mirror of
https://github.com/open-mmlab/mmsegmentation.git
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2825efe378
* add DPT head * [fix] fix init error * use mmcv function * delete code * remove transpose clas * support NLC output shape * Delete post_process_layer.py * add unittest and docstring * rename variables * fix project error and add unittest * match dpt weights * add configs * fix vit pos_embed bug and dpt feature fusion bug * match vit output * fix gelu * minor change * update unitest * fix configs error * inference test * remove auxilary * use local pretrain * update training results * update yml * update fps and memory test * update doc * update readme * add yml * update doc * remove with_cp * update config * update docstring * remove dpt-l * add init_cfg and modify readme.md * Update dpt_vit-b16.py * zh-n README * use constructor instead of build function * prevent tensor being modified by ConvModule * fix unittest Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
33 lines
844 B
Python
33 lines
844 B
Python
_base_ = [
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'../_base_/models/dpt_vit-b16.py', '../_base_/datasets/ade20k.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
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]
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# AdamW optimizer, no weight decay for position embedding & layer norm
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# in backbone
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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(
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custom_keys={
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'pos_embed': dict(decay_mult=0.),
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'cls_token': 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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# By default, models are trained on 8 GPUs with 2 images per GPU
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data = dict(samples_per_gpu=2, workers_per_gpu=2)
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