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Feature/lint #16

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merged 2 commits into from
May 13, 2022
Merged

Feature/lint #16

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d760d52
Fix lint
May 13, 2022
48dd814
Fix cfg
May 13, 2022
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141 changes: 0 additions & 141 deletions configs/mmtune/_base_/space/mmseg_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -230,143 +230,6 @@
test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(256, 256)),
)

ocrnet_hr18 = dict(
_delete_=True,
type='CascadeEncoderDecoder',
num_stages=2,
pretrained='open-mmlab://msra/hrnetv2_w18',
backbone=dict(
type='HRNet',
norm_cfg=norm_cfg,
norm_eval=False,
extra=dict(
stage1=dict(
num_modules=1,
num_branches=1,
block='BOTTLENECK',
num_blocks=(4, ),
num_channels=(64, ),
),
stage2=dict(
num_modules=1,
num_branches=2,
block='BASIC',
num_blocks=(4, 4),
num_channels=(18, 36),
),
stage3=dict(
num_modules=4,
num_branches=3,
block='BASIC',
num_blocks=(4, 4, 4),
num_channels=(18, 36, 72),
),
stage4=dict(
num_modules=3,
num_branches=4,
block='BASIC',
num_blocks=(4, 4, 4, 4),
num_channels=(18, 36, 72, 144),
),
),
),
decode_head=[
dict(
type='FCNHead',
in_channels=[18, 36, 72, 144],
channels=sum([18, 36, 72, 144]),
in_index=(0, 1, 2, 3),
input_transform='resize_concat',
kernel_size=1,
num_convs=1,
concat_input=False,
dropout_ratio=-1,
num_classes=3,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4),
),
dict(
type='OCRHead',
in_channels=[18, 36, 72, 144],
in_index=(0, 1, 2, 3),
input_transform='resize_concat',
channels=512,
ocr_channels=256,
dropout_ratio=-1,
num_classes=3,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
),
],
# model training and testing settings
train_cfg=dict(),
test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(256, 256)),
)

fcn_hr18 = dict(
_delete_=True,
type='EncoderDecoder',
pretrained='open-mmlab://msra/hrnetv2_w18',
backbone=dict(
type='HRNet',
norm_cfg=norm_cfg,
norm_eval=False,
extra=dict(
stage1=dict(
num_modules=1,
num_branches=1,
block='BOTTLENECK',
num_blocks=(4, ),
num_channels=(64, ),
),
stage2=dict(
num_modules=1,
num_branches=2,
block='BASIC',
num_blocks=(4, 4),
num_channels=(18, 36),
),
stage3=dict(
num_modules=4,
num_branches=3,
block='BASIC',
num_blocks=(4, 4, 4),
num_channels=(18, 36, 72),
),
stage4=dict(
num_modules=3,
num_branches=4,
block='BASIC',
num_blocks=(4, 4, 4, 4),
num_channels=(18, 36, 72, 144),
),
),
),
decode_head=dict(
type='FCNHead',
in_channels=[18, 36, 72, 144],
in_index=(0, 1, 2, 3),
channels=sum([18, 36, 72, 144]),
input_transform='resize_concat',
kernel_size=1,
num_convs=1,
concat_input=False,
dropout_ratio=-1,
num_classes=3,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
),
# model training and testing settings
train_cfg=dict(),
test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(256, 256)),
)

model = dict(
type='Choice',
categories=[
Expand All @@ -375,16 +238,12 @@
deeplabv3plus_r50_d8,
segformer_mit_b0,
fpn_r50,
ocrnet_hr18,
fcn_hr18,
],
alias=[
'pspnet_r50_d8',
'upernet_swin',
'deeplabv3plus_r50_d8',
'segformer_mit_b0',
'fpn_r50',
'ocrnet_hr18',
'fcn_hr18',
],
)
4 changes: 3 additions & 1 deletion configs/mmtune/mmseg_asynchb_nevergrad_pso.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,9 @@
space = {
'model': {{_base_.model}},
'optimizer': {{_base_.optimizer}},
'data.samples_per_gpu': {{_base_.batch_size}}
'data.samples_per_gpu': {{_base_.batch_size}},
'model.decode_head.num_classes': dict(type='Constant', value=21),
'model.auxiliary_head.num_classes': dict(type='Constant', value=21),
}

metric = 'val/mIoU'
Expand Down
2 changes: 0 additions & 2 deletions mmtune/mm/tasks/mmtrainbase.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,6 @@ def train_model(self, model: torch.nn.Module,
**kwargs) -> None:
pass


def contextaware_run(self, status, backend, *args, **kwargs) -> None:
from mmtune.mm import hooks # noqa F401
if backend == 'nccl' and os.getenv('NCCL_BLOCKING_WAIT') is None:
Expand All @@ -52,4 +51,3 @@ def create_trainable(self, backend: str = 'nccl') -> ray.tune.trainable:
num_workers=self.args.num_workers,
num_gpus_per_worker=self.args.num_cpus_per_worker,
num_cpus_per_worker=self.args.num_cpus_per_worker)

3 changes: 2 additions & 1 deletion mmtune/ray/spaces/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
from .builder import SPACES, build_space
from .choice import Choice
from .const import Constant

__all__ = ['SPACES', 'build_space', 'Choice']
__all__ = ['SPACES', 'build_space', 'Choice', 'Constant']
17 changes: 17 additions & 0 deletions mmtune/ray/spaces/const.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
from typing import Any, Optional

from mmtune.utils import ImmutableContainer
from .base import BaseSpace
from .builder import SPACES


@SPACES.register_module()
class Constant(BaseSpace):

def __init__(self,
value: Any,
alias: Optional[str] = None,
use_container: bool = True):
if use_container:
value = ImmutableContainer(value, alias)
self._space = value