42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
_base_ = [
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'../_base_/models/segformer_mit-b0.py',
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'../_base_/datasets/cityscapes_1024x1024.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
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]
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crop_size = (1024, 1024)
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data_preprocessor = dict(size=crop_size)
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model = dict(
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data_preprocessor=data_preprocessor,
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backbone=dict(
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init_cfg=dict(type='Pretrained', checkpoint='pretrain/mit_b0.pth')),
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test_cfg=dict(mode='slide', crop_size=(1024, 1024), stride=(768, 768)))
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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(
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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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'head': dict(lr_mult=10.)
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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=1, num_workers=4)
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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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