mirror of
https://github.com/Vision-CAIR/MiniGPT-4.git
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43 lines
3.2 KiB
Python
43 lines
3.2 KiB
Python
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import json
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import os
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import pandas as pd
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_route/mix_coco_gqa_ao_cocap_tcap_raw_QformerMoE_Post_Route_lnout_lr5e5_3ex3b_2loss_005_top6layer_textinqf_15epo_0314/20240314230/"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_route/mix_coco_gqa_ao_cocap_tcap_raw_Qformer_base_lr5e5_10epo_0316/20240316192"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_raw_QformerMoE_Post_Route_Universal_lnout_lr5e5_3ex3b_2loss_005_top6layer_textinqf_10epo_0317/20240317165/"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr5e5_3ex3b_2loss_005_top6layer_textinqf_12epo_0317/20240317165/"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr5e5_3ex3b_2loss_005_top6layer_textinqf_10epo_0318/20240318145/"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_tcap_raw_Qformer_base_lr5e5_10epo_0318/20240318113"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr5e5_4ex4b_2loss_005_top6layer_textinqf_10epo_0319/20240319110"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr5e5_4ex4b_2loss_005_top6layer_textinqf_10epo_0319/20240319110/"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr6e5_3ex3b_2loss_005_top6layer_textinqf_10epo_0319/20240319105"
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# path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_tcap_raw_Qformer_base_lr5e5_10epo_0320_instruct/20240320230/"
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path = "/mnt/pfs-guan-ssai/nlu/wanghanzi/experiments/blip2/vicuna7b/qformer_moe_uni_route/mix_coco_gqa_ao_cocap_textcap_raw_QformerMoE_Post_Route_Universal_lnout_lr3e5_3ex3b_2loss_005_top6layer_textinqf_10epo_0326/20240326134"
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modes = ['gqa','okvqa','vqav2','aokvqa']
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file_name = dict()
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data = dict()
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for mode in modes:
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file_name[mode] = os.path.join(path, f"evaluate_{mode}.txt")
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tmp = list()
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with open(file_name[mode], "r") as f:
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for line in f:
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tmp.append(json.loads(line))
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accs = [dd['agg_metrics'] for dd in tmp]
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data[mode] = accs
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print(data)
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df = pd.DataFrame(data)
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df.to_csv("/mnt/pfs-guan-ssai/nlu/wanghanzi/multimodal/PromptMoE/process_log/results.csv",index=False)
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print(df)
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modes = ['coco_cap','text_cap']
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for mode in modes:
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file_name[mode] = os.path.join(path, f"evaluate_{mode}.txt")
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tmp = list()
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with open(file_name[mode], "r") as f:
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for line in f:
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tmp.append(json.loads(line)["val"])
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df1 = pd.DataFrame(tmp)
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df1.to_csv("/mnt/pfs-guan-ssai/nlu/wanghanzi/multimodal/PromptMoE/process_log/results_{}.csv".format(mode),index=False)
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print("\n",df1)
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