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https://github.com/open-mmlab/mmpretrain.git
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a05c79e806
* [Refactor] Move transforms in mmselfsup to mmpretrain. * Update transform docs and configs. And register some mmcv transforms in mmpretrain. * Fix missing transform wrapper. * update selfsup transforms * Fix UT * Fix UT * update gaussianblur inconfigs --------- Co-authored-by: fangyixiao18 <fangyx18@hotmail.com>
46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
_base_ = [
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'../_base_/datasets/imagenet_bs32.py',
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'../_base_/schedules/imagenet_bs256.py',
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'../_base_/default_runtime.py',
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]
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# model settings
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model = dict(
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type='ImageClassifier',
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backbone=dict(type='CSPResNet', depth=50),
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neck=dict(type='GlobalAveragePooling'),
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head=dict(
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type='LinearClsHead',
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num_classes=1000,
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in_channels=1024,
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loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
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))
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# dataset settings
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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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backend='pillow',
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interpolation='bicubic'),
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dict(type='RandomFlip', prob=0.5, direction='horizontal'),
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dict(type='PackInputs'),
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]
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='ResizeEdge',
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scale=288,
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edge='short',
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backend='pillow',
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interpolation='bicubic'),
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dict(type='CenterCrop', crop_size=256),
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dict(type='PackInputs'),
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]
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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test_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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