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64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
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from opencompass.multimodal.models.minigpt_4 import MiniGPT4SEEDBenchPromptConstructor # noqa
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# dataloader settings
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image_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', 'answer', 'choices', 'data_type', 'question_type_id',
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'index', 'data_path', 'question_id'
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])
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]
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video_pipeline = [
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dict(type='mmaction.Resize', scale=(224, 224), interpolation='bicubic'),
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dict(type='mmaction.CenterCrop', crop_size=224),
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dict(type='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', 'answer', 'choices', 'data_type', 'question_type_id',
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'index', 'data_path', 'question_id'
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])
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]
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dataset = dict(
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type='opencompass.SEEDBenchDataset',
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ann_file='data/seedbench/SEED-Bench.json',
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cc3m_path='data/seedbench/SEED-Bench-image',
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sthv2_path='data/seedbench/sthv2/videos',
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epic_kitchens_path='data/seedbench/3h91syskeag572hl6tvuovwv4d/videos/test',
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breakfast_path='data/seedbench/BreakfastII_15fps_qvga_sync',
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image_pipeline=image_pipeline,
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video_pipeline=video_pipeline,
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only_image=True)
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minigpt_4_seedbench_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',
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shuffle=False))
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# model settings
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minigpt_4_seedbench_model = dict(
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type='minigpt-4',
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low_resource=False,
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llama_model='/path/to/vicuna/',
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prompt_constructor=dict(type=MiniGPT4SEEDBenchPromptConstructor,
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image_prompt='###Human: <Img><ImageHere></Img>',
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reply_prompt='###Assistant:'),
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post_processor=None,
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mode='loss')
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# evaluation settings
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minigpt_4_seedbench_evaluator = [dict(type='opencompass.SEEDBenchAcc')]
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minigpt_4_load_from = '/path/to/prerained_minigpt4_7b.pth'
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