +| explained_variance | 0.579 | +| learning_rate | 6e-05 | +| loss | 0.0858 | +| n_updates | 12840 | +| policy_gradient_loss | 0.013 | +| value_loss | 17.3 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 344 | +| iterations | 1286 | +| time_elapsed | 13364 | +| total_timesteps | 4609024 | +| train/ | | +| approx_kl | 1.764952 | +| clip_fraction | 0.191 | +| clip_range | 0.155 | +| entropy_loss | -3.67 | +| explained_variance | 0.57 | +| learning_rate | 6e-05 | +| loss | 8.28 | +| n_updates | 12850 | +| policy_gradient_loss | 0.0099 | +| value_loss | 11.2 | +-------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -107 | +| time/ | | +| fps | 344 | +| iterations | 1287 | +| time_elapsed | 13375 | +| total_timesteps | 4612608 | +| train/ | | +| approx_kl | 4.1738057 | +| clip_fraction | 0.175 | +| clip_range | 0.155 | +| entropy_loss | -5.91 | +| explained_variance | 0.0467 | +| learning_rate | 6e-05 | +| loss | 2.78 | +| n_updates | 12860 | +| policy_gradient_loss | 0.0219 | +| value_loss | 28.9 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -91.6 | +| time/ | | +| fps | 344 | +| iterations | 1288 | +| time_elapsed | 13387 | +| total_timesteps | 4616192 | +| train/ | | +| approx_kl | 0.119748764 | +| clip_fraction | 0.0475 | +| clip_range | 0.155 | +| entropy_loss | -6.97 | +| explained_variance | 0.21 | +| learning_rate | 6e-05 | +| loss | 117 | +| n_updates | 12870 | +| policy_gradient_loss | 0.0131 | +| value_loss | 40.4 | +----------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -90.5 | +| time/ | | +| fps | 344 | +| iterations | 1289 | +| time_elapsed | 13397 | +| total_timesteps | 4619776 | +| train/ | | +| approx_kl | 1.3477346 | +| clip_fraction | 0.0856 | +| clip_range | 0.155 | +| entropy_loss | -5.69 | +| explained_variance | 0.00482 | +| learning_rate | 6e-05 | +| loss | 1.31e+03 | +| n_updates | 12880 | +| policy_gradient_loss | 0.0204 | +| value_loss | 1.58e+03 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -90.8 | +| time/ | | +| fps | 344 | +| iterations | 1290 | +| time_elapsed | 13407 | +| total_timesteps | 4623360 | +| train/ | | +| approx_kl | 1.9719576 | +| clip_fraction | 0.206 | +| clip_range | 0.155 | +| entropy_loss | -4.84 | +| explained_variance | 0.159 | +| learning_rate | 6e-05 | +| loss | 2.24 | +| n_updates | 12890 | +| policy_gradient_loss | 0.0296 | +| value_loss | 7.1 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -89.4 | +| time/ | | +| fps | 344 | +| iterations | 1291 | +| time_elapsed | 13417 | +| total_timesteps | 4626944 | +| train/ | | +| approx_kl | 0.8320762 | +| clip_fraction | 0.146 | +| clip_range | 0.155 | +| entropy_loss | -3.31 | +| explained_variance | 0.0835 | +| learning_rate | 6e-05 | +| loss | 0.963 | +| n_updates | 12900 | +| policy_gradient_loss | 0.0904 | +| value_loss | 14.8 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -88.2 | +| time/ | | +| fps | 344 | +| iterations | 1292 | +| time_elapsed | 13428 | +| total_timesteps | 4630528 | +| train/ | | +| approx_kl | 0.64797676 | +| clip_fraction | 0.0893 | +| clip_range | 0.155 | +| entropy_loss | -5.28 | +| explained_variance | 0.332 | +| learning_rate | 6e-05 | +| loss | 1.17 | +| n_updates | 12910 | +| policy_gradient_loss | 0.027 | +| value_loss | 8.14 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -89.6 | +| time/ | | +| fps | 344 | +| iterations | 1293 | +| time_elapsed | 13438 | +| total_timesteps | 4634112 | +| train/ | | +| approx_kl | 1.8512771 | +| clip_fraction | 0.251 | +| clip_range | 0.155 | +| entropy_loss | -4.91 | +| explained_variance | 0.102 | +| learning_rate | 6e-05 | +| loss | 3.28 | +| n_updates | 12920 | +| policy_gradient_loss | 0.0532 | +| value_loss | 19.7 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -88.3 | +| time/ | | +| fps | 344 | +| iterations | 1294 | +| time_elapsed | 13448 | +| total_timesteps | 4637696 | +| train/ | | +| approx_kl | 0.8240376 | +| clip_fraction | 0.179 | +| clip_range | 0.155 | +| entropy_loss | -6.17 | +| explained_variance | 0.072 | +| learning_rate | 6e-05 | +| loss | 4.5 | +| n_updates | 12930 | +| policy_gradient_loss | 0.111 | +| value_loss | 11.7 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -89.9 | +| time/ | | +| fps | 344 | +| iterations | 1295 | +| time_elapsed | 13458 | +| total_timesteps | 4641280 | +| train/ | | +| approx_kl | 2.5454962 | +| clip_fraction | 0.126 | +| clip_range | 0.155 | +| entropy_loss | -7.13 | +| explained_variance | 0.15 | +| learning_rate | 6e-05 | +| loss | 0.557 | +| n_updates | 12940 | +| policy_gradient_loss | 0.0332 | +| value_loss | 8.58 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -92.3 | +| time/ | | +| fps | 344 | +| iterations | 1296 | +| time_elapsed | 13467 | +| total_timesteps | 4644864 | +| train/ | | +| approx_kl | 0.6861028 | +| clip_fraction | 0.124 | +| clip_range | 0.155 | +| entropy_loss | -6.85 | +| explained_variance | 0.0972 | +| learning_rate | 6e-05 | +| loss | 0.513 | +| n_updates | 12950 | +| policy_gradient_loss | 0.0548 | +| value_loss | 16.6 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -92 | +| time/ | | +| fps | 344 | +| iterations | 1297 | +| time_elapsed | 13477 | +| total_timesteps | 4648448 | +| train/ | | +| approx_kl | 0.73205936 | +| clip_fraction | 0.0663 | +| clip_range | 0.155 | +| entropy_loss | -4.6 | +| explained_variance | 0.221 | +| learning_rate | 6e-05 | +| loss | 2.5 | +| n_updates | 12960 | +| policy_gradient_loss | 0.0178 | +| value_loss | 9.84 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -86.3 | +| time/ | | +| fps | 344 | +| iterations | 1298 | +| time_elapsed | 13488 | +| total_timesteps | 4652032 | +| train/ | | +| approx_kl | 2.7199504 | +| clip_fraction | 0.12 | +| clip_range | 0.155 | +| entropy_loss | -7.33 | +| explained_variance | -0.00711 | +| learning_rate | 6e-05 | +| loss | 1.18 | +| n_updates | 12970 | +| policy_gradient_loss | 0.0785 | +| value_loss | 33.6 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -84.2 | +| time/ | | +| fps | 344 | +| iterations | 1299 | +| time_elapsed | 13498 | +| total_timesteps | 4655616 | +| train/ | | +| approx_kl | 0.14059801 | +| clip_fraction | 0.037 | +| clip_range | 0.155 | +| entropy_loss | -8.11 | +| explained_variance | 0.0677 | +| learning_rate | 6e-05 | +| loss | 5.6 | +| n_updates | 12980 | +| policy_gradient_loss | 0.00845 | +| value_loss | 9.26 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -86.7 | +| time/ | | +| fps | 344 | +| iterations | 1300 | +| time_elapsed | 13509 | +| total_timesteps | 4659200 | +| train/ | | +| approx_kl | 0.32773167 | +| clip_fraction | 0.0504 | +| clip_range | 0.155 | +| entropy_loss | -6.7 | +| explained_variance | 0.125 | +| learning_rate | 6e-05 | +| loss | 0.00101 | +| n_updates | 12990 | +| policy_gradient_loss | 0.0222 | +| value_loss | 6.25 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -87.6 | +| time/ | | +| fps | 344 | +| iterations | 1301 | +| time_elapsed | 13519 | +| total_timesteps | 4662784 | +| train/ | | +| approx_kl | 3.666361 | +| clip_fraction | 0.0654 | +| clip_range | 0.155 | +| entropy_loss | -7.54 | +| explained_variance | 0.0252 | +| learning_rate | 6e-05 | +| loss | 7.07 | +| n_updates | 13000 | +| policy_gradient_loss | 0.0124 | +| value_loss | 35.1 | +-------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -90.7 | +| time/ | | +| fps | 344 | +| iterations | 1302 | +| time_elapsed | 13529 | +| total_timesteps | 4666368 | +| train/ | | +| approx_kl | 3.6687698 | +| clip_fraction | 0.126 | +| clip_range | 0.155 | +| entropy_loss | -2.75 | +| explained_variance | 0.162 | +| learning_rate | 6e-05 | +| loss | 17.2 | +| n_updates | 13010 | +| policy_gradient_loss | 0.0112 | +| value_loss | 10.1 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -93.5 | +| time/ | | +| fps | 344 | +| iterations | 1303 | +| time_elapsed | 13539 | +| total_timesteps | 4669952 | +| train/ | | +| approx_kl | 0.39417234 | +| clip_fraction | 0.09 | +| clip_range | 0.155 | +| entropy_loss | -1.84 | +| explained_variance | 0.292 | +| learning_rate | 6e-05 | +| loss | 1.71 | +| n_updates | 13020 | +| policy_gradient_loss | 0.0595 | +| value_loss | 10.7 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -91.8 | +| time/ | | +| fps | 344 | +| iterations | 1304 | +| time_elapsed | 13549 | +| total_timesteps | 4673536 | +| train/ | | +| approx_kl | 0.8685249 | +| clip_fraction | 0.139 | +| clip_range | 0.155 | +| entropy_loss | -5.91 | +| explained_variance | 0.112 | +| learning_rate | 6e-05 | +| loss | 0.324 | +| n_updates | 13030 | +| policy_gradient_loss | 0.02 | +| value_loss | 20.9 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -91.9 | +| time/ | | +| fps | 344 | +| iterations | 1305 | +| time_elapsed | 13559 | +| total_timesteps | 4677120 | +| train/ | | +| approx_kl | 4.317981 | +| clip_fraction | 0.329 | +| clip_range | 0.155 | +| entropy_loss | -4.04 | +| explained_variance | 0.0329 | +| learning_rate | 6e-05 | +| loss | 12.3 | +| n_updates | 13040 | +| policy_gradient_loss | 0.0788 | +| value_loss | 13.1 | +-------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -92.7 | +| time/ | | +| fps | 344 | +| iterations | 1306 | +| time_elapsed | 13569 | +| total_timesteps | 4680704 | +| train/ | | +| approx_kl | 0.49836013 | +| clip_fraction | 0.19 | +| clip_range | 0.155 | +| entropy_loss | -3.15 | +| explained_variance | 0.243 | +| learning_rate | 6e-05 | +| loss | 16 | +| n_updates | 13050 | +| policy_gradient_loss | 0.0398 | +| value_loss | 3.96 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.27e+03 | +| ep_rew_mean | -95.1 | +| time/ | | +| fps | 344 | +| iterations | 1307 | +| time_elapsed | 13579 | +| total_timesteps | 4684288 | +| train/ | | +| approx_kl | 4.274094 | +| clip_fraction | 0.227 | +| clip_range | 0.155 | +| entropy_loss | -4.51 | +| explained_variance | 0.232 | +| learning_rate | 6e-05 | +| loss | 0.558 | +| n_updates | 13060 | +| policy_gradient_loss | 0.046 | +| value_loss | 8.21 | +-------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -97.4 | +| time/ | | +| fps | 344 | +| iterations | 1308 | +| time_elapsed | 13589 | +| total_timesteps | 4687872 | +| train/ | | +| approx_kl | 1.9331377 | +| clip_fraction | 0.173 | +| clip_range | 0.155 | +| entropy_loss | -3.48 | +| explained_variance | 0.0911 | +| learning_rate | 6e-05 | +| loss | 8.84 | +| n_updates | 13070 | +| policy_gradient_loss | 0.0354 | +| value_loss | 25.2 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -102 | +| time/ | | +| fps | 344 | +| iterations | 1309 | +| time_elapsed | 13599 | +| total_timesteps | 4691456 | +| train/ | | +| approx_kl | 1.7331865 | +| clip_fraction | 0.201 | +| clip_range | 0.155 | +| entropy_loss | -5.28 | +| explained_variance | 0.111 | +| learning_rate | 6e-05 | +| loss | 3 | +| n_updates | 13080 | +| policy_gradient_loss | 0.0356 | +| value_loss | 15.3 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 344 | +| iterations | 1310 | +| time_elapsed | 13610 | +| total_timesteps | 4695040 | +| train/ | | +| approx_kl | 0.6087994 | +| clip_fraction | 0.0963 | +| clip_range | 0.155 | +| entropy_loss | -6.06 | +| explained_variance | 0.00561 | +| learning_rate | 6e-05 | +| loss | 0.123 | +| n_updates | 13090 | +| policy_gradient_loss | 0.0218 | +| value_loss | 18.9 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.26e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 344 | +| iterations | 1311 | +| time_elapsed | 13620 | +| total_timesteps | 4698624 | +| train/ | | +| approx_kl | 2.6511552 | +| clip_fraction | 0.115 | +| clip_range | 0.155 | +| entropy_loss | -6.7 | +| explained_variance | 0.0278 | +| learning_rate | 6e-05 | +| loss | 21.4 | +| n_updates | 13100 | +| policy_gradient_loss | 0.0271 | +| value_loss | 30.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -108 | +| time/ | | +| fps | 344 | +| iterations | 1312 | +| time_elapsed | 13631 | +| total_timesteps | 4702208 | +| train/ | | +| approx_kl | 0.6218218 | +| clip_fraction | 0.113 | +| clip_range | 0.155 | +| entropy_loss | -6.51 | +| explained_variance | 0.153 | +| learning_rate | 6e-05 | +| loss | 7.66 | +| n_updates | 13110 | +| policy_gradient_loss | 0.0204 | +| value_loss | 13 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 344 | +| iterations | 1313 | +| time_elapsed | 13641 | +| total_timesteps | 4705792 | +| train/ | | +| approx_kl | 8.339106 | +| clip_fraction | 0.154 | +| clip_range | 0.155 | +| entropy_loss | -6.7 | +| explained_variance | 0.0206 | +| learning_rate | 6e-05 | +| loss | 8.33 | +| n_updates | 13120 | +| policy_gradient_loss | 0.0232 | +| value_loss | 37.6 | +-------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -123 | +| time/ | | +| fps | 344 | +| iterations | 1314 | +| time_elapsed | 13651 | +| total_timesteps | 4709376 | +| train/ | | +| approx_kl | 1.9048193 | +| clip_fraction | 0.0708 | +| clip_range | 0.155 | +| entropy_loss | -2.7 | +| explained_variance | 0.216 | +| learning_rate | 6e-05 | +| loss | 12.9 | +| n_updates | 13130 | +| policy_gradient_loss | 0.0262 | +| value_loss | 61.4 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.12e+03 | +| ep_rew_mean | -127 | +| time/ | | +| fps | 344 | +| iterations | 1315 | +| time_elapsed | 13662 | +| total_timesteps | 4712960 | +| train/ | | +| approx_kl | 3.905846 | +| clip_fraction | 0.166 | +| clip_range | 0.155 | +| entropy_loss | -5.31 | +| explained_variance | 0.153 | +| learning_rate | 6e-05 | +| loss | 3.5 | +| n_updates | 13140 | +| policy_gradient_loss | 0.0203 | +| value_loss | 53 | +-------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.11e+03 | +| ep_rew_mean | -130 | +| time/ | | +| fps | 344 | +| iterations | 1316 | +| time_elapsed | 13673 | +| total_timesteps | 4716544 | +| train/ | | +| approx_kl | 0.9581284 | +| clip_fraction | 0.151 | +| clip_range | 0.155 | +| entropy_loss | -4.87 | +| explained_variance | 0.447 | +| learning_rate | 6e-05 | +| loss | 0.393 | +| n_updates | 13150 | +| policy_gradient_loss | 0.0121 | +| value_loss | 21.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.1e+03 | +| ep_rew_mean | -130 | +| time/ | | +| fps | 344 | +| iterations | 1317 | +| time_elapsed | 13684 | +| total_timesteps | 4720128 | +| train/ | | +| approx_kl | 6.0071096 | +| clip_fraction | 0.104 | +| clip_range | 0.155 | +| entropy_loss | -7.49 | +| explained_variance | 0.0291 | +| learning_rate | 6e-05 | +| loss | 0.0845 | +| n_updates | 13160 | +| policy_gradient_loss | 0.016 | +| value_loss | 34.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.07e+03 | +| ep_rew_mean | -133 | +| time/ | | +| fps | 344 | +| iterations | 1318 | +| time_elapsed | 13693 | +| total_timesteps | 4723712 | +| train/ | | +| approx_kl | 1.7094698 | +| clip_fraction | 0.116 | +| clip_range | 0.155 | +| entropy_loss | -2.97 | +| explained_variance | 0.317 | +| learning_rate | 6e-05 | +| loss | 3.89 | +| n_updates | 13170 | +| policy_gradient_loss | 0.017 | +| value_loss | 38 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.02e+03 | +| ep_rew_mean | -140 | +| time/ | | +| fps | 344 | +| iterations | 1319 | +| time_elapsed | 13703 | +| total_timesteps | 4727296 | +| train/ | | +| approx_kl | 1.5869018 | +| clip_fraction | 0.0983 | +| clip_range | 0.155 | +| entropy_loss | -2.93 | +| explained_variance | 0.272 | +| learning_rate | 6e-05 | +| loss | 2.21 | +| n_updates | 13180 | +| policy_gradient_loss | 0.00846 | +| value_loss | 50.7 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 344 | +| iterations | 1320 | +| time_elapsed | 13713 | +| total_timesteps | 4730880 | +| train/ | | +| approx_kl | 0.2216737 | +| clip_fraction | 0.0522 | +| clip_range | 0.155 | +| entropy_loss | -3.41 | +| explained_variance | 0.826 | +| learning_rate | 6e-05 | +| loss | 16.2 | +| n_updates | 13190 | +| policy_gradient_loss | 0.0021 | +| value_loss | 39.5 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 344 | +| iterations | 1321 | +| time_elapsed | 13724 | +| total_timesteps | 4734464 | +| train/ | | +| approx_kl | 0.2463834 | +| clip_fraction | 0.115 | +| clip_range | 0.155 | +| entropy_loss | -4.06 | +| explained_variance | 0.555 | +| learning_rate | 6e-05 | +| loss | 4.5 | +| n_updates | 13200 | +| policy_gradient_loss | 0.00879 | +| value_loss | 23.7 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.02e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 344 | +| iterations | 1322 | +| time_elapsed | 13735 | +| total_timesteps | 4738048 | +| train/ | | +| approx_kl | 0.6501107 | +| clip_fraction | 0.125 | +| clip_range | 0.155 | +| entropy_loss | -6.15 | +| explained_variance | 0.142 | +| learning_rate | 6e-05 | +| loss | 0.0465 | +| n_updates | 13210 | +| policy_gradient_loss | 0.0244 | +| value_loss | 10.1 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 344 | +| iterations | 1323 | +| time_elapsed | 13745 | +| total_timesteps | 4741632 | +| train/ | | +| approx_kl | 0.5452938 | +| clip_fraction | 0.114 | +| clip_range | 0.155 | +| entropy_loss | -4.19 | +| explained_variance | 0.315 | +| learning_rate | 6e-05 | +| loss | 2.18 | +| n_updates | 13220 | +| policy_gradient_loss | 0.0266 | +| value_loss | 19.1 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -157 | +| time/ | | +| fps | 344 | +| iterations | 1324 | +| time_elapsed | 13755 | +| total_timesteps | 4745216 | +| train/ | | +| approx_kl | 1.4469587 | +| clip_fraction | 0.0904 | +| clip_range | 0.155 | +| entropy_loss | -4.79 | +| explained_variance | 0.139 | +| learning_rate | 6e-05 | +| loss | 2.66 | +| n_updates | 13230 | +| policy_gradient_loss | 0.011 | +| value_loss | 30.9 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -162 | +| time/ | | +| fps | 344 | +| iterations | 1325 | +| time_elapsed | 13765 | +| total_timesteps | 4748800 | +| train/ | | +| approx_kl | 1.0666864 | +| clip_fraction | 0.118 | +| clip_range | 0.155 | +| entropy_loss | -3.74 | +| explained_variance | 0.443 | +| learning_rate | 6e-05 | +| loss | 31.7 | +| n_updates | 13240 | +| policy_gradient_loss | 0.0201 | +| value_loss | 31.2 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -171 | +| time/ | | +| fps | 344 | +| iterations | 1326 | +| time_elapsed | 13776 | +| total_timesteps | 4752384 | +| train/ | | +| approx_kl | 0.5580775 | +| clip_fraction | 0.0901 | +| clip_range | 0.155 | +| entropy_loss | -3.69 | +| explained_variance | 0.756 | +| learning_rate | 6e-05 | +| loss | 2.57 | +| n_updates | 13250 | +| policy_gradient_loss | 0.0116 | +| value_loss | 22.7 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 344 | +| iterations | 1327 | +| time_elapsed | 13786 | +| total_timesteps | 4755968 | +| train/ | | +| approx_kl | 3.370088 | +| clip_fraction | 0.192 | +| clip_range | 0.155 | +| entropy_loss | -3.96 | +| explained_variance | 0.148 | +| learning_rate | 6e-05 | +| loss | 7.66 | +| n_updates | 13260 | +| policy_gradient_loss | 0.0336 | +| value_loss | 56.7 | +-------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -169 | +| time/ | | +| fps | 344 | +| iterations | 1328 | +| time_elapsed | 13796 | +| total_timesteps | 4759552 | +| train/ | | +| approx_kl | 0.69540817 | +| clip_fraction | 0.0988 | +| clip_range | 0.155 | +| entropy_loss | -3.84 | +| explained_variance | 0.694 | +| learning_rate | 6e-05 | +| loss | 0.533 | +| n_updates | 13270 | +| policy_gradient_loss | 0.0288 | +| value_loss | 6.83 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -168 | +| time/ | | +| fps | 345 | +| iterations | 1329 | +| time_elapsed | 13806 | +| total_timesteps | 4763136 | +| train/ | | +| approx_kl | 0.4503357 | +| clip_fraction | 0.0999 | +| clip_range | 0.155 | +| entropy_loss | -7.03 | +| explained_variance | 0.102 | +| learning_rate | 6e-05 | +| loss | 5.41 | +| n_updates | 13280 | +| policy_gradient_loss | 0.0174 | +| value_loss | 9 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 345 | +| iterations | 1330 | +| time_elapsed | 13816 | +| total_timesteps | 4766720 | +| train/ | | +| approx_kl | 2.3226244 | +| clip_fraction | 0.111 | +| clip_range | 0.155 | +| entropy_loss | -6.75 | +| explained_variance | 0.287 | +| learning_rate | 6e-05 | +| loss | 3.45 | +| n_updates | 13290 | +| policy_gradient_loss | 0.0565 | +| value_loss | 13 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 345 | +| iterations | 1331 | +| time_elapsed | 13826 | +| total_timesteps | 4770304 | +| train/ | | +| approx_kl | 1.2909917 | +| clip_fraction | 0.161 | +| clip_range | 0.155 | +| entropy_loss | -4.39 | +| explained_variance | 0.647 | +| learning_rate | 6e-05 | +| loss | 0.993 | +| n_updates | 13300 | +| policy_gradient_loss | 0.0316 | +| value_loss | 20.1 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 345 | +| iterations | 1332 | +| time_elapsed | 13836 | +| total_timesteps | 4773888 | +| train/ | | +| approx_kl | 1.6418638 | +| clip_fraction | 0.135 | +| clip_range | 0.155 | +| entropy_loss | -5.19 | +| explained_variance | 0.0704 | +| learning_rate | 6e-05 | +| loss | 0.391 | +| n_updates | 13310 | +| policy_gradient_loss | 0.0285 | +| value_loss | 22.3 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 345 | +| iterations | 1333 | +| time_elapsed | 13847 | +| total_timesteps | 4777472 | +| train/ | | +| approx_kl | 0.6947282 | +| clip_fraction | 0.0694 | +| clip_range | 0.155 | +| entropy_loss | -7.81 | +| explained_variance | 0.00247 | +| learning_rate | 6e-05 | +| loss | 0.0211 | +| n_updates | 13320 | +| policy_gradient_loss | 0.0193 | +| value_loss | 33.4 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -167 | +| time/ | | +| fps | 344 | +| iterations | 1334 | +| time_elapsed | 13858 | +| total_timesteps | 4781056 | +| train/ | | +| approx_kl | 0.32345656 | +| clip_fraction | 0.0597 | +| clip_range | 0.155 | +| entropy_loss | -7.95 | +| explained_variance | 0.000276 | +| learning_rate | 6e-05 | +| loss | 5.01 | +| n_updates | 13330 | +| policy_gradient_loss | 0.0241 | +| value_loss | 13.4 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1335 | +| time_elapsed | 13869 | +| total_timesteps | 4784640 | +| train/ | | +| approx_kl | 0.38155493 | +| clip_fraction | 0.0372 | +| clip_range | 0.155 | +| entropy_loss | -7.54 | +| explained_variance | 0.0433 | +| learning_rate | 6e-05 | +| loss | 2.55 | +| n_updates | 13340 | +| policy_gradient_loss | 0.024 | +| value_loss | 15.7 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 344 | +| iterations | 1336 | +| time_elapsed | 13879 | +| total_timesteps | 4788224 | +| train/ | | +| approx_kl | 1.4520452 | +| clip_fraction | 0.0743 | +| clip_range | 0.155 | +| entropy_loss | -7.37 | +| explained_variance | 0.118 | +| learning_rate | 6e-05 | +| loss | 4.44 | +| n_updates | 13350 | +| policy_gradient_loss | 0.0137 | +| value_loss | 11.6 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 344 | +| iterations | 1337 | +| time_elapsed | 13889 | +| total_timesteps | 4791808 | +| train/ | | +| approx_kl | 0.088653326 | +| clip_fraction | 0.0271 | +| clip_range | 0.155 | +| entropy_loss | -8.14 | +| explained_variance | 0.00218 | +| learning_rate | 6e-05 | +| loss | 3.56 | +| n_updates | 13360 | +| policy_gradient_loss | 0.0122 | +| value_loss | 8.62 | +----------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -163 | +| time/ | | +| fps | 345 | +| iterations | 1338 | +| time_elapsed | 13899 | +| total_timesteps | 4795392 | +| train/ | | +| approx_kl | 2.9231522 | +| clip_fraction | 0.0683 | +| clip_range | 0.155 | +| entropy_loss | -4.84 | +| explained_variance | 0.385 | +| learning_rate | 6e-05 | +| loss | 14.9 | +| n_updates | 13370 | +| policy_gradient_loss | 0.0141 | +| value_loss | 30.4 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -169 | +| time/ | | +| fps | 345 | +| iterations | 1339 | +| time_elapsed | 13909 | +| total_timesteps | 4798976 | +| train/ | | +| approx_kl | 3.6014905 | +| clip_fraction | 0.062 | +| clip_range | 0.155 | +| entropy_loss | -7.14 | +| explained_variance | 0.778 | +| learning_rate | 6e-05 | +| loss | 3.03 | +| n_updates | 13380 | +| policy_gradient_loss | 0.00323 | +| value_loss | 28.7 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -185 | +| time/ | | +| fps | 345 | +| iterations | 1340 | +| time_elapsed | 13919 | +| total_timesteps | 4802560 | +| train/ | | +| approx_kl | 2.1823676 | +| clip_fraction | 0.0739 | +| clip_range | 0.155 | +| entropy_loss | -7 | +| explained_variance | 0.139 | +| learning_rate | 6e-05 | +| loss | 2.84 | +| n_updates | 13390 | +| policy_gradient_loss | 0.0214 | +| value_loss | 33.2 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -186 | +| time/ | | +| fps | 345 | +| iterations | 1341 | +| time_elapsed | 13929 | +| total_timesteps | 4806144 | +| train/ | | +| approx_kl | 0.9393884 | +| clip_fraction | 0.0701 | +| clip_range | 0.155 | +| entropy_loss | -1.86 | +| explained_variance | 0.626 | +| learning_rate | 6e-05 | +| loss | 15.4 | +| n_updates | 13400 | +| policy_gradient_loss | 0.00433 | +| value_loss | 14.9 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -183 | +| time/ | | +| fps | 345 | +| iterations | 1342 | +| time_elapsed | 13939 | +| total_timesteps | 4809728 | +| train/ | | +| approx_kl | 2.0223339 | +| clip_fraction | 0.164 | +| clip_range | 0.155 | +| entropy_loss | -2.82 | +| explained_variance | 0.69 | +| learning_rate | 6e-05 | +| loss | 1.42 | +| n_updates | 13410 | +| policy_gradient_loss | 0.014 | +| value_loss | 16.6 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -184 | +| time/ | | +| fps | 345 | +| iterations | 1343 | +| time_elapsed | 13949 | +| total_timesteps | 4813312 | +| train/ | | +| approx_kl | 0.31642827 | +| clip_fraction | 0.0943 | +| clip_range | 0.155 | +| entropy_loss | -5.83 | +| explained_variance | 0.174 | +| learning_rate | 6e-05 | +| loss | 2.84 | +| n_updates | 13420 | +| policy_gradient_loss | 0.0294 | +| value_loss | 13 | +---------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -184 | +| time/ | | +| fps | 345 | +| iterations | 1344 | +| time_elapsed | 13959 | +| total_timesteps | 4816896 | +| train/ | | +| approx_kl | 1.0506774 | +| clip_fraction | 0.152 | +| clip_range | 0.155 | +| entropy_loss | -2.21 | +| explained_variance | 0.147 | +| learning_rate | 6e-05 | +| loss | 2.08 | +| n_updates | 13430 | +| policy_gradient_loss | 0.0501 | +| value_loss | 12.7 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -183 | +| time/ | | +| fps | 345 | +| iterations | 1345 | +| time_elapsed | 13970 | +| total_timesteps | 4820480 | +| train/ | | +| approx_kl | 1.1970882 | +| clip_fraction | 0.175 | +| clip_range | 0.155 | +| entropy_loss | -4.36 | +| explained_variance | 0.655 | +| learning_rate | 6e-05 | +| loss | 1.82 | +| n_updates | 13440 | +| policy_gradient_loss | 0.0331 | +| value_loss | 8.26 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -186 | +| time/ | | +| fps | 345 | +| iterations | 1346 | +| time_elapsed | 13980 | +| total_timesteps | 4824064 | +| train/ | | +| approx_kl | 0.5424376 | +| clip_fraction | 0.141 | +| clip_range | 0.155 | +| entropy_loss | -6.45 | +| explained_variance | 0.104 | +| learning_rate | 6e-05 | +| loss | 2.42 | +| n_updates | 13450 | +| policy_gradient_loss | 0.0255 | +| value_loss | 5.41 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -187 | +| time/ | | +| fps | 345 | +| iterations | 1347 | +| time_elapsed | 13991 | +| total_timesteps | 4827648 | +| train/ | | +| approx_kl | 1.1883717 | +| clip_fraction | 0.1 | +| clip_range | 0.155 | +| entropy_loss | -4.14 | +| explained_variance | 0.498 | +| learning_rate | 6e-05 | +| loss | 2.22 | +| n_updates | 13460 | +| policy_gradient_loss | 0.013 | +| value_loss | 27.2 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -184 | +| time/ | | +| fps | 345 | +| iterations | 1348 | +| time_elapsed | 14002 | +| total_timesteps | 4831232 | +| train/ | | +| approx_kl | 0.78207636 | +| clip_fraction | 0.163 | +| clip_range | 0.155 | +| entropy_loss | -4.48 | +| explained_variance | 0.341 | +| learning_rate | 6e-05 | +| loss | 6.05 | +| n_updates | 13470 | +| policy_gradient_loss | 0.0228 | +| value_loss | 9.41 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -187 | +| time/ | | +| fps | 345 | +| iterations | 1349 | +| time_elapsed | 14012 | +| total_timesteps | 4834816 | +| train/ | | +| approx_kl | 2.3643377 | +| clip_fraction | 0.239 | +| clip_range | 0.155 | +| entropy_loss | -5.9 | +| explained_variance | 0.0829 | +| learning_rate | 6e-05 | +| loss | 0.546 | +| n_updates | 13480 | +| policy_gradient_loss | 0.0688 | +| value_loss | 10.9 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -191 | +| time/ | | +| fps | 344 | +| iterations | 1350 | +| time_elapsed | 14024 | +| total_timesteps | 4838400 | +| train/ | | +| approx_kl | 3.341831 | +| clip_fraction | 0.236 | +| clip_range | 0.155 | +| entropy_loss | -4.69 | +| explained_variance | 0.29 | +| learning_rate | 6e-05 | +| loss | 0.479 | +| n_updates | 13490 | +| policy_gradient_loss | 0.0634 | +| value_loss | 22 | +-------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -191 | +| time/ | | +| fps | 344 | +| iterations | 1351 | +| time_elapsed | 14035 | +| total_timesteps | 4841984 | +| train/ | | +| approx_kl | 0.6706541 | +| clip_fraction | 0.0558 | +| clip_range | 0.155 | +| entropy_loss | -3.11 | +| explained_variance | 0.453 | +| learning_rate | 6e-05 | +| loss | 0.349 | +| n_updates | 13500 | +| policy_gradient_loss | 0.00736 | +| value_loss | 11.8 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -191 | +| time/ | | +| fps | 344 | +| iterations | 1352 | +| time_elapsed | 14046 | +| total_timesteps | 4845568 | +| train/ | | +| approx_kl | 0.7090221 | +| clip_fraction | 0.136 | +| clip_range | 0.155 | +| entropy_loss | -7.3 | +| explained_variance | 0.0492 | +| learning_rate | 6e-05 | +| loss | 0.143 | +| n_updates | 13510 | +| policy_gradient_loss | 0.0426 | +| value_loss | 3.34 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -191 | +| time/ | | +| fps | 344 | +| iterations | 1353 | +| time_elapsed | 14056 | +| total_timesteps | 4849152 | +| train/ | | +| approx_kl | 1.0634267 | +| clip_fraction | 0.0744 | +| clip_range | 0.155 | +| entropy_loss | -5.77 | +| explained_variance | 0.204 | +| learning_rate | 6e-05 | +| loss | 2.44 | +| n_updates | 13520 | +| policy_gradient_loss | 0.00946 | +| value_loss | 5.3 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -185 | +| time/ | | +| fps | 344 | +| iterations | 1354 | +| time_elapsed | 14066 | +| total_timesteps | 4852736 | +| train/ | | +| approx_kl | 0.20827296 | +| clip_fraction | 0.0522 | +| clip_range | 0.155 | +| entropy_loss | -6.91 | +| explained_variance | 0.00459 | +| learning_rate | 6e-05 | +| loss | -0.0133 | +| n_updates | 13530 | +| policy_gradient_loss | 0.0114 | +| value_loss | 3.79 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.98e+03 | +| ep_rew_mean | -184 | +| time/ | | +| fps | 345 | +| iterations | 1355 | +| time_elapsed | 14076 | +| total_timesteps | 4856320 | +| train/ | | +| approx_kl | 0.33593598 | +| clip_fraction | 0.109 | +| clip_range | 0.155 | +| entropy_loss | -5.45 | +| explained_variance | 0.00891 | +| learning_rate | 6e-05 | +| loss | 0.123 | +| n_updates | 13540 | +| policy_gradient_loss | 0.0399 | +| value_loss | 18.3 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -185 | +| time/ | | +| fps | 344 | +| iterations | 1356 | +| time_elapsed | 14086 | +| total_timesteps | 4859904 | +| train/ | | +| approx_kl | 0.05657869 | +| clip_fraction | 0.0286 | +| clip_range | 0.155 | +| entropy_loss | -8.22 | +| explained_variance | 0.000529 | +| learning_rate | 6e-05 | +| loss | 6.88 | +| n_updates | 13550 | +| policy_gradient_loss | 0.00637 | +| value_loss | 4.58 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -188 | +| time/ | | +| fps | 344 | +| iterations | 1357 | +| time_elapsed | 14097 | +| total_timesteps | 4863488 | +| train/ | | +| approx_kl | 0.07934006 | +| clip_fraction | 0.0436 | +| clip_range | 0.155 | +| entropy_loss | -8.16 | +| explained_variance | 0.0135 | +| learning_rate | 6e-05 | +| loss | 6.9 | +| n_updates | 13560 | +| policy_gradient_loss | 0.00919 | +| value_loss | 17.9 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -188 | +| time/ | | +| fps | 344 | +| iterations | 1358 | +| time_elapsed | 14108 | +| total_timesteps | 4867072 | +| train/ | | +| approx_kl | 0.8120286 | +| clip_fraction | 0.0188 | +| clip_range | 0.155 | +| entropy_loss | -8.04 | +| explained_variance | 0.0475 | +| learning_rate | 6e-05 | +| loss | 8.86 | +| n_updates | 13570 | +| policy_gradient_loss | 0.00439 | +| value_loss | 32 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -189 | +| time/ | | +| fps | 344 | +| iterations | 1359 | +| time_elapsed | 14118 | +| total_timesteps | 4870656 | +| train/ | | +| approx_kl | 0.110729255 | +| clip_fraction | 0.0207 | +| clip_range | 0.155 | +| entropy_loss | -8.16 | +| explained_variance | 0.0165 | +| learning_rate | 6e-05 | +| loss | 1.07 | +| n_updates | 13580 | +| policy_gradient_loss | 0.00468 | +| value_loss | 21.9 | +----------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -192 | +| time/ | | +| fps | 344 | +| iterations | 1360 | +| time_elapsed | 14128 | +| total_timesteps | 4874240 | +| train/ | | +| approx_kl | 0.18688758 | +| clip_fraction | 0.0241 | +| clip_range | 0.155 | +| entropy_loss | -6.68 | +| explained_variance | 0.18 | +| learning_rate | 6e-05 | +| loss | 11.2 | +| n_updates | 13590 | +| policy_gradient_loss | 0.00282 | +| value_loss | 9.49 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +------------------------------------------ +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -192 | +| time/ | | +| fps | 344 | +| iterations | 1361 | +| time_elapsed | 14138 | +| total_timesteps | 4877824 | +| train/ | | +| approx_kl | 0.0018398982 | +| clip_fraction | 0.000391 | +| clip_range | 0.155 | +| entropy_loss | -8.24 | +| explained_variance | 0.0547 | +| learning_rate | 6e-05 | +| loss | 67.1 | +| n_updates | 13600 | +| policy_gradient_loss | 9.2e-05 | +| value_loss | 26.4 | +------------------------------------------ + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -185 | +| time/ | | +| fps | 345 | +| iterations | 1362 | +| time_elapsed | 14148 | +| total_timesteps | 4881408 | +| train/ | | +| approx_kl | 3.6346858 | +| clip_fraction | 0.0984 | +| clip_range | 0.155 | +| entropy_loss | -7.13 | +| explained_variance | 0.0354 | +| learning_rate | 6e-05 | +| loss | 15.1 | +| n_updates | 13610 | +| policy_gradient_loss | 0.00815 | +| value_loss | 13.3 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -186 | +| time/ | | +| fps | 345 | +| iterations | 1363 | +| time_elapsed | 14159 | +| total_timesteps | 4884992 | +| train/ | | +| approx_kl | 0.53891695 | +| clip_fraction | 0.0695 | +| clip_range | 0.155 | +| entropy_loss | -7.62 | +| explained_variance | 0.0351 | +| learning_rate | 6e-05 | +| loss | 11.1 | +| n_updates | 13620 | +| policy_gradient_loss | 0.0368 | +| value_loss | 16.8 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -183 | +| time/ | | +| fps | 345 | +| iterations | 1364 | +| time_elapsed | 14169 | +| total_timesteps | 4888576 | +| train/ | | +| approx_kl | 0.2712156 | +| clip_fraction | 0.034 | +| clip_range | 0.155 | +| entropy_loss | -7.74 | +| explained_variance | 0.0233 | +| learning_rate | 6e-05 | +| loss | 0.708 | +| n_updates | 13630 | +| policy_gradient_loss | 0.063 | +| value_loss | 8.14 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -179 | +| time/ | | +| fps | 345 | +| iterations | 1365 | +| time_elapsed | 14179 | +| total_timesteps | 4892160 | +| train/ | | +| approx_kl | 0.13332911 | +| clip_fraction | 0.0186 | +| clip_range | 0.155 | +| entropy_loss | -8.19 | +| explained_variance | -0.00112 | +| learning_rate | 6e-05 | +| loss | 0.0954 | +| n_updates | 13640 | +| policy_gradient_loss | 0.00633 | +| value_loss | 26.2 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -178 | +| time/ | | +| fps | 345 | +| iterations | 1366 | +| time_elapsed | 14189 | +| total_timesteps | 4895744 | +| train/ | | +| approx_kl | 0.21810673 | +| clip_fraction | 0.0289 | +| clip_range | 0.155 | +| entropy_loss | -7.92 | +| explained_variance | 0.0827 | +| learning_rate | 6e-05 | +| loss | 3.73 | +| n_updates | 13650 | +| policy_gradient_loss | 0.0146 | +| value_loss | 14.4 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -177 | +| time/ | | +| fps | 345 | +| iterations | 1367 | +| time_elapsed | 14199 | +| total_timesteps | 4899328 | +| train/ | | +| approx_kl | 3.0550969 | +| clip_fraction | 0.0936 | +| clip_range | 0.155 | +| entropy_loss | -6.94 | +| explained_variance | 0.127 | +| learning_rate | 6e-05 | +| loss | 0.0931 | +| n_updates | 13660 | +| policy_gradient_loss | 0.00626 | +| value_loss | 13.6 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.98e+03 | +| ep_rew_mean | -177 | +| time/ | | +| fps | 345 | +| iterations | 1368 | +| time_elapsed | 14210 | +| total_timesteps | 4902912 | +| train/ | | +| approx_kl | 1.2949284 | +| clip_fraction | 0.037 | +| clip_range | 0.155 | +| entropy_loss | -7.63 | +| explained_variance | 0.117 | +| learning_rate | 6e-05 | +| loss | -0.0621 | +| n_updates | 13670 | +| policy_gradient_loss | 0.00637 | +| value_loss | 8.54 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.02e+03 | +| ep_rew_mean | -174 | +| time/ | | +| fps | 345 | +| iterations | 1369 | +| time_elapsed | 14221 | +| total_timesteps | 4906496 | +| train/ | | +| approx_kl | 1.1919372 | +| clip_fraction | 0.0134 | +| clip_range | 0.155 | +| entropy_loss | -8.16 | +| explained_variance | 0.0112 | +| learning_rate | 6e-05 | +| loss | 4.23 | +| n_updates | 13680 | +| policy_gradient_loss | 0.00778 | +| value_loss | 4.16 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.03e+03 | +| ep_rew_mean | -171 | +| time/ | | +| fps | 345 | +| iterations | 1370 | +| time_elapsed | 14231 | +| total_timesteps | 4910080 | +| train/ | | +| approx_kl | 0.0179961 | +| clip_fraction | 0.0041 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | -0.000182 | +| learning_rate | 6e-05 | +| loss | 43.1 | +| n_updates | 13690 | +| policy_gradient_loss | 0.0015 | +| value_loss | 22.8 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 345 | +| iterations | 1371 | +| time_elapsed | 14241 | +| total_timesteps | 4913664 | +| train/ | | +| approx_kl | 1.9386423 | +| clip_fraction | 0.0433 | +| clip_range | 0.155 | +| entropy_loss | -7.84 | +| explained_variance | 0.0032 | +| learning_rate | 6e-05 | +| loss | 26 | +| n_updates | 13700 | +| policy_gradient_loss | 0.00329 | +| value_loss | 12.1 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 345 | +| iterations | 1372 | +| time_elapsed | 14251 | +| total_timesteps | 4917248 | +| train/ | | +| approx_kl | 0.9494027 | +| clip_fraction | 0.113 | +| clip_range | 0.155 | +| entropy_loss | -4.43 | +| explained_variance | 0.373 | +| learning_rate | 6e-05 | +| loss | 2.7 | +| n_updates | 13710 | +| policy_gradient_loss | 0.0438 | +| value_loss | 7.09 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.04e+03 | +| ep_rew_mean | -170 | +| time/ | | +| fps | 345 | +| iterations | 1373 | +| time_elapsed | 14261 | +| total_timesteps | 4920832 | +| train/ | | +| approx_kl | 0.5891393 | +| clip_fraction | 0.0484 | +| clip_range | 0.155 | +| entropy_loss | -6.38 | +| explained_variance | 0.313 | +| learning_rate | 6e-05 | +| loss | 0.123 | +| n_updates | 13720 | +| policy_gradient_loss | 0.0104 | +| value_loss | 3.18 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -166 | +| time/ | | +| fps | 345 | +| iterations | 1374 | +| time_elapsed | 14271 | +| total_timesteps | 4924416 | +| train/ | | +| approx_kl | 0.6578528 | +| clip_fraction | 0.074 | +| clip_range | 0.155 | +| entropy_loss | -5.77 | +| explained_variance | 0.231 | +| learning_rate | 6e-05 | +| loss | 2.23 | +| n_updates | 13730 | +| policy_gradient_loss | 0.00877 | +| value_loss | 3.77 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 345 | +| iterations | 1375 | +| time_elapsed | 14281 | +| total_timesteps | 4928000 | +| train/ | | +| approx_kl | 0.118938096 | +| clip_fraction | 0.0303 | +| clip_range | 0.155 | +| entropy_loss | -8.08 | +| explained_variance | 0.00925 | +| learning_rate | 6e-05 | +| loss | 0.159 | +| n_updates | 13740 | +| policy_gradient_loss | 0.0133 | +| value_loss | 6.96 | +----------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 345 | +| iterations | 1376 | +| time_elapsed | 14291 | +| total_timesteps | 4931584 | +| train/ | | +| approx_kl | 0.06356572 | +| clip_fraction | 0.012 | +| clip_range | 0.155 | +| entropy_loss | -8.25 | +| explained_variance | -0.000404 | +| learning_rate | 6e-05 | +| loss | 4.82 | +| n_updates | 13750 | +| policy_gradient_loss | 0.00367 | +| value_loss | 10.6 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -163 | +| time/ | | +| fps | 345 | +| iterations | 1377 | +| time_elapsed | 14301 | +| total_timesteps | 4935168 | +| train/ | | +| approx_kl | 0.93235195 | +| clip_fraction | 0.0136 | +| clip_range | 0.155 | +| entropy_loss | -7.5 | +| explained_variance | 0.111 | +| learning_rate | 6e-05 | +| loss | 7.89 | +| n_updates | 13760 | +| policy_gradient_loss | 0.00156 | +| value_loss | 25.9 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.19e+03 | +| ep_rew_mean | -160 | +| time/ | | +| fps | 345 | +| iterations | 1378 | +| time_elapsed | 14311 | +| total_timesteps | 4938752 | +| train/ | | +| approx_kl | 0.013457686 | +| clip_fraction | 0.00879 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 4.8e-05 | +| learning_rate | 6e-05 | +| loss | 0.518 | +| n_updates | 13770 | +| policy_gradient_loss | 0.00207 | +| value_loss | 18.5 | +----------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.2e+03 | +| ep_rew_mean | -156 | +| time/ | | +| fps | 345 | +| iterations | 1379 | +| time_elapsed | 14322 | +| total_timesteps | 4942336 | +| train/ | | +| approx_kl | 5.237766 | +| clip_fraction | 0.143 | +| clip_range | 0.155 | +| entropy_loss | -5.75 | +| explained_variance | 0.0506 | +| learning_rate | 6e-05 | +| loss | 0.887 | +| n_updates | 13780 | +| policy_gradient_loss | 0.0298 | +| value_loss | 25.4 | +-------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -155 | +| time/ | | +| fps | 345 | +| iterations | 1380 | +| time_elapsed | 14333 | +| total_timesteps | 4945920 | +| train/ | | +| approx_kl | 5.0655437 | +| clip_fraction | 0.0989 | +| clip_range | 0.155 | +| entropy_loss | -6.18 | +| explained_variance | 0.289 | +| learning_rate | 6e-05 | +| loss | 0.946 | +| n_updates | 13790 | +| policy_gradient_loss | 0.00408 | +| value_loss | 15.3 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 345 | +| iterations | 1381 | +| time_elapsed | 14344 | +| total_timesteps | 4949504 | +| train/ | | +| approx_kl | 7.92747 | +| clip_fraction | 0.131 | +| clip_range | 0.155 | +| entropy_loss | -6.23 | +| explained_variance | 0.177 | +| learning_rate | 6e-05 | +| loss | 2.95 | +| n_updates | 13800 | +| policy_gradient_loss | 0.0115 | +| value_loss | 29 | +-------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 345 | +| iterations | 1382 | +| time_elapsed | 14355 | +| total_timesteps | 4953088 | +| train/ | | +| approx_kl | 5.3562403 | +| clip_fraction | 0.132 | +| clip_range | 0.155 | +| entropy_loss | -6.01 | +| explained_variance | 0.146 | +| learning_rate | 6e-05 | +| loss | 7.78 | +| n_updates | 13810 | +| policy_gradient_loss | 0.0218 | +| value_loss | 35.4 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 345 | +| iterations | 1383 | +| time_elapsed | 14365 | +| total_timesteps | 4956672 | +| train/ | | +| approx_kl | 1.4408809 | +| clip_fraction | 0.103 | +| clip_range | 0.155 | +| entropy_loss | -3.37 | +| explained_variance | 0.373 | +| learning_rate | 6e-05 | +| loss | 5 | +| n_updates | 13820 | +| policy_gradient_loss | 0.00697 | +| value_loss | 29.4 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.17e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1384 | +| time_elapsed | 14376 | +| total_timesteps | 4960256 | +| train/ | | +| approx_kl | 1.2644961 | +| clip_fraction | 0.0927 | +| clip_range | 0.155 | +| entropy_loss | -4.59 | +| explained_variance | 0.41 | +| learning_rate | 6e-05 | +| loss | 4.49 | +| n_updates | 13830 | +| policy_gradient_loss | 0.012 | +| value_loss | 33 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 345 | +| iterations | 1385 | +| time_elapsed | 14387 | +| total_timesteps | 4963840 | +| train/ | | +| approx_kl | 2.8429894 | +| clip_fraction | 0.128 | +| clip_range | 0.155 | +| entropy_loss | -4.69 | +| explained_variance | 0.439 | +| learning_rate | 6e-05 | +| loss | 5.44 | +| n_updates | 13840 | +| policy_gradient_loss | 0.00923 | +| value_loss | 17.7 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 344 | +| iterations | 1386 | +| time_elapsed | 14398 | +| total_timesteps | 4967424 | +| train/ | | +| approx_kl | 1.1384536 | +| clip_fraction | 0.0783 | +| clip_range | 0.155 | +| entropy_loss | -2.81 | +| explained_variance | 0.533 | +| learning_rate | 6e-05 | +| loss | 0.401 | +| n_updates | 13850 | +| policy_gradient_loss | 0.018 | +| value_loss | 10.5 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 344 | +| iterations | 1387 | +| time_elapsed | 14409 | +| total_timesteps | 4971008 | +| train/ | | +| approx_kl | 0.36252293 | +| clip_fraction | 0.0923 | +| clip_range | 0.155 | +| entropy_loss | -4.99 | +| explained_variance | 0.387 | +| learning_rate | 6e-05 | +| loss | 6.62 | +| n_updates | 13860 | +| policy_gradient_loss | 0.0102 | +| value_loss | 16.1 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.23e+03 | +| ep_rew_mean | -142 | +| time/ | | +| fps | 345 | +| iterations | 1388 | +| time_elapsed | 14419 | +| total_timesteps | 4974592 | +| train/ | | +| approx_kl | 2.1905668 | +| clip_fraction | 0.137 | +| clip_range | 0.155 | +| entropy_loss | -4.18 | +| explained_variance | 0.318 | +| learning_rate | 6e-05 | +| loss | 15.6 | +| n_updates | 13870 | +| policy_gradient_loss | 0.0195 | +| value_loss | 15.6 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 345 | +| iterations | 1389 | +| time_elapsed | 14429 | +| total_timesteps | 4978176 | +| train/ | | +| approx_kl | 0.25023693 | +| clip_fraction | 0.127 | +| clip_range | 0.155 | +| entropy_loss | -4.69 | +| explained_variance | 0.237 | +| learning_rate | 6e-05 | +| loss | 20.2 | +| n_updates | 13880 | +| policy_gradient_loss | 0.0187 | +| value_loss | 38.5 | +---------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.23e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 345 | +| iterations | 1390 | +| time_elapsed | 14439 | +| total_timesteps | 4981760 | +| train/ | | +| approx_kl | 0.89480674 | +| clip_fraction | 0.153 | +| clip_range | 0.155 | +| entropy_loss | -4.17 | +| explained_variance | 0.165 | +| learning_rate | 6e-05 | +| loss | 7.19 | +| n_updates | 13890 | +| policy_gradient_loss | 0.0175 | +| value_loss | 27 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.23e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 345 | +| iterations | 1391 | +| time_elapsed | 14450 | +| total_timesteps | 4985344 | +| train/ | | +| approx_kl | 0.4866137 | +| clip_fraction | 0.0922 | +| clip_range | 0.155 | +| entropy_loss | -3.19 | +| explained_variance | 0.439 | +| learning_rate | 6e-05 | +| loss | 4.27 | +| n_updates | 13900 | +| policy_gradient_loss | 0.0251 | +| value_loss | 11.1 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.22e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 344 | +| iterations | 1392 | +| time_elapsed | 14460 | +| total_timesteps | 4988928 | +| train/ | | +| approx_kl | 3.5420516 | +| clip_fraction | 0.167 | +| clip_range | 0.155 | +| entropy_loss | -6.47 | +| explained_variance | 0.0293 | +| learning_rate | 6e-05 | +| loss | 9.67 | +| n_updates | 13910 | +| policy_gradient_loss | 0.044 | +| value_loss | 23.4 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1393 | +| time_elapsed | 14470 | +| total_timesteps | 4992512 | +| train/ | | +| approx_kl | 0.54634434 | +| clip_fraction | 0.0764 | +| clip_range | 0.155 | +| entropy_loss | -7.96 | +| explained_variance | 0.0145 | +| learning_rate | 6e-05 | +| loss | 6.79 | +| n_updates | 13920 | +| policy_gradient_loss | 0.0286 | +| value_loss | 17.7 | +---------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 345 | +| iterations | 1394 | +| time_elapsed | 14481 | +| total_timesteps | 4996096 | +| train/ | | +| approx_kl | 3.3231447 | +| clip_fraction | 0.0629 | +| clip_range | 0.155 | +| entropy_loss | -3.05 | +| explained_variance | 0.322 | +| learning_rate | 6e-05 | +| loss | 12.5 | +| n_updates | 13930 | +| policy_gradient_loss | 0.00616 | +| value_loss | 61.2 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.15e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 345 | +| iterations | 1395 | +| time_elapsed | 14491 | +| total_timesteps | 4999680 | +| train/ | | +| approx_kl | 0.48948935 | +| clip_fraction | 0.0339 | +| clip_range | 0.155 | +| entropy_loss | -7.01 | +| explained_variance | 0.65 | +| learning_rate | 6e-05 | +| loss | 0.443 | +| n_updates | 13940 | +| policy_gradient_loss | 0.00547 | +| value_loss | 13.8 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.15e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1396 | +| time_elapsed | 14501 | +| total_timesteps | 5003264 | +| train/ | | +| approx_kl | 0.45854667 | +| clip_fraction | 0.134 | +| clip_range | 0.155 | +| entropy_loss | -7.75 | +| explained_variance | -0.0232 | +| learning_rate | 6e-05 | +| loss | 0.462 | +| n_updates | 13950 | +| policy_gradient_loss | 0.0632 | +| value_loss | 20.7 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.15e+03 | +| ep_rew_mean | -141 | +| time/ | | +| fps | 345 | +| iterations | 1397 | +| time_elapsed | 14511 | +| total_timesteps | 5006848 | +| train/ | | +| approx_kl | 0.5716791 | +| clip_fraction | 0.0808 | +| clip_range | 0.155 | +| entropy_loss | -5.06 | +| explained_variance | 0.144 | +| learning_rate | 6e-05 | +| loss | 0.452 | +| n_updates | 13960 | +| policy_gradient_loss | 0.0208 | +| value_loss | 13.2 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 345 | +| iterations | 1398 | +| time_elapsed | 14521 | +| total_timesteps | 5010432 | +| train/ | | +| approx_kl | 3.7487123 | +| clip_fraction | 0.176 | +| clip_range | 0.155 | +| entropy_loss | -5.06 | +| explained_variance | 0.0824 | +| learning_rate | 6e-05 | +| loss | 7.75 | +| n_updates | 13970 | +| policy_gradient_loss | 0.0468 | +| value_loss | 24.4 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.18e+03 | +| ep_rew_mean | -136 | +| time/ | | +| fps | 345 | +| iterations | 1399 | +| time_elapsed | 14531 | +| total_timesteps | 5014016 | +| train/ | | +| approx_kl | 1.0328172 | +| clip_fraction | 0.138 | +| clip_range | 0.155 | +| entropy_loss | -6.83 | +| explained_variance | 0.0668 | +| learning_rate | 6e-05 | +| loss | 20.9 | +| n_updates | 13980 | +| policy_gradient_loss | 0.0137 | +| value_loss | 12.7 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -137 | +| time/ | | +| fps | 345 | +| iterations | 1400 | +| time_elapsed | 14541 | +| total_timesteps | 5017600 | +| train/ | | +| approx_kl | 1.8316603 | +| clip_fraction | 0.124 | +| clip_range | 0.155 | +| entropy_loss | -6.52 | +| explained_variance | 0.0549 | +| learning_rate | 6e-05 | +| loss | 4.2 | +| n_updates | 13990 | +| policy_gradient_loss | 0.0216 | +| value_loss | 25.7 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -136 | +| time/ | | +| fps | 345 | +| iterations | 1401 | +| time_elapsed | 14551 | +| total_timesteps | 5021184 | +| train/ | | +| approx_kl | 0.35482427 | +| clip_fraction | 0.113 | +| clip_range | 0.155 | +| entropy_loss | -2.8 | +| explained_variance | 0.296 | +| learning_rate | 6e-05 | +| loss | 11.3 | +| n_updates | 14000 | +| policy_gradient_loss | 0.0241 | +| value_loss | 13.3 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -132 | +| time/ | | +| fps | 345 | +| iterations | 1402 | +| time_elapsed | 14561 | +| total_timesteps | 5024768 | +| train/ | | +| approx_kl | 1.0581255 | +| clip_fraction | 0.186 | +| clip_range | 0.155 | +| entropy_loss | -5.06 | +| explained_variance | 0.285 | +| learning_rate | 6e-05 | +| loss | 4.32 | +| n_updates | 14010 | +| policy_gradient_loss | 0.0162 | +| value_loss | 7.99 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.21e+03 | +| ep_rew_mean | -132 | +| time/ | | +| fps | 345 | +| iterations | 1403 | +| time_elapsed | 14572 | +| total_timesteps | 5028352 | +| train/ | | +| approx_kl | 3.6392674 | +| clip_fraction | 0.132 | +| clip_range | 0.155 | +| entropy_loss | -7.3 | +| explained_variance | 0.00257 | +| learning_rate | 6e-05 | +| loss | 0.693 | +| n_updates | 14020 | +| policy_gradient_loss | 0.0191 | +| value_loss | 19 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.2e+03 | +| ep_rew_mean | -132 | +| time/ | | +| fps | 345 | +| iterations | 1404 | +| time_elapsed | 14583 | +| total_timesteps | 5031936 | +| train/ | | +| approx_kl | 2.2182648 | +| clip_fraction | 0.108 | +| clip_range | 0.155 | +| entropy_loss | -6.48 | +| explained_variance | 0.113 | +| learning_rate | 6e-05 | +| loss | 0.0761 | +| n_updates | 14030 | +| policy_gradient_loss | 0.0094 | +| value_loss | 10.9 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.14e+03 | +| ep_rew_mean | -136 | +| time/ | | +| fps | 345 | +| iterations | 1405 | +| time_elapsed | 14593 | +| total_timesteps | 5035520 | +| train/ | | +| approx_kl | 1.0027443 | +| clip_fraction | 0.0607 | +| clip_range | 0.155 | +| entropy_loss | -6.64 | +| explained_variance | 0.188 | +| learning_rate | 6e-05 | +| loss | 8.84 | +| n_updates | 14040 | +| policy_gradient_loss | 0.00948 | +| value_loss | 20.2 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.14e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1406 | +| time_elapsed | 14603 | +| total_timesteps | 5039104 | +| train/ | | +| approx_kl | 0.668687 | +| clip_fraction | 0.0923 | +| clip_range | 0.155 | +| entropy_loss | -4.77 | +| explained_variance | 0.723 | +| learning_rate | 6e-05 | +| loss | 1.37 | +| n_updates | 14050 | +| policy_gradient_loss | 0.00564 | +| value_loss | 29.9 | +-------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -140 | +| time/ | | +| fps | 345 | +| iterations | 1407 | +| time_elapsed | 14613 | +| total_timesteps | 5042688 | +| train/ | | +| approx_kl | 1.6346362 | +| clip_fraction | 0.0435 | +| clip_range | 0.155 | +| entropy_loss | -4.52 | +| explained_variance | 0.726 | +| learning_rate | 6e-05 | +| loss | 12.9 | +| n_updates | 14060 | +| policy_gradient_loss | 0.00627 | +| value_loss | 39.4 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.14e+03 | +| ep_rew_mean | -140 | +| time/ | | +| fps | 345 | +| iterations | 1408 | +| time_elapsed | 14623 | +| total_timesteps | 5046272 | +| train/ | | +| approx_kl | 1.7040757 | +| clip_fraction | 0.104 | +| clip_range | 0.155 | +| entropy_loss | -6.85 | +| explained_variance | 0.809 | +| learning_rate | 6e-05 | +| loss | 16.3 | +| n_updates | 14070 | +| policy_gradient_loss | 0.026 | +| value_loss | 6.6 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 345 | +| iterations | 1409 | +| time_elapsed | 14633 | +| total_timesteps | 5049856 | +| train/ | | +| approx_kl | 0.43888965 | +| clip_fraction | 0.118 | +| clip_range | 0.155 | +| entropy_loss | -3.44 | +| explained_variance | 0.45 | +| learning_rate | 6e-05 | +| loss | 19.2 | +| n_updates | 14080 | +| policy_gradient_loss | 0.0258 | +| value_loss | 19.8 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 345 | +| iterations | 1410 | +| time_elapsed | 14643 | +| total_timesteps | 5053440 | +| train/ | | +| approx_kl | 0.498909 | +| clip_fraction | 0.105 | +| clip_range | 0.155 | +| entropy_loss | -4.67 | +| explained_variance | 0.302 | +| learning_rate | 6e-05 | +| loss | 2.89 | +| n_updates | 14090 | +| policy_gradient_loss | 0.012 | +| value_loss | 15.6 | +-------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 345 | +| iterations | 1411 | +| time_elapsed | 14652 | +| total_timesteps | 5057024 | +| train/ | | +| approx_kl | 6.417053 | +| clip_fraction | 0.106 | +| clip_range | 0.155 | +| entropy_loss | -6.39 | +| explained_variance | 0.125 | +| learning_rate | 6e-05 | +| loss | 4.54 | +| n_updates | 14100 | +| policy_gradient_loss | 0.0147 | +| value_loss | 17.1 | +-------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 345 | +| iterations | 1412 | +| time_elapsed | 14662 | +| total_timesteps | 5060608 | +| train/ | | +| approx_kl | 1.2884039 | +| clip_fraction | 0.0778 | +| clip_range | 0.155 | +| entropy_loss | -6.8 | +| explained_variance | 0.206 | +| learning_rate | 6e-05 | +| loss | 0.53 | +| n_updates | 14110 | +| policy_gradient_loss | 0.0253 | +| value_loss | 15 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -141 | +| time/ | | +| fps | 345 | +| iterations | 1413 | +| time_elapsed | 14672 | +| total_timesteps | 5064192 | +| train/ | | +| approx_kl | 0.7366382 | +| clip_fraction | 0.108 | +| clip_range | 0.155 | +| entropy_loss | -2.91 | +| explained_variance | 0.287 | +| learning_rate | 6e-05 | +| loss | 5.3 | +| n_updates | 14120 | +| policy_gradient_loss | 0.0187 | +| value_loss | 5.03 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.98e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 345 | +| iterations | 1414 | +| time_elapsed | 14683 | +| total_timesteps | 5067776 | +| train/ | | +| approx_kl | 4.1877112 | +| clip_fraction | 0.079 | +| clip_range | 0.155 | +| entropy_loss | -6.6 | +| explained_variance | 0.0934 | +| learning_rate | 6e-05 | +| loss | 4.25 | +| n_updates | 14130 | +| policy_gradient_loss | 0.0111 | +| value_loss | 20.9 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -142 | +| time/ | | +| fps | 345 | +| iterations | 1415 | +| time_elapsed | 14694 | +| total_timesteps | 5071360 | +| train/ | | +| approx_kl | 7.08166 | +| clip_fraction | 0.119 | +| clip_range | 0.155 | +| entropy_loss | -4.76 | +| explained_variance | 0.794 | +| learning_rate | 6e-05 | +| loss | 4.24 | +| n_updates | 14140 | +| policy_gradient_loss | 0.000252 | +| value_loss | 26.2 | +-------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 345 | +| iterations | 1416 | +| time_elapsed | 14705 | +| total_timesteps | 5074944 | +| train/ | | +| approx_kl | 2.4101455 | +| clip_fraction | 0.0798 | +| clip_range | 0.155 | +| entropy_loss | -7.07 | +| explained_variance | 0.0167 | +| learning_rate | 6e-05 | +| loss | 6.62 | +| n_updates | 14150 | +| policy_gradient_loss | 0.0234 | +| value_loss | 36.6 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1417 | +| time_elapsed | 14715 | +| total_timesteps | 5078528 | +| train/ | | +| approx_kl | 0.9413516 | +| clip_fraction | 0.0545 | +| clip_range | 0.155 | +| entropy_loss | -6.95 | +| explained_variance | 0.244 | +| learning_rate | 6e-05 | +| loss | 0.136 | +| n_updates | 14160 | +| policy_gradient_loss | 0.0195 | +| value_loss | 10.5 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.96e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 345 | +| iterations | 1418 | +| time_elapsed | 14725 | +| total_timesteps | 5082112 | +| train/ | | +| approx_kl | 1.449647 | +| clip_fraction | 0.0859 | +| clip_range | 0.155 | +| entropy_loss | -6.71 | +| explained_variance | 0.183 | +| learning_rate | 6e-05 | +| loss | 7.19 | +| n_updates | 14170 | +| policy_gradient_loss | 0.0109 | +| value_loss | 25.6 | +-------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -154 | +| time/ | | +| fps | 345 | +| iterations | 1419 | +| time_elapsed | 14735 | +| total_timesteps | 5085696 | +| train/ | | +| approx_kl | 0.5386229 | +| clip_fraction | 0.0544 | +| clip_range | 0.155 | +| entropy_loss | -6.48 | +| explained_variance | 0.297 | +| learning_rate | 6e-05 | +| loss | 0.164 | +| n_updates | 14180 | +| policy_gradient_loss | 0.00428 | +| value_loss | 13.3 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.97e+03 | +| ep_rew_mean | -154 | +| time/ | | +| fps | 345 | +| iterations | 1420 | +| time_elapsed | 14747 | +| total_timesteps | 5089280 | +| train/ | | +| approx_kl | 6.9624915 | +| clip_fraction | 0.171 | +| clip_range | 0.155 | +| entropy_loss | -4.06 | +| explained_variance | 0.268 | +| learning_rate | 6e-05 | +| loss | 0.66 | +| n_updates | 14190 | +| policy_gradient_loss | 0.0186 | +| value_loss | 8.85 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -157 | +| time/ | | +| fps | 345 | +| iterations | 1421 | +| time_elapsed | 14759 | +| total_timesteps | 5092864 | +| train/ | | +| approx_kl | 0.69206005 | +| clip_fraction | 0.0904 | +| clip_range | 0.155 | +| entropy_loss | -1.4 | +| explained_variance | 0.265 | +| learning_rate | 6e-05 | +| loss | 0.909 | +| n_updates | 14200 | +| policy_gradient_loss | 0.0157 | +| value_loss | 4.24 | +---------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.02e+03 | +| ep_rew_mean | -157 | +| time/ | | +| fps | 345 | +| iterations | 1422 | +| time_elapsed | 14769 | +| total_timesteps | 5096448 | +| train/ | | +| approx_kl | 5.0647073 | +| clip_fraction | 0.158 | +| clip_range | 0.155 | +| entropy_loss | -3.11 | +| explained_variance | 0.404 | +| learning_rate | 6e-05 | +| loss | 2.03 | +| n_updates | 14210 | +| policy_gradient_loss | 0.0339 | +| value_loss | 13.4 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.01e+03 | +| ep_rew_mean | -156 | +| time/ | | +| fps | 345 | +| iterations | 1423 | +| time_elapsed | 14779 | +| total_timesteps | 5100032 | +| train/ | | +| approx_kl | 1.6927248 | +| clip_fraction | 0.101 | +| clip_range | 0.155 | +| entropy_loss | -5.99 | +| explained_variance | 0.344 | +| learning_rate | 6e-05 | +| loss | 9.98 | +| n_updates | 14220 | +| policy_gradient_loss | 0.0056 | +| value_loss | 12 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -160 | +| time/ | | +| fps | 345 | +| iterations | 1424 | +| time_elapsed | 14789 | +| total_timesteps | 5103616 | +| train/ | | +| approx_kl | 1.2318003 | +| clip_fraction | 0.0294 | +| clip_range | 0.155 | +| entropy_loss | -8 | +| explained_variance | 0.0432 | +| learning_rate | 6e-05 | +| loss | 1.74 | +| n_updates | 14230 | +| policy_gradient_loss | 0.00725 | +| value_loss | 12.5 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -166 | +| time/ | | +| fps | 345 | +| iterations | 1425 | +| time_elapsed | 14799 | +| total_timesteps | 5107200 | +| train/ | | +| approx_kl | 2.021108 | +| clip_fraction | 0.097 | +| clip_range | 0.155 | +| entropy_loss | -3.6 | +| explained_variance | 0.343 | +| learning_rate | 6e-05 | +| loss | 2.05 | +| n_updates | 14240 | +| policy_gradient_loss | 0.00751 | +| value_loss | 21.7 | +-------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.81e+03 | +| ep_rew_mean | -169 | +| time/ | | +| fps | 345 | +| iterations | 1426 | +| time_elapsed | 14810 | +| total_timesteps | 5110784 | +| train/ | | +| approx_kl | 3.6411357 | +| clip_fraction | 0.0921 | +| clip_range | 0.155 | +| entropy_loss | -3.74 | +| explained_variance | 0.718 | +| learning_rate | 6e-05 | +| loss | 16.2 | +| n_updates | 14250 | +| policy_gradient_loss | 0.00802 | +| value_loss | 29 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.8e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 345 | +| iterations | 1427 | +| time_elapsed | 14821 | +| total_timesteps | 5114368 | +| train/ | | +| approx_kl | 1.2799231 | +| clip_fraction | 0.12 | +| clip_range | 0.155 | +| entropy_loss | -4.44 | +| explained_variance | 0.391 | +| learning_rate | 6e-05 | +| loss | 6.94 | +| n_updates | 14260 | +| policy_gradient_loss | 0.012 | +| value_loss | 43 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.79e+03 | +| ep_rew_mean | -164 | +| time/ | | +| fps | 345 | +| iterations | 1428 | +| time_elapsed | 14831 | +| total_timesteps | 5117952 | +| train/ | | +| approx_kl | 1.2394456 | +| clip_fraction | 0.144 | +| clip_range | 0.155 | +| entropy_loss | -4.25 | +| explained_variance | 0.355 | +| learning_rate | 6e-05 | +| loss | 2.42 | +| n_updates | 14270 | +| policy_gradient_loss | 0.0292 | +| value_loss | 17 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.82e+03 | +| ep_rew_mean | -165 | +| time/ | | +| fps | 345 | +| iterations | 1429 | +| time_elapsed | 14841 | +| total_timesteps | 5121536 | +| train/ | | +| approx_kl | 1.0479625 | +| clip_fraction | 0.091 | +| clip_range | 0.155 | +| entropy_loss | -6.93 | +| explained_variance | 0.322 | +| learning_rate | 6e-05 | +| loss | 0.627 | +| n_updates | 14280 | +| policy_gradient_loss | 0.0308 | +| value_loss | 9.47 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.82e+03 | +| ep_rew_mean | -166 | +| time/ | | +| fps | 345 | +| iterations | 1430 | +| time_elapsed | 14852 | +| total_timesteps | 5125120 | +| train/ | | +| approx_kl | 0.6925157 | +| clip_fraction | 0.029 | +| clip_range | 0.155 | +| entropy_loss | -7.53 | +| explained_variance | 0.112 | +| learning_rate | 6e-05 | +| loss | 13.7 | +| n_updates | 14290 | +| policy_gradient_loss | 0.00924 | +| value_loss | 9.14 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.82e+03 | +| ep_rew_mean | -163 | +| time/ | | +| fps | 345 | +| iterations | 1431 | +| time_elapsed | 14862 | +| total_timesteps | 5128704 | +| train/ | | +| approx_kl | 0.77993995 | +| clip_fraction | 0.0636 | +| clip_range | 0.155 | +| entropy_loss | -7.66 | +| explained_variance | 0.0535 | +| learning_rate | 6e-05 | +| loss | 1.4 | +| n_updates | 14300 | +| policy_gradient_loss | 0.00906 | +| value_loss | 31.2 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -161 | +| time/ | | +| fps | 345 | +| iterations | 1432 | +| time_elapsed | 14871 | +| total_timesteps | 5132288 | +| train/ | | +| approx_kl | 1.6816837 | +| clip_fraction | 0.172 | +| clip_range | 0.155 | +| entropy_loss | -7.37 | +| explained_variance | 0.548 | +| learning_rate | 6e-05 | +| loss | 2.08 | +| n_updates | 14310 | +| policy_gradient_loss | 0.019 | +| value_loss | 15.5 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.83e+03 | +| ep_rew_mean | -159 | +| time/ | | +| fps | 345 | +| iterations | 1433 | +| time_elapsed | 14881 | +| total_timesteps | 5135872 | +| train/ | | +| approx_kl | 1.1632298 | +| clip_fraction | 0.061 | +| clip_range | 0.155 | +| entropy_loss | -7.71 | +| explained_variance | 0.0763 | +| learning_rate | 6e-05 | +| loss | 1.6 | +| n_updates | 14320 | +| policy_gradient_loss | 0.0176 | +| value_loss | 23.7 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 345 | +| iterations | 1434 | +| time_elapsed | 14891 | +| total_timesteps | 5139456 | +| train/ | | +| approx_kl | 0.32584387 | +| clip_fraction | 0.0504 | +| clip_range | 0.155 | +| entropy_loss | -5.42 | +| explained_variance | 0.195 | +| learning_rate | 6e-05 | +| loss | 4.56 | +| n_updates | 14330 | +| policy_gradient_loss | 0.0156 | +| value_loss | 24.6 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -153 | +| time/ | | +| fps | 345 | +| iterations | 1435 | +| time_elapsed | 14901 | +| total_timesteps | 5143040 | +| train/ | | +| approx_kl | 0.8354033 | +| clip_fraction | 0.089 | +| clip_range | 0.155 | +| entropy_loss | -5.06 | +| explained_variance | 0.613 | +| learning_rate | 6e-05 | +| loss | 0.389 | +| n_updates | 14340 | +| policy_gradient_loss | 0.0181 | +| value_loss | 18.4 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -151 | +| time/ | | +| fps | 345 | +| iterations | 1436 | +| time_elapsed | 14911 | +| total_timesteps | 5146624 | +| train/ | | +| approx_kl | 0.69631916 | +| clip_fraction | 0.0537 | +| clip_range | 0.155 | +| entropy_loss | -7.03 | +| explained_variance | 0.334 | +| learning_rate | 6e-05 | +| loss | 0.136 | +| n_updates | 14350 | +| policy_gradient_loss | 0.00392 | +| value_loss | 17.4 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1437 | +| time_elapsed | 14921 | +| total_timesteps | 5150208 | +| train/ | | +| approx_kl | 1.4856218 | +| clip_fraction | 0.0313 | +| clip_range | 0.155 | +| entropy_loss | -8.06 | +| explained_variance | 0.00816 | +| learning_rate | 6e-05 | +| loss | 0.643 | +| n_updates | 14360 | +| policy_gradient_loss | 0.00316 | +| value_loss | 17.5 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 345 | +| iterations | 1438 | +| time_elapsed | 14931 | +| total_timesteps | 5153792 | +| train/ | | +| approx_kl | 0.5406733 | +| clip_fraction | 0.0928 | +| clip_range | 0.155 | +| entropy_loss | -6.54 | +| explained_variance | -0.0248 | +| learning_rate | 6e-05 | +| loss | 13.5 | +| n_updates | 14370 | +| policy_gradient_loss | 0.0215 | +| value_loss | 13.2 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 345 | +| iterations | 1439 | +| time_elapsed | 14942 | +| total_timesteps | 5157376 | +| train/ | | +| approx_kl | 0.5624845 | +| clip_fraction | 0.123 | +| clip_range | 0.155 | +| entropy_loss | -6.48 | +| explained_variance | 0.0423 | +| learning_rate | 6e-05 | +| loss | 8.24 | +| n_updates | 14380 | +| policy_gradient_loss | 0.0205 | +| value_loss | 14.8 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 345 | +| iterations | 1440 | +| time_elapsed | 14952 | +| total_timesteps | 5160960 | +| train/ | | +| approx_kl | 2.1709259 | +| clip_fraction | 0.0372 | +| clip_range | 0.155 | +| entropy_loss | -7.21 | +| explained_variance | 0.304 | +| learning_rate | 6e-05 | +| loss | 15.6 | +| n_updates | 14390 | +| policy_gradient_loss | 0.000438 | +| value_loss | 44.4 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -149 | +| time/ | | +| fps | 345 | +| iterations | 1441 | +| time_elapsed | 14962 | +| total_timesteps | 5164544 | +| train/ | | +| approx_kl | 0.09718137 | +| clip_fraction | 0.00826 | +| clip_range | 0.155 | +| entropy_loss | -6.91 | +| explained_variance | 0.425 | +| learning_rate | 6e-05 | +| loss | 11.3 | +| n_updates | 14400 | +| policy_gradient_loss | 0.000572 | +| value_loss | 41.6 | +---------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.84e+03 | +| ep_rew_mean | -149 | +| time/ | | +| fps | 345 | +| iterations | 1442 | +| time_elapsed | 14973 | +| total_timesteps | 5168128 | +| train/ | | +| approx_kl | 0.7057585 | +| clip_fraction | 0.0836 | +| clip_range | 0.155 | +| entropy_loss | -6.13 | +| explained_variance | 0.0684 | +| learning_rate | 6e-05 | +| loss | 3.82 | +| n_updates | 14410 | +| policy_gradient_loss | 0.0151 | +| value_loss | 20.8 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -152 | +| time/ | | +| fps | 345 | +| iterations | 1443 | +| time_elapsed | 14982 | +| total_timesteps | 5171712 | +| train/ | | +| approx_kl | 2.5924575 | +| clip_fraction | 0.0532 | +| clip_range | 0.155 | +| entropy_loss | -6.73 | +| explained_variance | 0.576 | +| learning_rate | 6e-05 | +| loss | 38.7 | +| n_updates | 14420 | +| policy_gradient_loss | 0.00743 | +| value_loss | 18 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 345 | +| iterations | 1444 | +| time_elapsed | 14992 | +| total_timesteps | 5175296 | +| train/ | | +| approx_kl | 1.7867857 | +| clip_fraction | 0.0823 | +| clip_range | 0.155 | +| entropy_loss | -5.59 | +| explained_variance | 0.726 | +| learning_rate | 6e-05 | +| loss | 3.54 | +| n_updates | 14430 | +| policy_gradient_loss | 0.021 | +| value_loss | 25.4 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -147 | +| time/ | | +| fps | 345 | +| iterations | 1445 | +| time_elapsed | 15002 | +| total_timesteps | 5178880 | +| train/ | | +| approx_kl | 1.024216 | +| clip_fraction | 0.102 | +| clip_range | 0.155 | +| entropy_loss | -4.76 | +| explained_variance | 0.0542 | +| learning_rate | 6e-05 | +| loss | 26.5 | +| n_updates | 14440 | +| policy_gradient_loss | 0.0144 | +| value_loss | 27.9 | +-------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 345 | +| iterations | 1446 | +| time_elapsed | 15012 | +| total_timesteps | 5182464 | +| train/ | | +| approx_kl | 0.72534424 | +| clip_fraction | 0.0754 | +| clip_range | 0.155 | +| entropy_loss | -7.07 | +| explained_variance | 0.204 | +| learning_rate | 6e-05 | +| loss | 7.06 | +| n_updates | 14450 | +| policy_gradient_loss | 0.0103 | +| value_loss | 15.6 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 345 | +| iterations | 1447 | +| time_elapsed | 15022 | +| total_timesteps | 5186048 | +| train/ | | +| approx_kl | 0.4955955 | +| clip_fraction | 0.0185 | +| clip_range | 0.155 | +| entropy_loss | -7.68 | +| explained_variance | 0.298 | +| learning_rate | 6e-05 | +| loss | 17.6 | +| n_updates | 14460 | +| policy_gradient_loss | 0.00142 | +| value_loss | 11.7 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 345 | +| iterations | 1448 | +| time_elapsed | 15031 | +| total_timesteps | 5189632 | +| train/ | | +| approx_kl | 0.3708353 | +| clip_fraction | 0.0448 | +| clip_range | 0.155 | +| entropy_loss | -7.85 | +| explained_variance | 0.0163 | +| learning_rate | 6e-05 | +| loss | 3.81 | +| n_updates | 14470 | +| policy_gradient_loss | 0.00994 | +| value_loss | 5.31 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 345 | +| iterations | 1449 | +| time_elapsed | 15042 | +| total_timesteps | 5193216 | +| train/ | | +| approx_kl | 0.02968044 | +| clip_fraction | 0.00619 | +| clip_range | 0.155 | +| entropy_loss | -8.26 | +| explained_variance | -0.00225 | +| learning_rate | 6e-05 | +| loss | 3.44 | +| n_updates | 14480 | +| policy_gradient_loss | 0.0027 | +| value_loss | 7.75 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -144 | +| time/ | | +| fps | 345 | +| iterations | 1450 | +| time_elapsed | 15052 | +| total_timesteps | 5196800 | +| train/ | | +| approx_kl | 2.5224452 | +| clip_fraction | 0.109 | +| clip_range | 0.155 | +| entropy_loss | -6.06 | +| explained_variance | 0.131 | +| learning_rate | 6e-05 | +| loss | 1.33 | +| n_updates | 14490 | +| policy_gradient_loss | 0.0237 | +| value_loss | 15 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -148 | +| time/ | | +| fps | 345 | +| iterations | 1451 | +| time_elapsed | 15063 | +| total_timesteps | 5200384 | +| train/ | | +| approx_kl | 0.083875604 | +| clip_fraction | 0.0242 | +| clip_range | 0.155 | +| entropy_loss | -8.25 | +| explained_variance | -0.00703 | +| learning_rate | 6e-05 | +| loss | 2.27 | +| n_updates | 14500 | +| policy_gradient_loss | 0.0159 | +| value_loss | 15.8 | +----------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -145 | +| time/ | | +| fps | 345 | +| iterations | 1452 | +| time_elapsed | 15074 | +| total_timesteps | 5203968 | +| train/ | | +| approx_kl | 0.5829459 | +| clip_fraction | 0.0175 | +| clip_range | 0.155 | +| entropy_loss | -7.66 | +| explained_variance | 0.0811 | +| learning_rate | 6e-05 | +| loss | 0.811 | +| n_updates | 14510 | +| policy_gradient_loss | 0.00523 | +| value_loss | 9.46 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -141 | +| time/ | | +| fps | 345 | +| iterations | 1453 | +| time_elapsed | 15084 | +| total_timesteps | 5207552 | +| train/ | | +| approx_kl | 2.2508388 | +| clip_fraction | 0.179 | +| clip_range | 0.155 | +| entropy_loss | -5.41 | +| explained_variance | 0.216 | +| learning_rate | 6e-05 | +| loss | 14.9 | +| n_updates | 14520 | +| policy_gradient_loss | 0.0232 | +| value_loss | 12.5 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1454 | +| time_elapsed | 15094 | +| total_timesteps | 5211136 | +| train/ | | +| approx_kl | 0.06257143 | +| clip_fraction | 0.0172 | +| clip_range | 0.155 | +| entropy_loss | -7.79 | +| explained_variance | 0.0527 | +| learning_rate | 6e-05 | +| loss | 9.86 | +| n_updates | 14530 | +| policy_gradient_loss | 0.00264 | +| value_loss | 18.1 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -140 | +| time/ | | +| fps | 345 | +| iterations | 1455 | +| time_elapsed | 15105 | +| total_timesteps | 5214720 | +| train/ | | +| approx_kl | 1.3155754 | +| clip_fraction | 0.0567 | +| clip_range | 0.155 | +| entropy_loss | -4.35 | +| explained_variance | 0.413 | +| learning_rate | 6e-05 | +| loss | 10.7 | +| n_updates | 14540 | +| policy_gradient_loss | 0.0301 | +| value_loss | 13.9 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1456 | +| time_elapsed | 15116 | +| total_timesteps | 5218304 | +| train/ | | +| approx_kl | 0.0993466 | +| clip_fraction | 0.0283 | +| clip_range | 0.155 | +| entropy_loss | -7.73 | +| explained_variance | 0.11 | +| learning_rate | 6e-05 | +| loss | 0.094 | +| n_updates | 14550 | +| policy_gradient_loss | 0.00574 | +| value_loss | 20.3 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1457 | +| time_elapsed | 15126 | +| total_timesteps | 5221888 | +| train/ | | +| approx_kl | 0.028285917 | +| clip_fraction | 0.00145 | +| clip_range | 0.155 | +| entropy_loss | -8.08 | +| explained_variance | 0.0919 | +| learning_rate | 6e-05 | +| loss | 8.77 | +| n_updates | 14560 | +| policy_gradient_loss | -0.000374 | +| value_loss | 13.2 | +----------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -137 | +| time/ | | +| fps | 345 | +| iterations | 1458 | +| time_elapsed | 15136 | +| total_timesteps | 5225472 | +| train/ | | +| approx_kl | 2.1230047 | +| clip_fraction | 0.0482 | +| clip_range | 0.155 | +| entropy_loss | -7.67 | +| explained_variance | 0.00806 | +| learning_rate | 6e-05 | +| loss | 3.27 | +| n_updates | 14570 | +| policy_gradient_loss | 0.00839 | +| value_loss | 15.7 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -135 | +| time/ | | +| fps | 345 | +| iterations | 1459 | +| time_elapsed | 15146 | +| total_timesteps | 5229056 | +| train/ | | +| approx_kl | 2.2068942 | +| clip_fraction | 0.0184 | +| clip_range | 0.155 | +| entropy_loss | -7.68 | +| explained_variance | 0.0447 | +| learning_rate | 6e-05 | +| loss | 3.15 | +| n_updates | 14580 | +| policy_gradient_loss | -0.000974 | +| value_loss | 36 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -135 | +| time/ | | +| fps | 345 | +| iterations | 1460 | +| time_elapsed | 15156 | +| total_timesteps | 5232640 | +| train/ | | +| approx_kl | 0.8723434 | +| clip_fraction | 0.063 | +| clip_range | 0.155 | +| entropy_loss | -4.91 | +| explained_variance | 0.502 | +| learning_rate | 6e-05 | +| loss | 3.82 | +| n_updates | 14590 | +| policy_gradient_loss | 0.00104 | +| value_loss | 34.5 | +--------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -134 | +| time/ | | +| fps | 345 | +| iterations | 1461 | +| time_elapsed | 15167 | +| total_timesteps | 5236224 | +| train/ | | +| approx_kl | 1.397867 | +| clip_fraction | 0.0527 | +| clip_range | 0.155 | +| entropy_loss | -7.02 | +| explained_variance | 0.0682 | +| learning_rate | 6e-05 | +| loss | 8.23 | +| n_updates | 14600 | +| policy_gradient_loss | 0.00342 | +| value_loss | 23.7 | +-------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1462 | +| time_elapsed | 15178 | +| total_timesteps | 5239808 | +| train/ | | +| approx_kl | 0.63009447 | +| clip_fraction | 0.0352 | +| clip_range | 0.155 | +| entropy_loss | -7.51 | +| explained_variance | 0.102 | +| learning_rate | 6e-05 | +| loss | 3.23 | +| n_updates | 14610 | +| policy_gradient_loss | 0.00537 | +| value_loss | 10.1 | +---------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1463 | +| time_elapsed | 15189 | +| total_timesteps | 5243392 | +| train/ | | +| approx_kl | 5.381866 | +| clip_fraction | 0.0496 | +| clip_range | 0.155 | +| entropy_loss | -3.49 | +| explained_variance | 0.508 | +| learning_rate | 6e-05 | +| loss | 0.885 | +| n_updates | 14620 | +| policy_gradient_loss | 0.00832 | +| value_loss | 24.6 | +-------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.85e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 345 | +| iterations | 1464 | +| time_elapsed | 15199 | +| total_timesteps | 5246976 | +| train/ | | +| approx_kl | 1.6812872 | +| clip_fraction | 0.0434 | +| clip_range | 0.155 | +| entropy_loss | -6.56 | +| explained_variance | 0.591 | +| learning_rate | 6e-05 | +| loss | 62.4 | +| n_updates | 14630 | +| policy_gradient_loss | 0.000363 | +| value_loss | 22.7 | +--------------------------------------- + +Current state: Champion.Level10.ChunLiVsVega +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 345 | +| iterations | 1465 | +| time_elapsed | 15209 | +| total_timesteps | 5250560 | +| train/ | | +| approx_kl | 0.662723 | +| clip_fraction | 0.116 | +| clip_range | 0.155 | +| entropy_loss | -7.29 | +| explained_variance | 0.0847 | +| learning_rate | 6e-05 | +| loss | 3.81 | +| n_updates | 14640 | +| policy_gradient_loss | 0.0177 | +| value_loss | 15.1 | +-------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -133 | +| time/ | | +| fps | 345 | +| iterations | 1466 | +| time_elapsed | 15219 | +| total_timesteps | 5254144 | +| train/ | | +| approx_kl | 1.3605807 | +| clip_fraction | 0.0423 | +| clip_range | 0.155 | +| entropy_loss | -6.48 | +| explained_variance | 0.194 | +| learning_rate | 6e-05 | +| loss | 0.11 | +| n_updates | 14650 | +| policy_gradient_loss | 0.00472 | +| value_loss | 7.16 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 345 | +| iterations | 1467 | +| time_elapsed | 15229 | +| total_timesteps | 5257728 | +| train/ | | +| approx_kl | 1.0328138 | +| clip_fraction | 0.0921 | +| clip_range | 0.155 | +| entropy_loss | -7.7 | +| explained_variance | -0.0128 | +| learning_rate | 6e-05 | +| loss | 5.2 | +| n_updates | 14660 | +| policy_gradient_loss | 0.0458 | +| value_loss | 25 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -127 | +| time/ | | +| fps | 345 | +| iterations | 1468 | +| time_elapsed | 15239 | +| total_timesteps | 5261312 | +| train/ | | +| approx_kl | 6.281489 | +| clip_fraction | 0.0757 | +| clip_range | 0.155 | +| entropy_loss | -6.72 | +| explained_variance | 0.0103 | +| learning_rate | 6e-05 | +| loss | 0.205 | +| n_updates | 14670 | +| policy_gradient_loss | 0.00543 | +| value_loss | 16.1 | +-------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -128 | +| time/ | | +| fps | 345 | +| iterations | 1469 | +| time_elapsed | 15249 | +| total_timesteps | 5264896 | +| train/ | | +| approx_kl | 2.3276184 | +| clip_fraction | 0.176 | +| clip_range | 0.155 | +| entropy_loss | -5.21 | +| explained_variance | 0.115 | +| learning_rate | 6e-05 | +| loss | 3.38 | +| n_updates | 14680 | +| policy_gradient_loss | 0.0355 | +| value_loss | 11.8 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.9e+03 | +| ep_rew_mean | -126 | +| time/ | | +| fps | 345 | +| iterations | 1470 | +| time_elapsed | 15259 | +| total_timesteps | 5268480 | +| train/ | | +| approx_kl | 2.2806563 | +| clip_fraction | 0.139 | +| clip_range | 0.155 | +| entropy_loss | -5.54 | +| explained_variance | 0.243 | +| learning_rate | 6e-05 | +| loss | 11.2 | +| n_updates | 14690 | +| policy_gradient_loss | 0.00997 | +| value_loss | 13.8 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 345 | +| iterations | 1471 | +| time_elapsed | 15269 | +| total_timesteps | 5272064 | +| train/ | | +| approx_kl | 3.74225 | +| clip_fraction | 0.109 | +| clip_range | 0.155 | +| entropy_loss | -5.18 | +| explained_variance | 0.592 | +| learning_rate | 6e-05 | +| loss | 9.44 | +| n_updates | 14700 | +| policy_gradient_loss | 0.00691 | +| value_loss | 22.6 | +-------------------------------------- + +Current state: Champion.Level11.ChunLiVsSagat +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 345 | +| iterations | 1472 | +| time_elapsed | 15279 | +| total_timesteps | 5275648 | +| train/ | | +| approx_kl | 1.3296187 | +| clip_fraction | 0.0622 | +| clip_range | 0.155 | +| entropy_loss | -6.85 | +| explained_variance | 0.158 | +| learning_rate | 6e-05 | +| loss | 3 | +| n_updates | 14710 | +| policy_gradient_loss | 0.0224 | +| value_loss | 11.5 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -127 | +| time/ | | +| fps | 345 | +| iterations | 1473 | +| time_elapsed | 15290 | +| total_timesteps | 5279232 | +| train/ | | +| approx_kl | 1.2698233 | +| clip_fraction | 0.0159 | +| clip_range | 0.155 | +| entropy_loss | -8.21 | +| explained_variance | 7.59e-05 | +| learning_rate | 6e-05 | +| loss | 246 | +| n_updates | 14720 | +| policy_gradient_loss | 0.00198 | +| value_loss | 177 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -128 | +| time/ | | +| fps | 345 | +| iterations | 1474 | +| time_elapsed | 15301 | +| total_timesteps | 5282816 | +| train/ | | +| approx_kl | 3.9318326 | +| clip_fraction | 0.0648 | +| clip_range | 0.155 | +| entropy_loss | -1.9 | +| explained_variance | 0.254 | +| learning_rate | 6e-05 | +| loss | 8.07 | +| n_updates | 14730 | +| policy_gradient_loss | 0.00314 | +| value_loss | 65.8 | +--------------------------------------- + +Current state: Champion.Level6.ChunLiVsRyu +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.86e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 345 | +| iterations | 1475 | +| time_elapsed | 15311 | +| total_timesteps | 5286400 | +| train/ | | +| approx_kl | 0.69109696 | +| clip_fraction | 0.0826 | +| clip_range | 0.155 | +| entropy_loss | -6.41 | +| explained_variance | 0.643 | +| learning_rate | 6e-05 | +| loss | 0.608 | +| n_updates | 14740 | +| policy_gradient_loss | 0.0487 | +| value_loss | 6.94 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.87e+03 | +| ep_rew_mean | -128 | +| time/ | | +| fps | 345 | +| iterations | 1476 | +| time_elapsed | 15321 | +| total_timesteps | 5289984 | +| train/ | | +| approx_kl | 2.5481944 | +| clip_fraction | 0.0385 | +| clip_range | 0.155 | +| entropy_loss | -7.24 | +| explained_variance | 0.139 | +| learning_rate | 6e-05 | +| loss | -0.047 | +| n_updates | 14750 | +| policy_gradient_loss | 1.68 | +| value_loss | 6.52 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.88e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 345 | +| iterations | 1477 | +| time_elapsed | 15331 | +| total_timesteps | 5293568 | +| train/ | | +| approx_kl | 2.8009365 | +| clip_fraction | 0.114 | +| clip_range | 0.155 | +| entropy_loss | -5.8 | +| explained_variance | 0.284 | +| learning_rate | 6e-05 | +| loss | 45.2 | +| n_updates | 14760 | +| policy_gradient_loss | 0.0192 | +| value_loss | 22 | +--------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.89e+03 | +| ep_rew_mean | -124 | +| time/ | | +| fps | 345 | +| iterations | 1478 | +| time_elapsed | 15341 | +| total_timesteps | 5297152 | +| train/ | | +| approx_kl | 1.3075736 | +| clip_fraction | 0.061 | +| clip_range | 0.155 | +| entropy_loss | -6.69 | +| explained_variance | 0.234 | +| learning_rate | 6e-05 | +| loss | 0.943 | +| n_updates | 14770 | +| policy_gradient_loss | 0.00463 | +| value_loss | 24.4 | +--------------------------------------- + +Current state: Champion.Level12.ChunLiVsBison +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -120 | +| time/ | | +| fps | 345 | +| iterations | 1479 | +| time_elapsed | 15351 | +| total_timesteps | 5300736 | +| train/ | | +| approx_kl | 1.4779198 | +| clip_fraction | 0.0879 | +| clip_range | 0.155 | +| entropy_loss | -7.38 | +| explained_variance | -0.0132 | +| learning_rate | 6e-05 | +| loss | 0.467 | +| n_updates | 14780 | +| policy_gradient_loss | 0.0231 | +| value_loss | 13.3 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1480 | +| time_elapsed | 15361 | +| total_timesteps | 5304320 | +| train/ | | +| approx_kl | 1.9090964 | +| clip_fraction | 0.0703 | +| clip_range | 0.155 | +| entropy_loss | -6.41 | +| explained_variance | 0.232 | +| learning_rate | 6e-05 | +| loss | 0.427 | +| n_updates | 14790 | +| policy_gradient_loss | 0.0253 | +| value_loss | 8.96 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 345 | +| iterations | 1481 | +| time_elapsed | 15370 | +| total_timesteps | 5307904 | +| train/ | | +| approx_kl | 1.4184047 | +| clip_fraction | 0.0764 | +| clip_range | 0.155 | +| entropy_loss | -4.07 | +| explained_variance | 0.68 | +| learning_rate | 6e-05 | +| loss | 18.1 | +| n_updates | 14800 | +| policy_gradient_loss | 0.00515 | +| value_loss | 15 | +--------------------------------------- + +Current state: Champion.Level4.ChunLiVsZangief +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -116 | +| time/ | | +| fps | 345 | +| iterations | 1482 | +| time_elapsed | 15380 | +| total_timesteps | 5311488 | +| train/ | | +| approx_kl | 1.4483336 | +| clip_fraction | 0.0834 | +| clip_range | 0.155 | +| entropy_loss | -4.6 | +| explained_variance | 0.468 | +| learning_rate | 6e-05 | +| loss | 2.56 | +| n_updates | 14810 | +| policy_gradient_loss | 0.0102 | +| value_loss | 10.5 | +--------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 345 | +| iterations | 1483 | +| time_elapsed | 15390 | +| total_timesteps | 5315072 | +| train/ | | +| approx_kl | 0.30256054 | +| clip_fraction | 0.0855 | +| clip_range | 0.155 | +| entropy_loss | -8.05 | +| explained_variance | 0.0391 | +| learning_rate | 6e-05 | +| loss | 6.96 | +| n_updates | 14820 | +| policy_gradient_loss | 0.0194 | +| value_loss | 11.5 | +---------------------------------------- + +Current state: Champion.Level1.ChunLiVsGuile +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 345 | +| iterations | 1484 | +| time_elapsed | 15400 | +| total_timesteps | 5318656 | +| train/ | | +| approx_kl | 0.70303136 | +| clip_fraction | 0.0391 | +| clip_range | 0.155 | +| entropy_loss | -6.1 | +| explained_variance | 0.35 | +| learning_rate | 6e-05 | +| loss | 1.72 | +| n_updates | 14830 | +| policy_gradient_loss | 0.00186 | +| value_loss | 7.43 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 345 | +| iterations | 1485 | +| time_elapsed | 15411 | +| total_timesteps | 5322240 | +| train/ | | +| approx_kl | 3.0615518 | +| clip_fraction | 0.0802 | +| clip_range | 0.155 | +| entropy_loss | -6.38 | +| explained_variance | 0.0648 | +| learning_rate | 6e-05 | +| loss | 3.72 | +| n_updates | 14840 | +| policy_gradient_loss | 0.0132 | +| value_loss | 17.4 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +----------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 345 | +| iterations | 1486 | +| time_elapsed | 15422 | +| total_timesteps | 5325824 | +| train/ | | +| approx_kl | 0.121159054 | +| clip_fraction | 0.0225 | +| clip_range | 0.155 | +| entropy_loss | -8.17 | +| explained_variance | -0.00174 | +| learning_rate | 6e-05 | +| loss | 10.1 | +| n_updates | 14850 | +| policy_gradient_loss | 0.0171 | +| value_loss | 7.69 | +----------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.94e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 345 | +| iterations | 1487 | +| time_elapsed | 15433 | +| total_timesteps | 5329408 | +| train/ | | +| approx_kl | 5.2687364 | +| clip_fraction | 0.108 | +| clip_range | 0.155 | +| entropy_loss | -5.69 | +| explained_variance | 0.0996 | +| learning_rate | 6e-05 | +| loss | 1.12 | +| n_updates | 14860 | +| policy_gradient_loss | 0.01 | +| value_loss | 19.5 | +--------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.95e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 345 | +| iterations | 1488 | +| time_elapsed | 15443 | +| total_timesteps | 5332992 | +| train/ | | +| approx_kl | 0.69310933 | +| clip_fraction | 0.0248 | +| clip_range | 0.155 | +| entropy_loss | -7.77 | +| explained_variance | 0.0132 | +| learning_rate | 6e-05 | +| loss | 90.2 | +| n_updates | 14870 | +| policy_gradient_loss | 0.00212 | +| value_loss | 30 | +---------------------------------------- + +Current state: Champion.Level3.ChunLiVsChunLi +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.93e+03 | +| ep_rew_mean | -116 | +| time/ | | +| fps | 345 | +| iterations | 1489 | +| time_elapsed | 15453 | +| total_timesteps | 5336576 | +| train/ | | +| approx_kl | 1.6383746 | +| clip_fraction | 0.0419 | +| clip_range | 0.155 | +| entropy_loss | -8.03 | +| explained_variance | -0.0422 | +| learning_rate | 6e-05 | +| loss | 2.53 | +| n_updates | 14880 | +| policy_gradient_loss | 0.0064 | +| value_loss | 15.6 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.92e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 345 | +| iterations | 1490 | +| time_elapsed | 15464 | +| total_timesteps | 5340160 | +| train/ | | +| approx_kl | 0.50850654 | +| clip_fraction | 0.0598 | +| clip_range | 0.155 | +| entropy_loss | -7.88 | +| explained_variance | 0.0201 | +| learning_rate | 6e-05 | +| loss | 16.6 | +| n_updates | 14890 | +| policy_gradient_loss | 0.0126 | +| value_loss | 28.4 | +---------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +-------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1491 | +| time_elapsed | 15475 | +| total_timesteps | 5343744 | +| train/ | | +| approx_kl | 6.179366 | +| clip_fraction | 0.104 | +| clip_range | 0.155 | +| entropy_loss | -7.5 | +| explained_variance | -0.0172 | +| learning_rate | 6e-05 | +| loss | 0.908 | +| n_updates | 14900 | +| policy_gradient_loss | 0.0157 | +| value_loss | 29.3 | +-------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1492 | +| time_elapsed | 15486 | +| total_timesteps | 5347328 | +| train/ | | +| approx_kl | 0.24448892 | +| clip_fraction | 0.0481 | +| clip_range | 0.155 | +| entropy_loss | -7.52 | +| explained_variance | -0.0218 | +| learning_rate | 6e-05 | +| loss | 4.31 | +| n_updates | 14910 | +| policy_gradient_loss | 0.0364 | +| value_loss | 9.42 | +---------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.91e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1493 | +| time_elapsed | 15495 | +| total_timesteps | 5350912 | +| train/ | | +| approx_kl | 1.1701069 | +| clip_fraction | 0.0626 | +| clip_range | 0.155 | +| entropy_loss | -6.08 | +| explained_variance | 0.181 | +| learning_rate | 6e-05 | +| loss | 2.23 | +| n_updates | 14920 | +| policy_gradient_loss | 0.00368 | +| value_loss | 4.42 | +--------------------------------------- + +Current state: Champion.Level8.ChunLiVsBlanka +--------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -121 | +| time/ | | +| fps | 345 | +| iterations | 1494 | +| time_elapsed | 15505 | +| total_timesteps | 5354496 | +| train/ | | +| approx_kl | 1.1823349 | +| clip_fraction | 0.0355 | +| clip_range | 0.155 | +| entropy_loss | -6.65 | +| explained_variance | 0.103 | +| learning_rate | 6e-05 | +| loss | 5.53 | +| n_updates | 14930 | +| policy_gradient_loss | 0.00474 | +| value_loss | 3.01 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 1.99e+03 | +| ep_rew_mean | -121 | +| time/ | | +| fps | 345 | +| iterations | 1495 | +| time_elapsed | 15515 | +| total_timesteps | 5358080 | +| train/ | | +| approx_kl | 0.17688313 | +| clip_fraction | 0.0545 | +| clip_range | 0.155 | +| entropy_loss | -5.68 | +| explained_variance | 0.137 | +| learning_rate | 6e-05 | +| loss | 0.713 | +| n_updates | 14940 | +| policy_gradient_loss | 0.0292 | +| value_loss | 2.44 | +---------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1496 | +| time_elapsed | 15526 | +| total_timesteps | 5361664 | +| train/ | | +| approx_kl | 0.9058685 | +| clip_fraction | 0.0271 | +| clip_range | 0.155 | +| entropy_loss | -7.94 | +| explained_variance | -0.00334 | +| learning_rate | 6e-05 | +| loss | 1.34 | +| n_updates | 14950 | +| policy_gradient_loss | 0.0123 | +| value_loss | 6.05 | +--------------------------------------- + +Current state: Champion.Level7.ChunLiVsEHonda +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.05e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 345 | +| iterations | 1497 | +| time_elapsed | 15536 | +| total_timesteps | 5365248 | +| train/ | | +| approx_kl | 0.8243508 | +| clip_fraction | 0.0875 | +| clip_range | 0.155 | +| entropy_loss | -5.34 | +| explained_variance | 0.0344 | +| learning_rate | 6e-05 | +| loss | -0.0197 | +| n_updates | 14960 | +| policy_gradient_loss | 0.0178 | +| value_loss | 3.86 | +--------------------------------------- + +Current state: Champion.Level5.ChunLiVsDhalsim +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 345 | +| iterations | 1498 | +| time_elapsed | 15547 | +| total_timesteps | 5368832 | +| train/ | | +| approx_kl | 0.52059186 | +| clip_fraction | 0.0796 | +| clip_range | 0.155 | +| entropy_loss | -5.76 | +| explained_variance | 0.12 | +| learning_rate | 6e-05 | +| loss | 1.54 | +| n_updates | 14970 | +| policy_gradient_loss | 0.0177 | +| value_loss | 3.81 | +---------------------------------------- + +Current state: Champion.Level9.ChunLiVsBalrog +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.13e+03 | +| ep_rew_mean | -113 | +| time/ | | +| fps | 345 | +| iterations | 1499 | +| time_elapsed | 15557 | +| total_timesteps | 5372416 | +| train/ | | +| approx_kl | 1.6673042 | +| clip_fraction | 0.0729 | +| clip_range | 0.155 | +| entropy_loss | -7.44 | +| explained_variance | 0.0163 | +| learning_rate | 6e-05 | +| loss | 0.749 | +| n_updates | 14980 | +| policy_gradient_loss | 0.0126 | +| value_loss | 6.92 | +--------------------------------------- + +Current state: Champion.Level2.ChunLiVsKen +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.16e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 345 | +| iterations | 1500 | +| time_elapsed | 15568 | +| total_timesteps | 5376000 | +| train/ | | +| approx_kl | 1.0374296 | +| clip_fraction | 0.0323 | +| clip_range | 0.155 | +| entropy_loss | -8 | +| explained_variance | 0.0126 | +| learning_rate | 6e-05 | +| loss | 8.36 | +| n_updates | 14990 | +| policy_gradient_loss | 0.00436 | +| value_loss | 10.5 | +--------------------------------------- \ No newline at end of file diff --git a/000_image_stack_ram_based_reward/trained_models_level_1/training_logs.txt b/000_image_stack_ram_based_reward/trained_models_level_1/training_logs.txt new file mode 100644 index 0000000..90266c6 --- /dev/null +++ b/000_image_stack_ram_based_reward/trained_models_level_1/training_logs.txt @@ -0,0 +1,3144 @@ +(StreetFighterAI) PS C:\Users\unitec\Documents\AIProjects\street-fighter-ai\000_image_stack_ram_based_reward> python .\train.py +Using cuda device +Wrapping the env in a DummyVecEnv. +Wrapping the env in a VecTransposeImage. +Logging to logs/PPO_30 +--------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -90.4 | +| time/ | | +| fps | 514 | +| iterations | 1 | +| time_elapsed | 69 | +| total_timesteps | 35840 | +--------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.57e+03 | +| ep_rew_mean | -89.4 | +| time/ | | +| fps | 397 | +| iterations | 2 | +| time_elapsed | 180 | +| total_timesteps | 71680 | +| train/ | | +| approx_kl | 0.0050133066 | +| clip_fraction | 0.0823 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | -4.42e-05 | +| learning_rate | 6e-05 | +| loss | 2.84 | +| n_updates | 10 | +| policy_gradient_loss | -0.0041 | +| value_loss | 13.8 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.61e+03 | +| ep_rew_mean | -85.8 | +| time/ | | +| fps | 364 | +| iterations | 3 | +| time_elapsed | 295 | +| total_timesteps | 107520 | +| train/ | | +| approx_kl | 0.005845706 | +| clip_fraction | 0.0964 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.0243 | +| learning_rate | 6e-05 | +| loss | 6.21 | +| n_updates | 20 | +| policy_gradient_loss | -0.00668 | +| value_loss | 9.59 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.56e+03 | +| ep_rew_mean | -86.6 | +| time/ | | +| fps | 351 | +| iterations | 4 | +| time_elapsed | 407 | +| total_timesteps | 143360 | +| train/ | | +| approx_kl | 0.007079247 | +| clip_fraction | 0.12 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.0379 | +| learning_rate | 6e-05 | +| loss | 2.52 | +| n_updates | 30 | +| policy_gradient_loss | -0.00804 | +| value_loss | 10.3 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.55e+03 | +| ep_rew_mean | -91.4 | +| time/ | | +| fps | 345 | +| iterations | 5 | +| time_elapsed | 518 | +| total_timesteps | 179200 | +| train/ | | +| approx_kl | 0.008851709 | +| clip_fraction | 0.157 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.105 | +| learning_rate | 6e-05 | +| loss | 0.579 | +| n_updates | 40 | +| policy_gradient_loss | -0.00843 | +| value_loss | 9.87 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.54e+03 | +| ep_rew_mean | -93.8 | +| time/ | | +| fps | 342 | +| iterations | 6 | +| time_elapsed | 628 | +| total_timesteps | 215040 | +| train/ | | +| approx_kl | 0.0116657885 | +| clip_fraction | 0.204 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.0882 | +| learning_rate | 6e-05 | +| loss | 0.201 | +| n_updates | 50 | +| policy_gradient_loss | -0.00743 | +| value_loss | 14.4 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -97.2 | +| time/ | | +| fps | 339 | +| iterations | 7 | +| time_elapsed | 738 | +| total_timesteps | 250880 | +| train/ | | +| approx_kl | 0.014411392 | +| clip_fraction | 0.25 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.148 | +| learning_rate | 6e-05 | +| loss | 2.61 | +| n_updates | 60 | +| policy_gradient_loss | -0.00736 | +| value_loss | 7.66 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -109 | +| time/ | | +| fps | 337 | +| iterations | 8 | +| time_elapsed | 849 | +| total_timesteps | 286720 | +| train/ | | +| approx_kl | 0.01602269 | +| clip_fraction | 0.264 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.112 | +| learning_rate | 6e-05 | +| loss | 0.436 | +| n_updates | 70 | +| policy_gradient_loss | -0.00533 | +| value_loss | 8.72 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.49e+03 | +| ep_rew_mean | -72.8 | +| time/ | | +| fps | 335 | +| iterations | 9 | +| time_elapsed | 960 | +| total_timesteps | 322560 | +| train/ | | +| approx_kl | 0.019153824 | +| clip_fraction | 0.286 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.0806 | +| learning_rate | 6e-05 | +| loss | 0.891 | +| n_updates | 80 | +| policy_gradient_loss | -0.00355 | +| value_loss | 11.8 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.46e+03 | +| ep_rew_mean | -71.8 | +| time/ | | +| fps | 333 | +| iterations | 10 | +| time_elapsed | 1074 | +| total_timesteps | 358400 | +| train/ | | +| approx_kl | 0.025319224 | +| clip_fraction | 0.332 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.00587 | +| learning_rate | 6e-05 | +| loss | 7.2e+03 | +| n_updates | 90 | +| policy_gradient_loss | 0.00131 | +| value_loss | 607 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.48e+03 | +| ep_rew_mean | -75.9 | +| time/ | | +| fps | 331 | +| iterations | 11 | +| time_elapsed | 1190 | +| total_timesteps | 394240 | +| train/ | | +| approx_kl | 0.022422956 | +| clip_fraction | 0.312 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.19 | +| learning_rate | 6e-05 | +| loss | 0.33 | +| n_updates | 100 | +| policy_gradient_loss | 0.00232 | +| value_loss | 7.57 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.46e+03 | +| ep_rew_mean | -80.5 | +| time/ | | +| fps | 330 | +| iterations | 12 | +| time_elapsed | 1300 | +| total_timesteps | 430080 | +| train/ | | +| approx_kl | 0.025700385 | +| clip_fraction | 0.321 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.136 | +| learning_rate | 6e-05 | +| loss | 2.56 | +| n_updates | 110 | +| policy_gradient_loss | 0.00435 | +| value_loss | 11.3 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.51e+03 | +| ep_rew_mean | -81.5 | +| time/ | | +| fps | 329 | +| iterations | 13 | +| time_elapsed | 1413 | +| total_timesteps | 465920 | +| train/ | | +| approx_kl | 0.023794638 | +| clip_fraction | 0.282 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.131 | +| learning_rate | 6e-05 | +| loss | 4.77 | +| n_updates | 120 | +| policy_gradient_loss | 0.00461 | +| value_loss | 9.29 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -70.6 | +| time/ | | +| fps | 328 | +| iterations | 14 | +| time_elapsed | 1528 | +| total_timesteps | 501760 | +| train/ | | +| approx_kl | 0.025345555 | +| clip_fraction | 0.279 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.0755 | +| learning_rate | 6e-05 | +| loss | 13.7 | +| n_updates | 130 | +| policy_gradient_loss | 0.00785 | +| value_loss | 8.64 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -51.6 | +| time/ | | +| fps | 328 | +| iterations | 15 | +| time_elapsed | 1635 | +| total_timesteps | 537600 | +| train/ | | +| approx_kl | 0.024148518 | +| clip_fraction | 0.268 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.105 | +| learning_rate | 6e-05 | +| loss | 0.792 | +| n_updates | 140 | +| policy_gradient_loss | 0.00487 | +| value_loss | 7.73 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.46e+03 | +| ep_rew_mean | -91.5 | +| time/ | | +| fps | 328 | +| iterations | 16 | +| time_elapsed | 1744 | +| total_timesteps | 573440 | +| train/ | | +| approx_kl | 0.022860302 | +| clip_fraction | 0.239 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.129 | +| learning_rate | 6e-05 | +| loss | 1.84 | +| n_updates | 150 | +| policy_gradient_loss | 0.0047 | +| value_loss | 9.31 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 328 | +| iterations | 17 | +| time_elapsed | 1855 | +| total_timesteps | 609280 | +| train/ | | +| approx_kl | 0.022038916 | +| clip_fraction | 0.239 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.132 | +| learning_rate | 6e-05 | +| loss | 0.592 | +| n_updates | 160 | +| policy_gradient_loss | 0.00797 | +| value_loss | 13.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -108 | +| time/ | | +| fps | 328 | +| iterations | 18 | +| time_elapsed | 1965 | +| total_timesteps | 645120 | +| train/ | | +| approx_kl | 0.019105315 | +| clip_fraction | 0.21 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.177 | +| learning_rate | 6e-05 | +| loss | 4.11 | +| n_updates | 170 | +| policy_gradient_loss | 0.00811 | +| value_loss | 10.7 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -107 | +| time/ | | +| fps | 328 | +| iterations | 19 | +| time_elapsed | 2075 | +| total_timesteps | 680960 | +| train/ | | +| approx_kl | 0.018897315 | +| clip_fraction | 0.19 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.192 | +| learning_rate | 6e-05 | +| loss | 32.8 | +| n_updates | 180 | +| policy_gradient_loss | 0.00387 | +| value_loss | 8.64 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -117 | +| time/ | | +| fps | 327 | +| iterations | 20 | +| time_elapsed | 2188 | +| total_timesteps | 716800 | +| train/ | | +| approx_kl | 0.019180825 | +| clip_fraction | 0.189 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.191 | +| learning_rate | 6e-05 | +| loss | 3.44 | +| n_updates | 190 | +| policy_gradient_loss | 0.00363 | +| value_loss | 11 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.39e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 327 | +| iterations | 21 | +| time_elapsed | 2299 | +| total_timesteps | 752640 | +| train/ | | +| approx_kl | 0.020077143 | +| clip_fraction | 0.177 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.135 | +| learning_rate | 6e-05 | +| loss | 13.4 | +| n_updates | 200 | +| policy_gradient_loss | 0.00547 | +| value_loss | 11.4 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -139 | +| time/ | | +| fps | 327 | +| iterations | 22 | +| time_elapsed | 2410 | +| total_timesteps | 788480 | +| train/ | | +| approx_kl | 0.01744306 | +| clip_fraction | 0.163 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.198 | +| learning_rate | 6e-05 | +| loss | 0.382 | +| n_updates | 210 | +| policy_gradient_loss | 0.00595 | +| value_loss | 9.73 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -140 | +| time/ | | +| fps | 326 | +| iterations | 23 | +| time_elapsed | 2521 | +| total_timesteps | 824320 | +| train/ | | +| approx_kl | 0.01349086 | +| clip_fraction | 0.136 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.193 | +| learning_rate | 6e-05 | +| loss | 0.953 | +| n_updates | 220 | +| policy_gradient_loss | 0.00365 | +| value_loss | 9.73 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -77.1 | +| time/ | | +| fps | 325 | +| iterations | 24 | +| time_elapsed | 2639 | +| total_timesteps | 860160 | +| train/ | | +| approx_kl | 0.013683978 | +| clip_fraction | 0.147 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.128 | +| learning_rate | 6e-05 | +| loss | 0.79 | +| n_updates | 230 | +| policy_gradient_loss | 0.00506 | +| value_loss | 15.5 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.39e+03 | +| ep_rew_mean | -45.8 | +| time/ | | +| fps | 325 | +| iterations | 25 | +| time_elapsed | 2752 | +| total_timesteps | 896000 | +| train/ | | +| approx_kl | 0.014018106 | +| clip_fraction | 0.14 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.00416 | +| learning_rate | 6e-05 | +| loss | 0.622 | +| n_updates | 240 | +| policy_gradient_loss | 0.00429 | +| value_loss | 954 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -33.8 | +| time/ | | +| fps | 325 | +| iterations | 26 | +| time_elapsed | 2863 | +| total_timesteps | 931840 | +| train/ | | +| approx_kl | 0.011773149 | +| clip_fraction | 0.131 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.00377 | +| learning_rate | 6e-05 | +| loss | 3.8 | +| n_updates | 250 | +| policy_gradient_loss | 0.00287 | +| value_loss | 350 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -28.5 | +| time/ | | +| fps | 324 | +| iterations | 27 | +| time_elapsed | 2979 | +| total_timesteps | 967680 | +| train/ | | +| approx_kl | 0.01187954 | +| clip_fraction | 0.121 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.0948 | +| learning_rate | 6e-05 | +| loss | 7.15 | +| n_updates | 260 | +| policy_gradient_loss | 0.0039 | +| value_loss | 11.3 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -14.4 | +| time/ | | +| fps | 324 | +| iterations | 28 | +| time_elapsed | 3090 | +| total_timesteps | 1003520 | +| train/ | | +| approx_kl | 0.011217899 | +| clip_fraction | 0.124 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.122 | +| learning_rate | 6e-05 | +| loss | 0.323 | +| n_updates | 270 | +| policy_gradient_loss | 0.00335 | +| value_loss | 14.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -11.3 | +| time/ | | +| fps | 324 | +| iterations | 29 | +| time_elapsed | 3200 | +| total_timesteps | 1039360 | +| train/ | | +| approx_kl | 0.012944548 | +| clip_fraction | 0.136 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.175 | +| learning_rate | 6e-05 | +| loss | 1.6 | +| n_updates | 280 | +| policy_gradient_loss | 0.00392 | +| value_loss | 11.6 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -18.7 | +| time/ | | +| fps | 324 | +| iterations | 30 | +| time_elapsed | 3313 | +| total_timesteps | 1075200 | +| train/ | | +| approx_kl | 0.011754743 | +| clip_fraction | 0.115 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.219 | +| learning_rate | 6e-05 | +| loss | 0.318 | +| n_updates | 290 | +| policy_gradient_loss | 0.0017 | +| value_loss | 9.09 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -71.9 | +| time/ | | +| fps | 324 | +| iterations | 31 | +| time_elapsed | 3425 | +| total_timesteps | 1111040 | +| train/ | | +| approx_kl | 0.01659386 | +| clip_fraction | 0.131 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.177 | +| learning_rate | 6e-05 | +| loss | 0.556 | +| n_updates | 300 | +| policy_gradient_loss | 0.00461 | +| value_loss | 9.77 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.54e+03 | +| ep_rew_mean | -101 | +| time/ | | +| fps | 324 | +| iterations | 32 | +| time_elapsed | 3535 | +| total_timesteps | 1146880 | +| train/ | | +| approx_kl | 0.011952113 | +| clip_fraction | 0.109 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.245 | +| learning_rate | 6e-05 | +| loss | 0.356 | +| n_updates | 310 | +| policy_gradient_loss | 0.00122 | +| value_loss | 8.21 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.54e+03 | +| ep_rew_mean | -120 | +| time/ | | +| fps | 324 | +| iterations | 33 | +| time_elapsed | 3649 | +| total_timesteps | 1182720 | +| train/ | | +| approx_kl | 0.012140925 | +| clip_fraction | 0.1 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.171 | +| learning_rate | 6e-05 | +| loss | 9.4 | +| n_updates | 320 | +| policy_gradient_loss | 0.00255 | +| value_loss | 9.02 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.56e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 323 | +| iterations | 34 | +| time_elapsed | 3763 | +| total_timesteps | 1218560 | +| train/ | | +| approx_kl | 0.015660465 | +| clip_fraction | 0.119 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.226 | +| learning_rate | 6e-05 | +| loss | 2.52 | +| n_updates | 330 | +| policy_gradient_loss | 0.00669 | +| value_loss | 11.8 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.57e+03 | +| ep_rew_mean | -116 | +| time/ | | +| fps | 323 | +| iterations | 35 | +| time_elapsed | 3873 | +| total_timesteps | 1254400 | +| train/ | | +| approx_kl | 0.012417111 | +| clip_fraction | 0.0986 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.215 | +| learning_rate | 6e-05 | +| loss | 1.76 | +| n_updates | 340 | +| policy_gradient_loss | 0.0034 | +| value_loss | 8.17 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -113 | +| time/ | | +| fps | 323 | +| iterations | 36 | +| time_elapsed | 3989 | +| total_timesteps | 1290240 | +| train/ | | +| approx_kl | 0.012947853 | +| clip_fraction | 0.103 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.172 | +| learning_rate | 6e-05 | +| loss | 2.13 | +| n_updates | 350 | +| policy_gradient_loss | 0.00457 | +| value_loss | 11.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -100 | +| time/ | | +| fps | 322 | +| iterations | 37 | +| time_elapsed | 4107 | +| total_timesteps | 1326080 | +| train/ | | +| approx_kl | 0.011590318 | +| clip_fraction | 0.0958 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.217 | +| learning_rate | 6e-05 | +| loss | 0.361 | +| n_updates | 360 | +| policy_gradient_loss | 0.00357 | +| value_loss | 12.3 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -105 | +| time/ | | +| fps | 322 | +| iterations | 38 | +| time_elapsed | 4220 | +| total_timesteps | 1361920 | +| train/ | | +| approx_kl | 0.010220998 | +| clip_fraction | 0.0941 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.233 | +| learning_rate | 6e-05 | +| loss | 0.713 | +| n_updates | 370 | +| policy_gradient_loss | 0.00461 | +| value_loss | 7.02 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -98.9 | +| time/ | | +| fps | 322 | +| iterations | 39 | +| time_elapsed | 4332 | +| total_timesteps | 1397760 | +| train/ | | +| approx_kl | 0.016354688 | +| clip_fraction | 0.111 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.175 | +| learning_rate | 6e-05 | +| loss | 4.73 | +| n_updates | 380 | +| policy_gradient_loss | 0.00377 | +| value_loss | 12.6 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -86.4 | +| time/ | | +| fps | 322 | +| iterations | 40 | +| time_elapsed | 4448 | +| total_timesteps | 1433600 | +| train/ | | +| approx_kl | 0.01376914 | +| clip_fraction | 0.0929 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.205 | +| learning_rate | 6e-05 | +| loss | 0.676 | +| n_updates | 390 | +| policy_gradient_loss | 0.00817 | +| value_loss | 10.1 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -81.9 | +| time/ | | +| fps | 322 | +| iterations | 41 | +| time_elapsed | 4557 | +| total_timesteps | 1469440 | +| train/ | | +| approx_kl | 0.009162674 | +| clip_fraction | 0.0872 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.133 | +| learning_rate | 6e-05 | +| loss | 1.28 | +| n_updates | 400 | +| policy_gradient_loss | 0.00412 | +| value_loss | 14.1 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -82.9 | +| time/ | | +| fps | 322 | +| iterations | 42 | +| time_elapsed | 4664 | +| total_timesteps | 1505280 | +| train/ | | +| approx_kl | 0.009312105 | +| clip_fraction | 0.0653 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.158 | +| learning_rate | 6e-05 | +| loss | 0.0358 | +| n_updates | 410 | +| policy_gradient_loss | 0.00398 | +| value_loss | 9.32 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.51e+03 | +| ep_rew_mean | -80.6 | +| time/ | | +| fps | 322 | +| iterations | 43 | +| time_elapsed | 4776 | +| total_timesteps | 1541120 | +| train/ | | +| approx_kl | 0.0116137685 | +| clip_fraction | 0.0647 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.185 | +| learning_rate | 6e-05 | +| loss | 0.971 | +| n_updates | 420 | +| policy_gradient_loss | 0.00522 | +| value_loss | 11.2 | +------------------------------------------ +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -88 | +| time/ | | +| fps | 322 | +| iterations | 44 | +| time_elapsed | 4883 | +| total_timesteps | 1576960 | +| train/ | | +| approx_kl | 0.0075986898 | +| clip_fraction | 0.0622 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.132 | +| learning_rate | 6e-05 | +| loss | 0.595 | +| n_updates | 430 | +| policy_gradient_loss | 0.0035 | +| value_loss | 10.2 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.63e+03 | +| ep_rew_mean | -31.5 | +| time/ | | +| fps | 323 | +| iterations | 45 | +| time_elapsed | 4992 | +| total_timesteps | 1612800 | +| train/ | | +| approx_kl | 0.008369539 | +| clip_fraction | 0.0486 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.184 | +| learning_rate | 6e-05 | +| loss | 3.35 | +| n_updates | 440 | +| policy_gradient_loss | 0.00372 | +| value_loss | 9.04 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.58e+03 | +| ep_rew_mean | -26.2 | +| time/ | | +| fps | 322 | +| iterations | 46 | +| time_elapsed | 5105 | +| total_timesteps | 1648640 | +| train/ | | +| approx_kl | 0.0073546325 | +| clip_fraction | 0.0519 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.00525 | +| learning_rate | 6e-05 | +| loss | 2.19 | +| n_updates | 450 | +| policy_gradient_loss | 0.00373 | +| value_loss | 463 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.57e+03 | +| ep_rew_mean | -7.57 | +| time/ | | +| fps | 322 | +| iterations | 47 | +| time_elapsed | 5216 | +| total_timesteps | 1684480 | +| train/ | | +| approx_kl | 0.019465668 | +| clip_fraction | 0.0381 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.098 | +| learning_rate | 6e-05 | +| loss | 38.6 | +| n_updates | 460 | +| policy_gradient_loss | 0.000535 | +| value_loss | 12.1 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.63e+03 | +| ep_rew_mean | -28.9 | +| time/ | | +| fps | 322 | +| iterations | 48 | +| time_elapsed | 5326 | +| total_timesteps | 1720320 | +| train/ | | +| approx_kl | 0.006279047 | +| clip_fraction | 0.042 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.034 | +| learning_rate | 6e-05 | +| loss | 0.114 | +| n_updates | 470 | +| policy_gradient_loss | 0.00356 | +| value_loss | 78.5 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.55e+03 | +| ep_rew_mean | -13.1 | +| time/ | | +| fps | 322 | +| iterations | 49 | +| time_elapsed | 5438 | +| total_timesteps | 1756160 | +| train/ | | +| approx_kl | 0.005161907 | +| clip_fraction | 0.0307 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.116 | +| learning_rate | 6e-05 | +| loss | 13.1 | +| n_updates | 480 | +| policy_gradient_loss | 0.00278 | +| value_loss | 12.5 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.58e+03 | +| ep_rew_mean | -17.4 | +| time/ | | +| fps | 322 | +| iterations | 50 | +| time_elapsed | 5550 | +| total_timesteps | 1792000 | +| train/ | | +| approx_kl | 0.0066763177 | +| clip_fraction | 0.0317 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.116 | +| learning_rate | 6e-05 | +| loss | 0.257 | +| n_updates | 490 | +| policy_gradient_loss | 0.00152 | +| value_loss | 13.9 | +------------------------------------------ +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.64e+03 | +| ep_rew_mean | -2.15 | +| time/ | | +| fps | 322 | +| iterations | 51 | +| time_elapsed | 5663 | +| total_timesteps | 1827840 | +| train/ | | +| approx_kl | 0.0054794447 | +| clip_fraction | 0.0303 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.0188 | +| learning_rate | 6e-05 | +| loss | 1.88 | +| n_updates | 500 | +| policy_gradient_loss | 0.00216 | +| value_loss | 128 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.64e+03 | +| ep_rew_mean | -59.1 | +| time/ | | +| fps | 322 | +| iterations | 52 | +| time_elapsed | 5781 | +| total_timesteps | 1863680 | +| train/ | | +| approx_kl | 0.004004343 | +| clip_fraction | 0.0281 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.126 | +| learning_rate | 6e-05 | +| loss | 6.13 | +| n_updates | 510 | +| policy_gradient_loss | 0.000878 | +| value_loss | 11.3 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.63e+03 | +| ep_rew_mean | -51.9 | +| time/ | | +| fps | 322 | +| iterations | 53 | +| time_elapsed | 5894 | +| total_timesteps | 1899520 | +| train/ | | +| approx_kl | 0.0040078186 | +| clip_fraction | 0.026 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.0973 | +| learning_rate | 6e-05 | +| loss | 0.153 | +| n_updates | 520 | +| policy_gradient_loss | 0.00193 | +| value_loss | 10 | +------------------------------------------ +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.64e+03 | +| ep_rew_mean | -62 | +| time/ | | +| fps | 322 | +| iterations | 54 | +| time_elapsed | 6004 | +| total_timesteps | 1935360 | +| train/ | | +| approx_kl | 0.0059778546 | +| clip_fraction | 0.0321 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.0963 | +| learning_rate | 6e-05 | +| loss | 3.3 | +| n_updates | 530 | +| policy_gradient_loss | 0.00259 | +| value_loss | 10.9 | +------------------------------------------ +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.57e+03 | +| ep_rew_mean | -52.9 | +| time/ | | +| fps | 322 | +| iterations | 55 | +| time_elapsed | 6112 | +| total_timesteps | 1971200 | +| train/ | | +| approx_kl | 0.0063833822 | +| clip_fraction | 0.0278 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.188 | +| learning_rate | 6e-05 | +| loss | 3.17 | +| n_updates | 540 | +| policy_gradient_loss | 0.00346 | +| value_loss | 9.17 | +------------------------------------------ +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.6e+03 | +| ep_rew_mean | -57.5 | +| time/ | | +| fps | 322 | +| iterations | 56 | +| time_elapsed | 6223 | +| total_timesteps | 2007040 | +| train/ | | +| approx_kl | 0.0073829913 | +| clip_fraction | 0.033 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.114 | +| learning_rate | 6e-05 | +| loss | 3.82 | +| n_updates | 550 | +| policy_gradient_loss | 0.00575 | +| value_loss | 14.8 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.64e+03 | +| ep_rew_mean | -51.7 | +| time/ | | +| fps | 322 | +| iterations | 57 | +| time_elapsed | 6331 | +| total_timesteps | 2042880 | +| train/ | | +| approx_kl | 0.006855669 | +| clip_fraction | 0.0367 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.147 | +| learning_rate | 6e-05 | +| loss | 1.13 | +| n_updates | 560 | +| policy_gradient_loss | 0.00607 | +| value_loss | 9.96 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.54e+03 | +| ep_rew_mean | -79.9 | +| time/ | | +| fps | 322 | +| iterations | 58 | +| time_elapsed | 6437 | +| total_timesteps | 2078720 | +| train/ | | +| approx_kl | 0.00765656 | +| clip_fraction | 0.024 | +| clip_range | 0.155 | +| entropy_loss | -8.31 | +| explained_variance | 0.0883 | +| learning_rate | 6e-05 | +| loss | 0.762 | +| n_updates | 570 | +| policy_gradient_loss | 0.00303 | +| value_loss | 9.47 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -83.6 | +| time/ | | +| fps | 322 | +| iterations | 59 | +| time_elapsed | 6551 | +| total_timesteps | 2114560 | +| train/ | | +| approx_kl | 0.011897133 | +| clip_fraction | 0.0378 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.163 | +| learning_rate | 6e-05 | +| loss | 3.51 | +| n_updates | 580 | +| policy_gradient_loss | 0.00693 | +| value_loss | 11.8 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -84.7 | +| time/ | | +| fps | 322 | +| iterations | 60 | +| time_elapsed | 6660 | +| total_timesteps | 2150400 | +| train/ | | +| approx_kl | 0.009864187 | +| clip_fraction | 0.0326 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.149 | +| learning_rate | 6e-05 | +| loss | 3.69 | +| n_updates | 590 | +| policy_gradient_loss | 0.0073 | +| value_loss | 11.6 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -95.9 | +| time/ | | +| fps | 322 | +| iterations | 61 | +| time_elapsed | 6771 | +| total_timesteps | 2186240 | +| train/ | | +| approx_kl | 0.015894253 | +| clip_fraction | 0.0338 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.118 | +| learning_rate | 6e-05 | +| loss | 1.35 | +| n_updates | 600 | +| policy_gradient_loss | 0.00843 | +| value_loss | 11.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.49e+03 | +| ep_rew_mean | -108 | +| time/ | | +| fps | 322 | +| iterations | 62 | +| time_elapsed | 6883 | +| total_timesteps | 2222080 | +| train/ | | +| approx_kl | 0.008286863 | +| clip_fraction | 0.0252 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.12 | +| learning_rate | 6e-05 | +| loss | 0.408 | +| n_updates | 610 | +| policy_gradient_loss | 0.00399 | +| value_loss | 11.3 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -107 | +| time/ | | +| fps | 322 | +| iterations | 63 | +| time_elapsed | 6994 | +| total_timesteps | 2257920 | +| train/ | | +| approx_kl | 0.017238934 | +| clip_fraction | 0.0246 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.156 | +| learning_rate | 6e-05 | +| loss | 5.56 | +| n_updates | 620 | +| policy_gradient_loss | 0.00791 | +| value_loss | 15.3 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.48e+03 | +| ep_rew_mean | -126 | +| time/ | | +| fps | 322 | +| iterations | 64 | +| time_elapsed | 7106 | +| total_timesteps | 2293760 | +| train/ | | +| approx_kl | 0.009971302 | +| clip_fraction | 0.0238 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.141 | +| learning_rate | 6e-05 | +| loss | 0.729 | +| n_updates | 630 | +| policy_gradient_loss | 0.00418 | +| value_loss | 20.7 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.48e+03 | +| ep_rew_mean | -116 | +| time/ | | +| fps | 322 | +| iterations | 65 | +| time_elapsed | 7218 | +| total_timesteps | 2329600 | +| train/ | | +| approx_kl | 0.010677262 | +| clip_fraction | 0.024 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.166 | +| learning_rate | 6e-05 | +| loss | 0.867 | +| n_updates | 640 | +| policy_gradient_loss | 0.00226 | +| value_loss | 19.7 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.58e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 322 | +| iterations | 66 | +| time_elapsed | 7328 | +| total_timesteps | 2365440 | +| train/ | | +| approx_kl | 0.0071625956 | +| clip_fraction | 0.0256 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.104 | +| learning_rate | 6e-05 | +| loss | 2.4 | +| n_updates | 650 | +| policy_gradient_loss | 0.00594 | +| value_loss | 14.4 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -84.8 | +| time/ | | +| fps | 322 | +| iterations | 67 | +| time_elapsed | 7439 | +| total_timesteps | 2401280 | +| train/ | | +| approx_kl | 0.011161038 | +| clip_fraction | 0.0223 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.15 | +| learning_rate | 6e-05 | +| loss | 4.37 | +| n_updates | 660 | +| policy_gradient_loss | 0.00536 | +| value_loss | 9.4 | +----------------------------------------- +------------------------------------------ +| rollout/ | | +| ep_len_mean | 2.51e+03 | +| ep_rew_mean | -78.5 | +| time/ | | +| fps | 322 | +| iterations | 68 | +| time_elapsed | 7547 | +| total_timesteps | 2437120 | +| train/ | | +| approx_kl | 0.0055492893 | +| clip_fraction | 0.0199 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.00508 | +| learning_rate | 6e-05 | +| loss | 3.14 | +| n_updates | 670 | +| policy_gradient_loss | 0.00415 | +| value_loss | 540 | +------------------------------------------ +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.54e+03 | +| ep_rew_mean | -77.1 | +| time/ | | +| fps | 322 | +| iterations | 69 | +| time_elapsed | 7660 | +| total_timesteps | 2472960 | +| train/ | | +| approx_kl | 0.009921813 | +| clip_fraction | 0.0249 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.291 | +| learning_rate | 6e-05 | +| loss | 6.92 | +| n_updates | 680 | +| policy_gradient_loss | 0.00479 | +| value_loss | 8.89 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.51e+03 | +| ep_rew_mean | -84.3 | +| time/ | | +| fps | 322 | +| iterations | 70 | +| time_elapsed | 7767 | +| total_timesteps | 2508800 | +| train/ | | +| approx_kl | 0.008127724 | +| clip_fraction | 0.0249 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.13 | +| learning_rate | 6e-05 | +| loss | 1.88 | +| n_updates | 690 | +| policy_gradient_loss | 0.0039 | +| value_loss | 12 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.48e+03 | +| ep_rew_mean | -85 | +| time/ | | +| fps | 323 | +| iterations | 71 | +| time_elapsed | 7876 | +| total_timesteps | 2544640 | +| train/ | | +| approx_kl | 0.014872775 | +| clip_fraction | 0.0288 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.125 | +| learning_rate | 6e-05 | +| loss | -0.0535 | +| n_updates | 700 | +| policy_gradient_loss | 0.00914 | +| value_loss | 16.1 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.57e+03 | +| ep_rew_mean | -76.3 | +| time/ | | +| fps | 322 | +| iterations | 72 | +| time_elapsed | 7991 | +| total_timesteps | 2580480 | +| train/ | | +| approx_kl | 0.016463093 | +| clip_fraction | 0.0383 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.299 | +| learning_rate | 6e-05 | +| loss | 0.0458 | +| n_updates | 710 | +| policy_gradient_loss | 0.00876 | +| value_loss | 11.1 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -75.6 | +| time/ | | +| fps | 322 | +| iterations | 73 | +| time_elapsed | 8103 | +| total_timesteps | 2616320 | +| train/ | | +| approx_kl | 0.009839703 | +| clip_fraction | 0.0311 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.169 | +| learning_rate | 6e-05 | +| loss | 3.51 | +| n_updates | 720 | +| policy_gradient_loss | 0.00673 | +| value_loss | 10.7 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.46e+03 | +| ep_rew_mean | -112 | +| time/ | | +| fps | 322 | +| iterations | 74 | +| time_elapsed | 8214 | +| total_timesteps | 2652160 | +| train/ | | +| approx_kl | 0.028734079 | +| clip_fraction | 0.0455 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.209 | +| learning_rate | 6e-05 | +| loss | 7.12 | +| n_updates | 730 | +| policy_gradient_loss | 0.00743 | +| value_loss | 12 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -58 | +| time/ | | +| fps | 322 | +| iterations | 75 | +| time_elapsed | 8326 | +| total_timesteps | 2688000 | +| train/ | | +| approx_kl | 0.02214181 | +| clip_fraction | 0.0544 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.16 | +| learning_rate | 6e-05 | +| loss | 2.05 | +| n_updates | 740 | +| policy_gradient_loss | 0.0127 | +| value_loss | 13.8 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -56.9 | +| time/ | | +| fps | 322 | +| iterations | 76 | +| time_elapsed | 8436 | +| total_timesteps | 2723840 | +| train/ | | +| approx_kl | 0.01680419 | +| clip_fraction | 0.0459 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.00435 | +| learning_rate | 6e-05 | +| loss | 2.08 | +| n_updates | 750 | +| policy_gradient_loss | 0.00956 | +| value_loss | 962 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.52e+03 | +| ep_rew_mean | -53.8 | +| time/ | | +| fps | 322 | +| iterations | 77 | +| time_elapsed | 8548 | +| total_timesteps | 2759680 | +| train/ | | +| approx_kl | 0.022428373 | +| clip_fraction | 0.0394 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.198 | +| learning_rate | 6e-05 | +| loss | 0.678 | +| n_updates | 760 | +| policy_gradient_loss | 0.00761 | +| value_loss | 9.44 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.47e+03 | +| ep_rew_mean | -41.5 | +| time/ | | +| fps | 322 | +| iterations | 78 | +| time_elapsed | 8658 | +| total_timesteps | 2795520 | +| train/ | | +| approx_kl | 0.018052083 | +| clip_fraction | 0.0357 | +| clip_range | 0.155 | +| entropy_loss | -8.3 | +| explained_variance | 0.113 | +| learning_rate | 6e-05 | +| loss | 8.2 | +| n_updates | 770 | +| policy_gradient_loss | 0.00723 | +| value_loss | 12.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -44.2 | +| time/ | | +| fps | 322 | +| iterations | 79 | +| time_elapsed | 8770 | +| total_timesteps | 2831360 | +| train/ | | +| approx_kl | 0.018138604 | +| clip_fraction | 0.0362 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.152 | +| learning_rate | 6e-05 | +| loss | 1.26 | +| n_updates | 780 | +| policy_gradient_loss | 0.00648 | +| value_loss | 15 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.43e+03 | +| ep_rew_mean | -46.5 | +| time/ | | +| fps | 322 | +| iterations | 80 | +| time_elapsed | 8879 | +| total_timesteps | 2867200 | +| train/ | | +| approx_kl | 0.025932662 | +| clip_fraction | 0.0341 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.204 | +| learning_rate | 6e-05 | +| loss | 3.03 | +| n_updates | 790 | +| policy_gradient_loss | 0.00861 | +| value_loss | 8.87 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.46e+03 | +| ep_rew_mean | -52.3 | +| time/ | | +| fps | 323 | +| iterations | 81 | +| time_elapsed | 8987 | +| total_timesteps | 2903040 | +| train/ | | +| approx_kl | 0.016968325 | +| clip_fraction | 0.0369 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.153 | +| learning_rate | 6e-05 | +| loss | 0.209 | +| n_updates | 800 | +| policy_gradient_loss | 0.00617 | +| value_loss | 12.4 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -109 | +| time/ | | +| fps | 323 | +| iterations | 82 | +| time_elapsed | 9098 | +| total_timesteps | 2938880 | +| train/ | | +| approx_kl | 0.025080647 | +| clip_fraction | 0.0355 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.241 | +| learning_rate | 6e-05 | +| loss | 11.9 | +| n_updates | 810 | +| policy_gradient_loss | 0.0105 | +| value_loss | 9.72 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -107 | +| time/ | | +| fps | 323 | +| iterations | 83 | +| time_elapsed | 9206 | +| total_timesteps | 2974720 | +| train/ | | +| approx_kl | 0.02796489 | +| clip_fraction | 0.0335 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.166 | +| learning_rate | 6e-05 | +| loss | 0.346 | +| n_updates | 820 | +| policy_gradient_loss | 0.00976 | +| value_loss | 13.8 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 323 | +| iterations | 84 | +| time_elapsed | 9314 | +| total_timesteps | 3010560 | +| train/ | | +| approx_kl | 0.03354401 | +| clip_fraction | 0.0355 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.164 | +| learning_rate | 6e-05 | +| loss | 14 | +| n_updates | 830 | +| policy_gradient_loss | 0.0089 | +| value_loss | 13.4 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.39e+03 | +| ep_rew_mean | -111 | +| time/ | | +| fps | 323 | +| iterations | 85 | +| time_elapsed | 9428 | +| total_timesteps | 3046400 | +| train/ | | +| approx_kl | 0.04482753 | +| clip_fraction | 0.0399 | +| clip_range | 0.155 | +| entropy_loss | -8.28 | +| explained_variance | 0.142 | +| learning_rate | 6e-05 | +| loss | 4.24 | +| n_updates | 840 | +| policy_gradient_loss | 0.00868 | +| value_loss | 12.4 | +---------------------------------------- +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 322 | +| iterations | 86 | +| time_elapsed | 9543 | +| total_timesteps | 3082240 | +| train/ | | +| approx_kl | 0.029196 | +| clip_fraction | 0.0325 | +| clip_range | 0.155 | +| entropy_loss | -8.29 | +| explained_variance | 0.178 | +| learning_rate | 6e-05 | +| loss | 31.3 | +| n_updates | 850 | +| policy_gradient_loss | 0.00857 | +| value_loss | 9.72 | +-------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -126 | +| time/ | | +| fps | 322 | +| iterations | 87 | +| time_elapsed | 9658 | +| total_timesteps | 3118080 | +| train/ | | +| approx_kl | 0.03724062 | +| clip_fraction | 0.0473 | +| clip_range | 0.155 | +| entropy_loss | -8.26 | +| explained_variance | 0.162 | +| learning_rate | 6e-05 | +| loss | 1.17 | +| n_updates | 860 | +| policy_gradient_loss | 0.0102 | +| value_loss | 10.7 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -122 | +| time/ | | +| fps | 322 | +| iterations | 88 | +| time_elapsed | 9771 | +| total_timesteps | 3153920 | +| train/ | | +| approx_kl | 0.073307335 | +| clip_fraction | 0.059 | +| clip_range | 0.155 | +| entropy_loss | -8.24 | +| explained_variance | 0.164 | +| learning_rate | 6e-05 | +| loss | 0.052 | +| n_updates | 870 | +| policy_gradient_loss | 0.0146 | +| value_loss | 17.2 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 322 | +| iterations | 89 | +| time_elapsed | 9884 | +| total_timesteps | 3189760 | +| train/ | | +| approx_kl | 0.052658338 | +| clip_fraction | 0.0485 | +| clip_range | 0.155 | +| entropy_loss | -8.26 | +| explained_variance | 0.167 | +| learning_rate | 6e-05 | +| loss | 4.54 | +| n_updates | 880 | +| policy_gradient_loss | 0.0106 | +| value_loss | 11.7 | +----------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 322 | +| iterations | 90 | +| time_elapsed | 9997 | +| total_timesteps | 3225600 | +| train/ | | +| approx_kl | 0.047828972 | +| clip_fraction | 0.0548 | +| clip_range | 0.155 | +| entropy_loss | -8.25 | +| explained_variance | 0.151 | +| learning_rate | 6e-05 | +| loss | 4.92 | +| n_updates | 890 | +| policy_gradient_loss | 0.0171 | +| value_loss | 9.67 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 322 | +| iterations | 91 | +| time_elapsed | 10109 | +| total_timesteps | 3261440 | +| train/ | | +| approx_kl | 0.04650531 | +| clip_fraction | 0.063 | +| clip_range | 0.155 | +| entropy_loss | -8.22 | +| explained_variance | 0.107 | +| learning_rate | 6e-05 | +| loss | 3.9 | +| n_updates | 900 | +| policy_gradient_loss | 0.0169 | +| value_loss | 12.6 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.43e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 322 | +| iterations | 92 | +| time_elapsed | 10222 | +| total_timesteps | 3297280 | +| train/ | | +| approx_kl | 0.026718527 | +| clip_fraction | 0.0444 | +| clip_range | 0.155 | +| entropy_loss | -8.27 | +| explained_variance | 0.132 | +| learning_rate | 6e-05 | +| loss | 1.67 | +| n_updates | 910 | +| policy_gradient_loss | 0.00786 | +| value_loss | 9.84 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 322 | +| iterations | 93 | +| time_elapsed | 10337 | +| total_timesteps | 3333120 | +| train/ | | +| approx_kl | 0.07109032 | +| clip_fraction | 0.0635 | +| clip_range | 0.155 | +| entropy_loss | -8.19 | +| explained_variance | 0.211 | +| learning_rate | 6e-05 | +| loss | 0.688 | +| n_updates | 920 | +| policy_gradient_loss | 0.0149 | +| value_loss | 8.78 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -97.6 | +| time/ | | +| fps | 322 | +| iterations | 94 | +| time_elapsed | 10450 | +| total_timesteps | 3368960 | +| train/ | | +| approx_kl | 0.06335044 | +| clip_fraction | 0.0486 | +| clip_range | 0.155 | +| entropy_loss | -8.25 | +| explained_variance | 0.2 | +| learning_rate | 6e-05 | +| loss | 10.3 | +| n_updates | 930 | +| policy_gradient_loss | 0.0139 | +| value_loss | 10.9 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -107 | +| time/ | | +| fps | 322 | +| iterations | 95 | +| time_elapsed | 10566 | +| total_timesteps | 3404800 | +| train/ | | +| approx_kl | 0.043878794 | +| clip_fraction | 0.0491 | +| clip_range | 0.155 | +| entropy_loss | -8.25 | +| explained_variance | 0.0986 | +| learning_rate | 6e-05 | +| loss | 9.38 | +| n_updates | 940 | +| policy_gradient_loss | 0.0125 | +| value_loss | 15.9 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.36e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 322 | +| iterations | 96 | +| time_elapsed | 10680 | +| total_timesteps | 3440640 | +| train/ | | +| approx_kl | 0.05979298 | +| clip_fraction | 0.0676 | +| clip_range | 0.155 | +| entropy_loss | -8.2 | +| explained_variance | 0.197 | +| learning_rate | 6e-05 | +| loss | 1.4 | +| n_updates | 950 | +| policy_gradient_loss | 0.0175 | +| value_loss | 11.4 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -112 | +| time/ | | +| fps | 322 | +| iterations | 97 | +| time_elapsed | 10794 | +| total_timesteps | 3476480 | +| train/ | | +| approx_kl | 0.091493666 | +| clip_fraction | 0.0731 | +| clip_range | 0.155 | +| entropy_loss | -8.2 | +| explained_variance | 0.149 | +| learning_rate | 6e-05 | +| loss | 46.5 | +| n_updates | 960 | +| policy_gradient_loss | 0.0195 | +| value_loss | 15.3 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.29e+03 | +| ep_rew_mean | -108 | +| time/ | | +| fps | 322 | +| iterations | 98 | +| time_elapsed | 10906 | +| total_timesteps | 3512320 | +| train/ | | +| approx_kl | 0.07293383 | +| clip_fraction | 0.0632 | +| clip_range | 0.155 | +| entropy_loss | -8.21 | +| explained_variance | 0.233 | +| learning_rate | 6e-05 | +| loss | 3.57 | +| n_updates | 970 | +| policy_gradient_loss | 0.0189 | +| value_loss | 10 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.28e+03 | +| ep_rew_mean | -101 | +| time/ | | +| fps | 321 | +| iterations | 99 | +| time_elapsed | 11020 | +| total_timesteps | 3548160 | +| train/ | | +| approx_kl | 0.05710225 | +| clip_fraction | 0.0589 | +| clip_range | 0.155 | +| entropy_loss | -8.22 | +| explained_variance | 0.264 | +| learning_rate | 6e-05 | +| loss | 0.0927 | +| n_updates | 980 | +| policy_gradient_loss | 0.0166 | +| value_loss | 12 | +---------------------------------------- +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.31e+03 | +| ep_rew_mean | -98.2 | +| time/ | | +| fps | 322 | +| iterations | 100 | +| time_elapsed | 11128 | +| total_timesteps | 3584000 | +| train/ | | +| approx_kl | 0.084365 | +| clip_fraction | 0.063 | +| clip_range | 0.155 | +| entropy_loss | -8.19 | +| explained_variance | 0.224 | +| learning_rate | 6e-05 | +| loss | 0.5 | +| n_updates | 990 | +| policy_gradient_loss | 0.0194 | +| value_loss | 9.49 | +-------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.31e+03 | +| ep_rew_mean | -104 | +| time/ | | +| fps | 321 | +| iterations | 101 | +| time_elapsed | 11242 | +| total_timesteps | 3619840 | +| train/ | | +| approx_kl | 0.09273384 | +| clip_fraction | 0.0506 | +| clip_range | 0.155 | +| entropy_loss | -8.22 | +| explained_variance | 0.178 | +| learning_rate | 6e-05 | +| loss | 0.00826 | +| n_updates | 1000 | +| policy_gradient_loss | 0.0135 | +| value_loss | 10.2 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 321 | +| iterations | 102 | +| time_elapsed | 11355 | +| total_timesteps | 3655680 | +| train/ | | +| approx_kl | 0.07110433 | +| clip_fraction | 0.0701 | +| clip_range | 0.155 | +| entropy_loss | -8.16 | +| explained_variance | 0.176 | +| learning_rate | 6e-05 | +| loss | 0.493 | +| n_updates | 1010 | +| policy_gradient_loss | 0.039 | +| value_loss | 10.8 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -101 | +| time/ | | +| fps | 321 | +| iterations | 103 | +| time_elapsed | 11470 | +| total_timesteps | 3691520 | +| train/ | | +| approx_kl | 0.12202358 | +| clip_fraction | 0.0564 | +| clip_range | 0.155 | +| entropy_loss | -8.2 | +| explained_variance | 0.163 | +| learning_rate | 6e-05 | +| loss | 0.342 | +| n_updates | 1020 | +| policy_gradient_loss | 0.0155 | +| value_loss | 13.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -106 | +| time/ | | +| fps | 321 | +| iterations | 104 | +| time_elapsed | 11583 | +| total_timesteps | 3727360 | +| train/ | | +| approx_kl | 0.05147917 | +| clip_fraction | 0.0448 | +| clip_range | 0.155 | +| entropy_loss | -8.23 | +| explained_variance | 0.176 | +| learning_rate | 6e-05 | +| loss | 0.532 | +| n_updates | 1030 | +| policy_gradient_loss | 0.0145 | +| value_loss | 11.6 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -115 | +| time/ | | +| fps | 321 | +| iterations | 105 | +| time_elapsed | 11696 | +| total_timesteps | 3763200 | +| train/ | | +| approx_kl | 0.10852592 | +| clip_fraction | 0.0717 | +| clip_range | 0.155 | +| entropy_loss | -8.14 | +| explained_variance | 0.213 | +| learning_rate | 6e-05 | +| loss | 1.09 | +| n_updates | 1040 | +| policy_gradient_loss | 0.0211 | +| value_loss | 10.3 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.36e+03 | +| ep_rew_mean | -120 | +| time/ | | +| fps | 321 | +| iterations | 106 | +| time_elapsed | 11808 | +| total_timesteps | 3799040 | +| train/ | | +| approx_kl | 0.11565618 | +| clip_fraction | 0.0687 | +| clip_range | 0.155 | +| entropy_loss | -8.16 | +| explained_variance | 0.114 | +| learning_rate | 6e-05 | +| loss | 0.0915 | +| n_updates | 1050 | +| policy_gradient_loss | 0.0209 | +| value_loss | 14 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 321 | +| iterations | 107 | +| time_elapsed | 11919 | +| total_timesteps | 3834880 | +| train/ | | +| approx_kl | 0.14752688 | +| clip_fraction | 0.0839 | +| clip_range | 0.155 | +| entropy_loss | -8.1 | +| explained_variance | 0.198 | +| learning_rate | 6e-05 | +| loss | 1.8 | +| n_updates | 1060 | +| policy_gradient_loss | 0.0262 | +| value_loss | 11.4 | +---------------------------------------- +----------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -75 | +| time/ | | +| fps | 321 | +| iterations | 108 | +| time_elapsed | 12031 | +| total_timesteps | 3870720 | +| train/ | | +| approx_kl | 0.121228136 | +| clip_fraction | 0.0701 | +| clip_range | 0.155 | +| entropy_loss | -8.11 | +| explained_variance | 0.25 | +| learning_rate | 6e-05 | +| loss | 5.19 | +| n_updates | 1070 | +| policy_gradient_loss | 0.0229 | +| value_loss | 7.36 | +----------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -72.3 | +| time/ | | +| fps | 321 | +| iterations | 109 | +| time_elapsed | 12143 | +| total_timesteps | 3906560 | +| train/ | | +| approx_kl | 0.10632153 | +| clip_fraction | 0.0787 | +| clip_range | 0.155 | +| entropy_loss | -8.09 | +| explained_variance | 0.0061 | +| learning_rate | 6e-05 | +| loss | 1.19 | +| n_updates | 1080 | +| policy_gradient_loss | 0.0222 | +| value_loss | 513 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.49e+03 | +| ep_rew_mean | -63.3 | +| time/ | | +| fps | 321 | +| iterations | 110 | +| time_elapsed | 12255 | +| total_timesteps | 3942400 | +| train/ | | +| approx_kl | 0.15867813 | +| clip_fraction | 0.0861 | +| clip_range | 0.155 | +| entropy_loss | -8.06 | +| explained_variance | 0.255 | +| learning_rate | 6e-05 | +| loss | 0.495 | +| n_updates | 1090 | +| policy_gradient_loss | 0.0242 | +| value_loss | 10.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.5e+03 | +| ep_rew_mean | -67.5 | +| time/ | | +| fps | 321 | +| iterations | 111 | +| time_elapsed | 12369 | +| total_timesteps | 3978240 | +| train/ | | +| approx_kl | 0.12611906 | +| clip_fraction | 0.0647 | +| clip_range | 0.155 | +| entropy_loss | -8.13 | +| explained_variance | 0.0467 | +| learning_rate | 6e-05 | +| loss | 5.08 | +| n_updates | 1100 | +| policy_gradient_loss | 0.0195 | +| value_loss | 80.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -66.4 | +| time/ | | +| fps | 321 | +| iterations | 112 | +| time_elapsed | 12483 | +| total_timesteps | 4014080 | +| train/ | | +| approx_kl | 0.16015784 | +| clip_fraction | 0.0553 | +| clip_range | 0.155 | +| entropy_loss | -8.17 | +| explained_variance | 0.149 | +| learning_rate | 6e-05 | +| loss | 0.0422 | +| n_updates | 1110 | +| policy_gradient_loss | 0.031 | +| value_loss | 11.2 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -61 | +| time/ | | +| fps | 321 | +| iterations | 113 | +| time_elapsed | 12595 | +| total_timesteps | 4049920 | +| train/ | | +| approx_kl | 0.19592966 | +| clip_fraction | 0.0659 | +| clip_range | 0.155 | +| entropy_loss | -8.13 | +| explained_variance | 0.149 | +| learning_rate | 6e-05 | +| loss | 1.63 | +| n_updates | 1120 | +| policy_gradient_loss | 0.0197 | +| value_loss | 16.1 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -64.9 | +| time/ | | +| fps | 321 | +| iterations | 114 | +| time_elapsed | 12713 | +| total_timesteps | 4085760 | +| train/ | | +| approx_kl | 0.14562534 | +| clip_fraction | 0.063 | +| clip_range | 0.155 | +| entropy_loss | -8.11 | +| explained_variance | 0.194 | +| learning_rate | 6e-05 | +| loss | 3.38 | +| n_updates | 1130 | +| policy_gradient_loss | 0.0332 | +| value_loss | 11.3 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -97 | +| time/ | | +| fps | 321 | +| iterations | 115 | +| time_elapsed | 12825 | +| total_timesteps | 4121600 | +| train/ | | +| approx_kl | 0.1879231 | +| clip_fraction | 0.0709 | +| clip_range | 0.155 | +| entropy_loss | -8.07 | +| explained_variance | 0.214 | +| learning_rate | 6e-05 | +| loss | 0.503 | +| n_updates | 1140 | +| policy_gradient_loss | 0.024 | +| value_loss | 10.5 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 321 | +| iterations | 116 | +| time_elapsed | 12936 | +| total_timesteps | 4157440 | +| train/ | | +| approx_kl | 0.21333364 | +| clip_fraction | 0.0792 | +| clip_range | 0.155 | +| entropy_loss | -8.08 | +| explained_variance | 0.216 | +| learning_rate | 6e-05 | +| loss | 0.0629 | +| n_updates | 1150 | +| policy_gradient_loss | 0.0234 | +| value_loss | 10.2 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -113 | +| time/ | | +| fps | 321 | +| iterations | 117 | +| time_elapsed | 13044 | +| total_timesteps | 4193280 | +| train/ | | +| approx_kl | 0.29418498 | +| clip_fraction | 0.104 | +| clip_range | 0.155 | +| entropy_loss | -7.91 | +| explained_variance | 0.291 | +| learning_rate | 6e-05 | +| loss | 3.07 | +| n_updates | 1160 | +| policy_gradient_loss | 0.0309 | +| value_loss | 13.1 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -111 | +| time/ | | +| fps | 321 | +| iterations | 118 | +| time_elapsed | 13156 | +| total_timesteps | 4229120 | +| train/ | | +| approx_kl | 0.26577407 | +| clip_fraction | 0.0855 | +| clip_range | 0.155 | +| entropy_loss | -7.96 | +| explained_variance | 0.182 | +| learning_rate | 6e-05 | +| loss | 0.717 | +| n_updates | 1170 | +| policy_gradient_loss | 0.0294 | +| value_loss | 10.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -118 | +| time/ | | +| fps | 321 | +| iterations | 119 | +| time_elapsed | 13270 | +| total_timesteps | 4264960 | +| train/ | | +| approx_kl | 0.24464282 | +| clip_fraction | 0.078 | +| clip_range | 0.155 | +| entropy_loss | -8.03 | +| explained_variance | 0.209 | +| learning_rate | 6e-05 | +| loss | 0.217 | +| n_updates | 1180 | +| policy_gradient_loss | 0.0215 | +| value_loss | 11.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.48e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 321 | +| iterations | 120 | +| time_elapsed | 13382 | +| total_timesteps | 4300800 | +| train/ | | +| approx_kl | 0.19720955 | +| clip_fraction | 0.0707 | +| clip_range | 0.155 | +| entropy_loss | -8.06 | +| explained_variance | 0.14 | +| learning_rate | 6e-05 | +| loss | 76.4 | +| n_updates | 1190 | +| policy_gradient_loss | 0.035 | +| value_loss | 15.7 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -117 | +| time/ | | +| fps | 321 | +| iterations | 121 | +| time_elapsed | 13496 | +| total_timesteps | 4336640 | +| train/ | | +| approx_kl | 0.23292133 | +| clip_fraction | 0.0855 | +| clip_range | 0.155 | +| entropy_loss | -7.9 | +| explained_variance | 0.26 | +| learning_rate | 6e-05 | +| loss | 2.33 | +| n_updates | 1200 | +| policy_gradient_loss | 0.03 | +| value_loss | 9.48 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -123 | +| time/ | | +| fps | 321 | +| iterations | 122 | +| time_elapsed | 13609 | +| total_timesteps | 4372480 | +| train/ | | +| approx_kl | 0.30917075 | +| clip_fraction | 0.0809 | +| clip_range | 0.155 | +| entropy_loss | -7.91 | +| explained_variance | 0.234 | +| learning_rate | 6e-05 | +| loss | 0.732 | +| n_updates | 1210 | +| policy_gradient_loss | 0.0296 | +| value_loss | 12.5 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 321 | +| iterations | 123 | +| time_elapsed | 13720 | +| total_timesteps | 4408320 | +| train/ | | +| approx_kl | 0.3058498 | +| clip_fraction | 0.0735 | +| clip_range | 0.155 | +| entropy_loss | -8.03 | +| explained_variance | 0.197 | +| learning_rate | 6e-05 | +| loss | -0.0221 | +| n_updates | 1220 | +| policy_gradient_loss | 0.146 | +| value_loss | 11.8 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -109 | +| time/ | | +| fps | 321 | +| iterations | 124 | +| time_elapsed | 13832 | +| total_timesteps | 4444160 | +| train/ | | +| approx_kl | 0.30846933 | +| clip_fraction | 0.0646 | +| clip_range | 0.155 | +| entropy_loss | -8.02 | +| explained_variance | 0.145 | +| learning_rate | 6e-05 | +| loss | 5.6 | +| n_updates | 1230 | +| policy_gradient_loss | 0.0238 | +| value_loss | 12.9 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -111 | +| time/ | | +| fps | 321 | +| iterations | 125 | +| time_elapsed | 13944 | +| total_timesteps | 4480000 | +| train/ | | +| approx_kl | 0.24360867 | +| clip_fraction | 0.0597 | +| clip_range | 0.155 | +| entropy_loss | -8.03 | +| explained_variance | 0.203 | +| learning_rate | 6e-05 | +| loss | 1.73 | +| n_updates | 1240 | +| policy_gradient_loss | 0.0223 | +| value_loss | 9.69 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -100 | +| time/ | | +| fps | 321 | +| iterations | 126 | +| time_elapsed | 14056 | +| total_timesteps | 4515840 | +| train/ | | +| approx_kl | 0.4805094 | +| clip_fraction | 0.0725 | +| clip_range | 0.155 | +| entropy_loss | -7.95 | +| explained_variance | 0.166 | +| learning_rate | 6e-05 | +| loss | 3.72 | +| n_updates | 1250 | +| policy_gradient_loss | 0.0229 | +| value_loss | 13 | +--------------------------------------- +-------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -99.2 | +| time/ | | +| fps | 321 | +| iterations | 127 | +| time_elapsed | 14171 | +| total_timesteps | 4551680 | +| train/ | | +| approx_kl | 0.311447 | +| clip_fraction | 0.0721 | +| clip_range | 0.155 | +| entropy_loss | -7.96 | +| explained_variance | 0.194 | +| learning_rate | 6e-05 | +| loss | 4.36 | +| n_updates | 1260 | +| policy_gradient_loss | 0.025 | +| value_loss | 9.4 | +-------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.36e+03 | +| ep_rew_mean | -109 | +| time/ | | +| fps | 320 | +| iterations | 128 | +| time_elapsed | 14291 | +| total_timesteps | 4587520 | +| train/ | | +| approx_kl | 0.3889818 | +| clip_fraction | 0.0736 | +| clip_range | 0.155 | +| entropy_loss | -7.89 | +| explained_variance | 0.201 | +| learning_rate | 6e-05 | +| loss | 2.15 | +| n_updates | 1270 | +| policy_gradient_loss | 0.0234 | +| value_loss | 11.9 | +--------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.33e+03 | +| ep_rew_mean | -101 | +| time/ | | +| fps | 320 | +| iterations | 129 | +| time_elapsed | 14405 | +| total_timesteps | 4623360 | +| train/ | | +| approx_kl | 0.3869719 | +| clip_fraction | 0.0722 | +| clip_range | 0.155 | +| entropy_loss | -7.94 | +| explained_variance | 0.218 | +| learning_rate | 6e-05 | +| loss | 0.791 | +| n_updates | 1280 | +| policy_gradient_loss | 0.0855 | +| value_loss | 10.1 | +--------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.35e+03 | +| ep_rew_mean | -110 | +| time/ | | +| fps | 320 | +| iterations | 130 | +| time_elapsed | 14519 | +| total_timesteps | 4659200 | +| train/ | | +| approx_kl | 0.4129661 | +| clip_fraction | 0.0907 | +| clip_range | 0.155 | +| entropy_loss | -7.94 | +| explained_variance | 0.181 | +| learning_rate | 6e-05 | +| loss | 1.6 | +| n_updates | 1290 | +| policy_gradient_loss | 0.0309 | +| value_loss | 16.1 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -108 | +| time/ | | +| fps | 320 | +| iterations | 131 | +| time_elapsed | 14631 | +| total_timesteps | 4695040 | +| train/ | | +| approx_kl | 0.40856624 | +| clip_fraction | 0.0743 | +| clip_range | 0.155 | +| entropy_loss | -7.91 | +| explained_variance | 0.228 | +| learning_rate | 6e-05 | +| loss | 0.0513 | +| n_updates | 1300 | +| policy_gradient_loss | 0.0213 | +| value_loss | 11.4 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.25e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 320 | +| iterations | 132 | +| time_elapsed | 14742 | +| total_timesteps | 4730880 | +| train/ | | +| approx_kl | 0.32232064 | +| clip_fraction | 0.0699 | +| clip_range | 0.155 | +| entropy_loss | -7.82 | +| explained_variance | 0.226 | +| learning_rate | 6e-05 | +| loss | 2.34 | +| n_updates | 1310 | +| policy_gradient_loss | 0.0267 | +| value_loss | 9.5 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.24e+03 | +| ep_rew_mean | -138 | +| time/ | | +| fps | 320 | +| iterations | 133 | +| time_elapsed | 14858 | +| total_timesteps | 4766720 | +| train/ | | +| approx_kl | 0.36457273 | +| clip_fraction | 0.0725 | +| clip_range | 0.155 | +| entropy_loss | -7.88 | +| explained_variance | 0.233 | +| learning_rate | 6e-05 | +| loss | 2.28 | +| n_updates | 1320 | +| policy_gradient_loss | 0.0233 | +| value_loss | 13.1 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.3e+03 | +| ep_rew_mean | -143 | +| time/ | | +| fps | 320 | +| iterations | 134 | +| time_elapsed | 14969 | +| total_timesteps | 4802560 | +| train/ | | +| approx_kl | 0.37729052 | +| clip_fraction | 0.0805 | +| clip_range | 0.155 | +| entropy_loss | -7.83 | +| explained_variance | 0.237 | +| learning_rate | 6e-05 | +| loss | 0.926 | +| n_updates | 1330 | +| policy_gradient_loss | 0.0275 | +| value_loss | 12 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.31e+03 | +| ep_rew_mean | -150 | +| time/ | | +| fps | 320 | +| iterations | 135 | +| time_elapsed | 15081 | +| total_timesteps | 4838400 | +| train/ | | +| approx_kl | 0.26841652 | +| clip_fraction | 0.0684 | +| clip_range | 0.155 | +| entropy_loss | -7.91 | +| explained_variance | 0.282 | +| learning_rate | 6e-05 | +| loss | 1.26 | +| n_updates | 1340 | +| policy_gradient_loss | 0.0345 | +| value_loss | 8.77 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -146 | +| time/ | | +| fps | 320 | +| iterations | 136 | +| time_elapsed | 15194 | +| total_timesteps | 4874240 | +| train/ | | +| approx_kl | 0.38375458 | +| clip_fraction | 0.0603 | +| clip_range | 0.155 | +| entropy_loss | -7.99 | +| explained_variance | 0.196 | +| learning_rate | 6e-05 | +| loss | 7.85 | +| n_updates | 1350 | +| policy_gradient_loss | 0.0208 | +| value_loss | 11.5 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.32e+03 | +| ep_rew_mean | -149 | +| time/ | | +| fps | 320 | +| iterations | 137 | +| time_elapsed | 15305 | +| total_timesteps | 4910080 | +| train/ | | +| approx_kl | 0.49587908 | +| clip_fraction | 0.0631 | +| clip_range | 0.155 | +| entropy_loss | -7.96 | +| explained_variance | 0.196 | +| learning_rate | 6e-05 | +| loss | 8.14 | +| n_updates | 1360 | +| policy_gradient_loss | 0.0247 | +| value_loss | 10.5 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.37e+03 | +| ep_rew_mean | -137 | +| time/ | | +| fps | 320 | +| iterations | 138 | +| time_elapsed | 15418 | +| total_timesteps | 4945920 | +| train/ | | +| approx_kl | 0.7668628 | +| clip_fraction | 0.0773 | +| clip_range | 0.155 | +| entropy_loss | -7.82 | +| explained_variance | 0.247 | +| learning_rate | 6e-05 | +| loss | 2.83 | +| n_updates | 1370 | +| policy_gradient_loss | 0.0227 | +| value_loss | 12.9 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.43e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 320 | +| iterations | 139 | +| time_elapsed | 15531 | +| total_timesteps | 4981760 | +| train/ | | +| approx_kl | 0.34270757 | +| clip_fraction | 0.0768 | +| clip_range | 0.155 | +| entropy_loss | -7.82 | +| explained_variance | 0.13 | +| learning_rate | 6e-05 | +| loss | 0.79 | +| n_updates | 1380 | +| policy_gradient_loss | 0.0259 | +| value_loss | 20 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.4e+03 | +| ep_rew_mean | -126 | +| time/ | | +| fps | 320 | +| iterations | 140 | +| time_elapsed | 15641 | +| total_timesteps | 5017600 | +| train/ | | +| approx_kl | 0.5019565 | +| clip_fraction | 0.0815 | +| clip_range | 0.155 | +| entropy_loss | -7.71 | +| explained_variance | 0.311 | +| learning_rate | 6e-05 | +| loss | 1.58 | +| n_updates | 1390 | +| policy_gradient_loss | 0.0215 | +| value_loss | 7.63 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.34e+03 | +| ep_rew_mean | -117 | +| time/ | | +| fps | 320 | +| iterations | 141 | +| time_elapsed | 15751 | +| total_timesteps | 5053440 | +| train/ | | +| approx_kl | 0.62975854 | +| clip_fraction | 0.0772 | +| clip_range | 0.155 | +| entropy_loss | -7.87 | +| explained_variance | 0.298 | +| learning_rate | 6e-05 | +| loss | 1.16 | +| n_updates | 1400 | +| policy_gradient_loss | 0.0212 | +| value_loss | 9.34 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.38e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 320 | +| iterations | 142 | +| time_elapsed | 15860 | +| total_timesteps | 5089280 | +| train/ | | +| approx_kl | 0.42187455 | +| clip_fraction | 0.0763 | +| clip_range | 0.155 | +| entropy_loss | -7.92 | +| explained_variance | 0.243 | +| learning_rate | 6e-05 | +| loss | 0.0562 | +| n_updates | 1410 | +| policy_gradient_loss | 0.026 | +| value_loss | 11.1 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -112 | +| time/ | | +| fps | 320 | +| iterations | 143 | +| time_elapsed | 15972 | +| total_timesteps | 5125120 | +| train/ | | +| approx_kl | 0.41300878 | +| clip_fraction | 0.0712 | +| clip_range | 0.155 | +| entropy_loss | -7.95 | +| explained_variance | 0.217 | +| learning_rate | 6e-05 | +| loss | 1.55 | +| n_updates | 1420 | +| policy_gradient_loss | 0.0201 | +| value_loss | 10.5 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.44e+03 | +| ep_rew_mean | -114 | +| time/ | | +| fps | 320 | +| iterations | 144 | +| time_elapsed | 16080 | +| total_timesteps | 5160960 | +| train/ | | +| approx_kl | 0.5569242 | +| clip_fraction | 0.0822 | +| clip_range | 0.155 | +| entropy_loss | -7.73 | +| explained_variance | 0.266 | +| learning_rate | 6e-05 | +| loss | 33 | +| n_updates | 1430 | +| policy_gradient_loss | 0.0315 | +| value_loss | 9.46 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -119 | +| time/ | | +| fps | 321 | +| iterations | 145 | +| time_elapsed | 16188 | +| total_timesteps | 5196800 | +| train/ | | +| approx_kl | 0.53122234 | +| clip_fraction | 0.0719 | +| clip_range | 0.155 | +| entropy_loss | -7.82 | +| explained_variance | 0.186 | +| learning_rate | 6e-05 | +| loss | 11.7 | +| n_updates | 1440 | +| policy_gradient_loss | 0.0229 | +| value_loss | 11.7 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.42e+03 | +| ep_rew_mean | -125 | +| time/ | | +| fps | 321 | +| iterations | 146 | +| time_elapsed | 16299 | +| total_timesteps | 5232640 | +| train/ | | +| approx_kl | 0.74737495 | +| clip_fraction | 0.069 | +| clip_range | 0.155 | +| entropy_loss | -7.9 | +| explained_variance | 0.253 | +| learning_rate | 6e-05 | +| loss | 0.321 | +| n_updates | 1450 | +| policy_gradient_loss | 0.024 | +| value_loss | 8.96 | +---------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -128 | +| time/ | | +| fps | 321 | +| iterations | 147 | +| time_elapsed | 16407 | +| total_timesteps | 5268480 | +| train/ | | +| approx_kl | 0.48857084 | +| clip_fraction | 0.074 | +| clip_range | 0.155 | +| entropy_loss | -7.88 | +| explained_variance | 0.219 | +| learning_rate | 6e-05 | +| loss | 1.87 | +| n_updates | 1460 | +| policy_gradient_loss | 0.0244 | +| value_loss | 10.8 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.43e+03 | +| ep_rew_mean | -129 | +| time/ | | +| fps | 321 | +| iterations | 148 | +| time_elapsed | 16514 | +| total_timesteps | 5304320 | +| train/ | | +| approx_kl | 0.7808695 | +| clip_fraction | 0.0811 | +| clip_range | 0.155 | +| entropy_loss | -7.75 | +| explained_variance | 0.225 | +| learning_rate | 6e-05 | +| loss | 0.597 | +| n_updates | 1470 | +| policy_gradient_loss | 0.0207 | +| value_loss | 13.5 | +--------------------------------------- +---------------------------------------- +| rollout/ | | +| ep_len_mean | 2.45e+03 | +| ep_rew_mean | -137 | +| time/ | | +| fps | 321 | +| iterations | 149 | +| time_elapsed | 16627 | +| total_timesteps | 5340160 | +| train/ | | +| approx_kl | 0.73379165 | +| clip_fraction | 0.0797 | +| clip_range | 0.155 | +| entropy_loss | -7.79 | +| explained_variance | 0.26 | +| learning_rate | 6e-05 | +| loss | 0.554 | +| n_updates | 1480 | +| policy_gradient_loss | 0.0295 | +| value_loss | 8.54 | +---------------------------------------- +--------------------------------------- +| rollout/ | | +| ep_len_mean | 2.41e+03 | +| ep_rew_mean | -123 | +| time/ | | +| fps | 321 | +| iterations | 150 | +| time_elapsed | 16738 | +| total_timesteps | 5376000 | +| train/ | | +| approx_kl | 0.6530856 | +| clip_fraction | 0.0916 | +| clip_range | 0.155 | +| entropy_loss | -7.55 | +| explained_variance | 0.334 | +| learning_rate | 6e-05 | +| loss | 18.9 | +| n_updates | 1490 | +| policy_gradient_loss | 0.0353 | +| value_loss | 8.39 | +--------------------------------------- \ No newline at end of file diff --git a/004_custom_policy/custom_cnn.py b/004_custom_policy/custom_cnn.py new file mode 100644 index 0000000..9ef0a3b --- /dev/null +++ b/004_custom_policy/custom_cnn.py @@ -0,0 +1,35 @@ +import torch.nn as nn + +def conv2d_custom_init(in_channels, out_channels, kernel_size=3, stride=1, padding=1, bias=False): + conv = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias) + nn.init.xavier_uniform_(conv.weight) + return conv + +def custom_conv2d(in_channels, out_channels, kernel_size=3, stride=1, padding=1, bias=False): + return nn.Sequential( + conv2d_custom_init(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias) + nn.Relu(), + nn.MaxPool2d((2, 2)) + ) + +# Custom feature extractor (CNN) +class CustomCNN(nn.Module): + def __init__(self, num_frames, num_moves, num_attacks): + super(CustomCNN, self).__init__() + self.num_moves = num_moves + self.num_attacks = num_attacks + self.cnn = nn.Sequential( + nn.Conv2d(4, 32, kernel_size=5, stride=2, padding=0), + nn.ReLU(), + nn.Conv2d(32, 64, kernel_size=5, stride=2, padding=0), + nn.ReLU(), + nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=0), + nn.ReLU(), + nn.Flatten(), + nn.Linear(16384, self.features_dim), + nn.ReLU() + ) + + def forward(self, observations: torch.Tensor) -> torch.Tensor: + return self.cnn(observations) + \ No newline at end of file