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mmsegmentation/configs/setr/setr_pup_512x512_160k_b16_ade20k.py

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[Feature] Official implementation of SETR (#531) * Adjust vision transformer backbone architectures; * Add DropPath, trunc_normal_ for VisionTransformer implementation; * Add class token buring intermediate period and remove it during final period; * Fix some parameters loss bug; * * Store intermediate token features and impose no processes on them; * Remove class token and reshape entire token feature from NLC to NCHW; * Fix some doc error * Add a arg for VisionTransformer backbone to control if input class token into transformer; * Add stochastic depth decay rule for DropPath; * * Fix output bug when input_cls_token=False; * Add related unit test; * Re-implement of SETR * Add two head -- SETRUPHead (Naive, PUP) & SETRMLAHead (MLA); * * Modify some docs of heads of SETR; * Add MLA auxiliary head of SETR; * * Modify some arg of setr heads; * Add unit test for setr heads; * * Add 768x768 cityscapes dataset config; * Add Backbone: SETR -- Backbone: MLA, PUP, Naive; * Add SETR cityscapes training & testing config; * * Fix the low code coverage of unit test about heads of setr; * Remove some rebundant error capture; * * Add pascal context dataset & ade20k dataset config; * Modify auxiliary head relative config; * Modify folder structure. * add setr * modify vit * Fix the test_cfg arg position; * Fix some learning schedule bug; * optimize setr code * Add arg: final_reshape to control if converting output feature information from NLC to NCHW; * Fix the default value of final_reshape; * Modify arg: final_reshape to arg: out_shape; * Fix some unit test bug; * Add MLA neck; * Modify setr configs to add MLA neck; * Modify MLA decode head to remove rebundant structure; * Remove some rebundant files. * * Fix the code style bug; * Remove some rebundant files; * Modify some unit tests of SETR; * Ignoring CityscapesCoarseDataset and MapillaryDataset. * Fix the activation function loss bug; * Fix the img_size bug of SETR_PUP_ADE20K * * Fix the lint bug of transformers.py; * Add mla neck unit test; * Convert vit of setr out shape from NLC to NCHW. * * Modify Resize action of data pipeline; * Fix deit related bug; * Set find_unused_parameters=False for pascal context dataset; * Remove arg: find_unused_parameters which is False by default. * Error auxiliary head of PUP deit * Remove the minimal restrict of slide inference. * Modify doc string of Resize * Seperate this part of code to a new PR #544 * * Remove some rebundant codes; * Modify unit tests of SETR heads; * Fix the tuple in_channels of mla_deit. * Modify code style * Move detailed definition of auxiliary head into model config dict; * Add some setr config for default cityscapes.py; * Fix the doc string of SETR head; * Modify implementation of SETR Heads * Remove setr aux head and use fcn head to replace it; * Remove arg: img_size and remove last interpolate op of heads; * Rename arg: conv3x3_conv1x1 to kernel_size of SETRUPHead; * non-square input support for setr heads * Modify config argument for above commits * Remove norm_layer argument of SETRMLAHead * Add mla_align_corners for MLAModule interpolate * [Refactor]Refactor of SETRMLAHead * Modify Head implementation; * Modify Head unit test; * Modify related config file; * [Refactor]MLA Neck * Fix config bug * [Refactor]SETR Naive Head and SETR PUP Head * [Fix]Fix the lack of arg: act_cfg and arg: norm_cfg * Fix config error * Refactor of SETR MLA, Naive, PUP heads. * Modify some attribute name of SETR Heads. * Modify setr configs to adapt new vit code. * Fix trunc_normal_ bug * Parameters init adjustment. * Remove redundant doc string of SETRUPHead * Fix pretrained bug * [Fix] Fix vit init bug * Add some vit unit tests * Modify module import * Remove norm from PatchEmbed * Fix pretrain weights bug * Modify pretrained judge * Fix some gradient backward bugs. * Add some unit tests to improve code cov * Fix init_weights of setr up head * Add DropPath in FFN * Finish benchmark of SETR 1. Add benchmark information into README.MD of SETR; 2. Fix some name bugs of vit; * Remove DropPath implementation and use DropPath from mmcv. * Modify out_indices arg * Fix out_indices bug. * Remove cityscapes base dataset config. Co-authored-by: sennnnn <201730271412@mail.scut.edu.cn> Co-authored-by: CuttlefishXuan <zhaoxinxuan1997@gmail.com>
2021-06-24 00:39:29 +08:00
_base_ = [
'../_base_/models/setr_pup.py', '../_base_/datasets/ade20k.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
]
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
[Enhancement] Delete convert function and add instruction to ViT/Swin README.md (#791) * delete convert function and add instruction to README.md * unified model convert and README * remove url * fix import error * fix unittest * rename pretrain * rename vit and deit pretrain * Update upernet_deit-b16_512x512_160k_ade20k.py * Update upernet_deit-b16_512x512_80k_ade20k.py * Update upernet_deit-b16_ln_mln_512x512_160k_ade20k.py * Update upernet_deit-b16_mln_512x512_160k_ade20k.py * Update upernet_deit-s16_512x512_160k_ade20k.py * Update upernet_deit-s16_512x512_80k_ade20k.py * Update upernet_deit-s16_ln_mln_512x512_160k_ade20k.py * Update upernet_deit-s16_mln_512x512_160k_ade20k.py Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com> Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
2021-08-26 06:00:41 +08:00
pretrained='pretrain/vit_large_patch16_384.pth',
[Feature] Official implementation of SETR (#531) * Adjust vision transformer backbone architectures; * Add DropPath, trunc_normal_ for VisionTransformer implementation; * Add class token buring intermediate period and remove it during final period; * Fix some parameters loss bug; * * Store intermediate token features and impose no processes on them; * Remove class token and reshape entire token feature from NLC to NCHW; * Fix some doc error * Add a arg for VisionTransformer backbone to control if input class token into transformer; * Add stochastic depth decay rule for DropPath; * * Fix output bug when input_cls_token=False; * Add related unit test; * Re-implement of SETR * Add two head -- SETRUPHead (Naive, PUP) & SETRMLAHead (MLA); * * Modify some docs of heads of SETR; * Add MLA auxiliary head of SETR; * * Modify some arg of setr heads; * Add unit test for setr heads; * * Add 768x768 cityscapes dataset config; * Add Backbone: SETR -- Backbone: MLA, PUP, Naive; * Add SETR cityscapes training & testing config; * * Fix the low code coverage of unit test about heads of setr; * Remove some rebundant error capture; * * Add pascal context dataset & ade20k dataset config; * Modify auxiliary head relative config; * Modify folder structure. * add setr * modify vit * Fix the test_cfg arg position; * Fix some learning schedule bug; * optimize setr code * Add arg: final_reshape to control if converting output feature information from NLC to NCHW; * Fix the default value of final_reshape; * Modify arg: final_reshape to arg: out_shape; * Fix some unit test bug; * Add MLA neck; * Modify setr configs to add MLA neck; * Modify MLA decode head to remove rebundant structure; * Remove some rebundant files. * * Fix the code style bug; * Remove some rebundant files; * Modify some unit tests of SETR; * Ignoring CityscapesCoarseDataset and MapillaryDataset. * Fix the activation function loss bug; * Fix the img_size bug of SETR_PUP_ADE20K * * Fix the lint bug of transformers.py; * Add mla neck unit test; * Convert vit of setr out shape from NLC to NCHW. * * Modify Resize action of data pipeline; * Fix deit related bug; * Set find_unused_parameters=False for pascal context dataset; * Remove arg: find_unused_parameters which is False by default. * Error auxiliary head of PUP deit * Remove the minimal restrict of slide inference. * Modify doc string of Resize * Seperate this part of code to a new PR #544 * * Remove some rebundant codes; * Modify unit tests of SETR heads; * Fix the tuple in_channels of mla_deit. * Modify code style * Move detailed definition of auxiliary head into model config dict; * Add some setr config for default cityscapes.py; * Fix the doc string of SETR head; * Modify implementation of SETR Heads * Remove setr aux head and use fcn head to replace it; * Remove arg: img_size and remove last interpolate op of heads; * Rename arg: conv3x3_conv1x1 to kernel_size of SETRUPHead; * non-square input support for setr heads * Modify config argument for above commits * Remove norm_layer argument of SETRMLAHead * Add mla_align_corners for MLAModule interpolate * [Refactor]Refactor of SETRMLAHead * Modify Head implementation; * Modify Head unit test; * Modify related config file; * [Refactor]MLA Neck * Fix config bug * [Refactor]SETR Naive Head and SETR PUP Head * [Fix]Fix the lack of arg: act_cfg and arg: norm_cfg * Fix config error * Refactor of SETR MLA, Naive, PUP heads. * Modify some attribute name of SETR Heads. * Modify setr configs to adapt new vit code. * Fix trunc_normal_ bug * Parameters init adjustment. * Remove redundant doc string of SETRUPHead * Fix pretrained bug * [Fix] Fix vit init bug * Add some vit unit tests * Modify module import * Remove norm from PatchEmbed * Fix pretrain weights bug * Modify pretrained judge * Fix some gradient backward bugs. * Add some unit tests to improve code cov * Fix init_weights of setr up head * Add DropPath in FFN * Finish benchmark of SETR 1. Add benchmark information into README.MD of SETR; 2. Fix some name bugs of vit; * Remove DropPath implementation and use DropPath from mmcv. * Modify out_indices arg * Fix out_indices bug. * Remove cityscapes base dataset config. Co-authored-by: sennnnn <201730271412@mail.scut.edu.cn> Co-authored-by: CuttlefishXuan <zhaoxinxuan1997@gmail.com>
2021-06-24 00:39:29 +08:00
backbone=dict(img_size=(512, 512), drop_rate=0.),
decode_head=dict(num_classes=150),
auxiliary_head=[
dict(
type='SETRUPHead',
in_channels=1024,
channels=256,
in_index=0,
num_classes=150,
dropout_ratio=0,
norm_cfg=norm_cfg,
act_cfg=dict(type='ReLU'),
num_convs=2,
kernel_size=3,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
dict(
type='SETRUPHead',
in_channels=1024,
channels=256,
in_index=1,
num_classes=150,
dropout_ratio=0,
norm_cfg=norm_cfg,
act_cfg=dict(type='ReLU'),
num_convs=2,
kernel_size=3,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
dict(
type='SETRUPHead',
in_channels=1024,
channels=256,
in_index=2,
num_classes=150,
dropout_ratio=0,
norm_cfg=norm_cfg,
act_cfg=dict(type='ReLU'),
num_convs=2,
kernel_size=3,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
],
test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(341, 341)),
)
optimizer = dict(
lr=0.001,
weight_decay=0.0,
paramwise_cfg=dict(custom_keys={'head': dict(lr_mult=10.)}))
# num_gpus: 8 -> batch_size: 16
data = dict(samples_per_gpu=2)
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