28 lines
852 B
Python
28 lines
852 B
Python
_base_ = [
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'../_base_/models/repmlp-base_224.py',
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'../_base_/datasets/imagenet_bs64_mixer_224.py',
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'../_base_/schedules/imagenet_bs4096_AdamW.py',
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'../_base_/default_runtime.py'
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]
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default_hooks = dict(optimizer=dict(grad_clip=dict(max_norm=1.0)))
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model = dict(backbone=dict(img_size=256))
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='Resize',
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scale_factor=(256 * 256 // 224, -1),
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keep_ratio=True,
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backend='pillow'),
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dict(type='CenterCrop', crop_size=256),
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dict(type='Normalize', **img_norm_cfg),
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dict(type='ImageToTensor', keys=['img']),
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dict(type='Collect', keys=['img'])
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]
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data = dict(
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val=dict(pipeline=test_pipeline), test=dict(pipeline=test_pipeline))
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