33 lines
832 B
Python
33 lines
832 B
Python
# dataset settings
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dataset_type = 'ImageNet'
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data_root = 'data/imagenet/'
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data_preprocessor = dict(
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type='SelfSupDataPreprocessor',
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mean=[123.675, 116.28, 103.53],
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std=[58.395, 57.12, 57.375],
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to_rgb=True)
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train_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='RandomResizedCrop',
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scale=224,
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crop_ratio_range=(0.2, 1.0),
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backend='pillow',
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interpolation='bicubic'),
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dict(type='RandomFlip', prob=0.5),
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dict(type='PackInputs')
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]
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train_dataloader = dict(
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batch_size=512,
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num_workers=8,
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persistent_workers=True,
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sampler=dict(type='DefaultSampler', shuffle=True),
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collate_fn=dict(type='default_collate'),
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dataset=dict(
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type=dataset_type,
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data_root=data_root,
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split='train',
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pipeline=train_pipeline))
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