44 lines
1.2 KiB
Python
44 lines
1.2 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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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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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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optimizer = dict(
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_delete_=True,
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type='AdamW',
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lr=0.00006,
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betas=(0.9, 0.999),
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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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lr_config = dict(
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_delete_=True,
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policy='poly',
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warmup='linear',
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warmup_iters=1500,
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warmup_ratio=1e-6,
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power=1.0,
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min_lr=0.0,
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by_epoch=False)
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data = dict(samples_per_gpu=2, workers_per_gpu=2)
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