50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
_base_ = [
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'../_base_/models/twins_pcpvt-s_upernet.py',
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'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
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'../_base_/schedules/schedule_160k.py'
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]
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crop_size = (512, 512)
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data_preprocessor = dict(size=crop_size)
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checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/twins/alt_gvt_small_20220308-7e1c3695.pth' # noqa
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model = dict(
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data_preprocessor=data_preprocessor,
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backbone=dict(
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type='SVT',
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init_cfg=dict(type='Pretrained', checkpoint=checkpoint),
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embed_dims=[64, 128, 256, 512],
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num_heads=[2, 4, 8, 16],
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mlp_ratios=[4, 4, 4, 4],
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depths=[2, 2, 10, 4],
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windiow_sizes=[7, 7, 7, 7],
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norm_after_stage=True),
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decode_head=dict(in_channels=[64, 128, 256, 512]),
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auxiliary_head=dict(in_channels=256))
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optim_wrapper = dict(
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_delete_=True,
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type='OptimWrapper',
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optimizer=dict(
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type='AdamW', lr=0.00006, betas=(0.9, 0.999), weight_decay=0.01),
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paramwise_cfg=dict(custom_keys={
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'pos_block': dict(decay_mult=0.),
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'norm': dict(decay_mult=0.)
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}))
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param_scheduler = [
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dict(
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type='LinearLR', start_factor=1e-6, by_epoch=False, begin=0, end=1500),
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dict(
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type='PolyLR',
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eta_min=0.0,
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power=1.0,
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begin=1500,
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end=160000,
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by_epoch=False,
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)
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]
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train_dataloader = dict(batch_size=2, num_workers=2)
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val_dataloader = dict(batch_size=1, num_workers=4)
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test_dataloader = val_dataloader
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