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46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
# dataloader settings
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val_pipeline = [
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dict(type='mmpretrain.torchvision/Resize',
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size=(224, 224),
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interpolation=3),
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dict(type='mmpretrain.torchvision/ToTensor'),
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dict(type='mmpretrain.torchvision/Normalize',
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mean=(0.48145466, 0.4578275, 0.40821073),
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std=(0.26862954, 0.26130258, 0.27577711)),
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dict(type='mmpretrain.PackInputs',
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algorithm_keys=[
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'question', 'category', 'l2-category', 'context',
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'index', 'options_dict', 'options', 'split'
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])
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]
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dataset = dict(type='opencompass.MMBench',
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data_file='data/mmbench/mmbench_test_20230712.tsv',
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pipeline=val_pipeline)
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dataloader = dict(batch_size=1,
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num_workers=4,
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dataset=dataset,
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collate_fn=dict(type='pseudo_collate'),
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sampler=dict(type='DefaultSampler', shuffle=False))
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# model settings
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model = dict(
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type='blip2-vicuna-instruct-mmbench',
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freeze_vit=True,
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low_resource=False,
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llm_model='/path/to/vicuna-7b/',
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sys_prompt= # noqa: E251
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'###Human: What is the capital of China? There are several options:\nA. Beijing\nB. Shanghai\nC. Guangzhou\nD. Shenzhen\n###Assistant: A\n'
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)
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# evaluation settings
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evaluator = [
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dict(
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type='opencompass.DumpResults',
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save_path= # noqa: E251
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'work_dirs/instructblip_vicuna7b/instructblipvicuna_mmbench.xlsx')
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]
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load_from = '/path/to/instruct_blip_vicuna7b_trimmed.pth' # noqa
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