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| # Copyright (c) OpenMMLab. All rights reserved. | |
| # This is a BETA new format config file, and the usage may change recently. | |
| from mmengine.dataset import DefaultSampler, default_collate | |
| from mmpretrain.datasets import (BEiTMaskGenerator, ColorJitter, ImageNet, | |
| LoadImageFromFile, PackInputs, RandomFlip, | |
| RandomResizedCropAndInterpolationWithTwoPic) | |
| from mmpretrain.models import TwoNormDataPreprocessor | |
| dataset_type = ImageNet | |
| data_root = 'data/imagenet/' | |
| data_preprocessor = dict( | |
| type=TwoNormDataPreprocessor, | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| second_mean=[127.5, 127.5, 127.5], | |
| second_std=[127.5, 127.5, 127.5], | |
| to_rgb=True) | |
| train_pipeline = [ | |
| dict(type=LoadImageFromFile), | |
| dict( | |
| type=ColorJitter, brightness=0.4, contrast=0.4, saturation=0.4, | |
| hue=0.), | |
| dict(type=RandomFlip, prob=0.5, direction='horizontal'), | |
| dict( | |
| type=RandomResizedCropAndInterpolationWithTwoPic, | |
| size=224, | |
| second_size=224, | |
| interpolation='bicubic', | |
| second_interpolation='bicubic', | |
| scale=(0.2, 1.0)), | |
| dict( | |
| type=BEiTMaskGenerator, | |
| input_size=(14, 14), | |
| num_masking_patches=75, | |
| max_num_patches=75, | |
| min_num_patches=16), | |
| dict(type=PackInputs) | |
| ] | |
| train_dataloader = dict( | |
| batch_size=256, | |
| num_workers=8, | |
| persistent_workers=True, | |
| sampler=dict(type=DefaultSampler, shuffle=True), | |
| collate_fn=dict(type=default_collate), | |
| dataset=dict( | |
| type=dataset_type, | |
| data_root=data_root, | |
| split='train', | |
| pipeline=train_pipeline)) | |