36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
_base_ = [
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'../_base_/models/bisenetv1_r18-d32.py',
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'../_base_/datasets/coco-stuff164k.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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model = dict(
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data_preprocessor=data_preprocessor,
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backbone=dict(
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context_channels=(512, 1024, 2048),
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spatial_channels=(256, 256, 256, 512),
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out_channels=1024,
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backbone_cfg=dict(type='ResNet', depth=50)),
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decode_head=dict(in_channels=1024, channels=1024, num_classes=171),
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auxiliary_head=[
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dict(in_channels=512, channels=256, num_classes=171),
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dict(in_channels=512, channels=256, num_classes=171),
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])
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param_scheduler = [
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dict(type='LinearLR', by_epoch=False, start_factor=0.1, begin=0, end=1000),
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dict(
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type='PolyLR',
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eta_min=1e-4,
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power=0.9,
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begin=1000,
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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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optimizer = dict(type='SGD', lr=0.005, momentum=0.9, weight_decay=0.0005)
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optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer)
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train_dataloader = dict(batch_size=4, 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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