35 lines
812 B
Python
35 lines
812 B
Python
_base_ = [
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'../_base_/datasets/imagenet_bs64_swin_384.py',
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'../_base_/schedules/imagenet_bs1024_adamw_swin.py',
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'../_base_/default_runtime.py',
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]
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model = dict(
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type='ImageClassifier',
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backbone=dict(
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type='XCiT',
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patch_size=8,
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embed_dims=192,
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depth=12,
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num_heads=4,
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mlp_ratio=4,
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qkv_bias=True,
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layer_scale_init_value=1.0,
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tokens_norm=True,
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out_type='cls_token',
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),
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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=192,
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loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
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),
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train_cfg=dict(augments=[
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dict(type='Mixup', alpha=0.8),
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dict(type='CutMix', alpha=1.0),
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]),
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)
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# dataset settings
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train_dataloader = dict(batch_size=128)
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