[Refactor] Refactor all registries

mmseg/core/__init__.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from .builder import (OPTIMIZER_BUILDERS, build_optimizer,
-                      build_optimizer_constructor)
+from .builder import build_optimizer, build_optimizer_constructor
 from .evaluation import *  # noqa: F401, F403
 from .optimizers import *  # noqa: F401, F403
 from .seg import *  # noqa: F401, F403
 from .utils import *  # noqa: F401, F403
 
-__all__ = [
-    'OPTIMIZER_BUILDERS', 'build_optimizer', 'build_optimizer_constructor'
-]
+__all__ = ['build_optimizer', 'build_optimizer_constructor']

mmseg/core/builder.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
 
-from mmcv.runner.optimizer import OPTIMIZER_BUILDERS as MMCV_OPTIMIZER_BUILDERS
-from mmcv.utils import Registry, build_from_cfg
-
-OPTIMIZER_BUILDERS = Registry(
-    'optimizer builder', parent=MMCV_OPTIMIZER_BUILDERS)
+from mmseg.registry import OPTIMIZER_CONSTRUCTORS
 
 
 def build_optimizer_constructor(cfg):
     constructor_type = cfg.get('type')
-    if constructor_type in OPTIMIZER_BUILDERS:
-        return build_from_cfg(cfg, OPTIMIZER_BUILDERS)
-    elif constructor_type in MMCV_OPTIMIZER_BUILDERS:
-        return build_from_cfg(cfg, MMCV_OPTIMIZER_BUILDERS)
+    if constructor_type in OPTIMIZER_CONSTRUCTORS:
+        return OPTIMIZER_CONSTRUCTORS.build(cfg)
     else:
         raise KeyError(f'{constructor_type} is not registered '
                        'in the optimizer builder registry.')

mmseg/core/optimizers/layer_decay_optimizer_constructor.py

@@ -2,10 +2,11 @@
 import json
 import warnings
 
-from mmcv.runner import DefaultOptimizerConstructor, get_dist_info
+from mmengine.dist import get_dist_info
+from mmengine.optim import DefaultOptimizerConstructor
 
+from mmseg.registry import OPTIMIZER_CONSTRUCTORS
 from mmseg.utils import get_root_logger
-from ..builder import OPTIMIZER_BUILDERS
 
 
 def get_layer_id_for_convnext(var_name, max_layer_id):
@@ -99,7 +100,7 @@ def get_layer_id_for_vit(var_name, max_layer_id):
         return max_layer_id - 1
 
 
-@OPTIMIZER_BUILDERS.register_module()
+@OPTIMIZER_CONSTRUCTORS.register_module()
 class LearningRateDecayOptimizerConstructor(DefaultOptimizerConstructor):
     """Different learning rates are set for different layers of backbone.
 
@@ -185,7 +186,7 @@ class LearningRateDecayOptimizerConstructor(DefaultOptimizerConstructor):
         params.extend(parameter_groups.values())
 
 
-@OPTIMIZER_BUILDERS.register_module()
+@OPTIMIZER_CONSTRUCTORS.register_module()
 class LayerDecayOptimizerConstructor(LearningRateDecayOptimizerConstructor):
     """Different learning rates are set for different layers of backbone.
 

mmseg/core/seg/builder.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from mmcv.utils import Registry, build_from_cfg
+import warnings
 
-PIXEL_SAMPLERS = Registry('pixel sampler')
+from mmseg.registry import TASK_UTILS
+
+PIXEL_SAMPLERS = TASK_UTILS
 
 
 def build_pixel_sampler(cfg, **default_args):
     """Build pixel sampler for segmentation map."""
-    return build_from_cfg(cfg, PIXEL_SAMPLERS, default_args)
+    warnings.warn(
+        '``build_pixel_sampler`` would be deprecated soon, please use '
+        '``mmseg.registry.TASK_UTILS.build()`` ')
+    return TASK_UTILS.build(cfg, default_args=default_args)

mmseg/datasets/ade.py

@@ -5,7 +5,7 @@ import mmcv
 import numpy as np
 from PIL import Image
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/builder.py

@@ -8,9 +8,10 @@ import numpy as np
 import torch
 from mmcv.parallel import collate
 from mmcv.runner import get_dist_info
-from mmcv.utils import Registry, build_from_cfg, digit_version
+from mmcv.utils import digit_version
 from torch.utils.data import DataLoader
 
+from mmseg.registry import DATASETS, TRANSFORMS
 from .samplers import DistributedSampler
 
 if platform.system() != 'Windows':
@@ -22,8 +23,7 @@ if platform.system() != 'Windows':
     soft_limit = min(max(4096, base_soft_limit), hard_limit)
     resource.setrlimit(resource.RLIMIT_NOFILE, (soft_limit, hard_limit))
 
-DATASETS = Registry('dataset')
-PIPELINES = Registry('pipeline')
+PIPELINES = TRANSFORMS
 
 
 def _concat_dataset(cfg, default_args=None):
@@ -82,7 +82,7 @@ def build_dataset(cfg, default_args=None):
             cfg.get('split', None), (list, tuple)):
         dataset = _concat_dataset(cfg, default_args)
     else:
-        dataset = build_from_cfg(cfg, DATASETS, default_args)
+        dataset = DATASETS.build(cfg, default_args=default_args)
 
     return dataset
 

mmseg/datasets/chase_db1.py

 # Copyright (c) OpenMMLab. All rights reserved.
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/cityscapes.py

@@ -6,7 +6,7 @@ import numpy as np
 from mmcv.utils import print_log
 from PIL import Image
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/coco_stuff.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/custom.py

@@ -10,8 +10,8 @@ from prettytable import PrettyTable
 from torch.utils.data import Dataset
 
 from mmseg.core import eval_metrics, intersect_and_union, pre_eval_to_metrics
+from mmseg.registry import DATASETS
 from mmseg.utils import get_root_logger
-from .builder import DATASETS
 from .pipelines import Compose, LoadAnnotations
 
 

mmseg/datasets/dark_zurich.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .cityscapes import CityscapesDataset
 
 

mmseg/datasets/dataset_wrappers.py

@@ -6,10 +6,10 @@ from itertools import chain
 
 import mmcv
 import numpy as np
-from mmcv.utils import build_from_cfg, print_log
+from mmcv.utils import print_log
 from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
 
-from .builder import DATASETS, PIPELINES
+from mmseg.registry import DATASETS, TRANSFORMS
 from .cityscapes import CityscapesDataset
 
 
@@ -225,7 +225,7 @@ class MultiImageMixDataset:
         for transform in pipeline:
             if isinstance(transform, dict):
                 self.pipeline_types.append(transform['type'])
-                transform = build_from_cfg(transform, PIPELINES)
+                transform = TRANSFORMS.build(transform)
                 self.pipeline.append(transform)
             else:
                 raise TypeError('pipeline must be a dict')

mmseg/datasets/drive.py

 # Copyright (c) OpenMMLab. All rights reserved.
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/hrf.py

 # Copyright (c) OpenMMLab. All rights reserved.
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/isaid.py

@@ -3,8 +3,8 @@
 import mmcv
 from mmcv.utils import print_log
 
+from mmseg.registry import DATASETS
 from ..utils import get_root_logger
-from .builder import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/isprs.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/loveda.py

@@ -5,7 +5,7 @@ import mmcv
 import numpy as np
 from PIL import Image
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/night_driving.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .cityscapes import CityscapesDataset
 
 

mmseg/datasets/pascal_context.py

 # Copyright (c) OpenMMLab. All rights reserved.
 
-from .builder import DATASETS
+from mmseg.registry import DATASETS
 from .custom import CustomDataset
 
 

mmseg/datasets/pipelines/compose.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import collections
 
-from mmcv.utils import build_from_cfg
+from mmseg.registry import TRANSFORMS
 
-from ..builder import PIPELINES
 
-
-@PIPELINES.register_module()
+@TRANSFORMS.register_module()
 class Compose(object):
     """Compose multiple transforms sequentially.
 
@@ -20,7 +18,7 @@ class Compose(object):
         self.transforms = []
         for transform in transforms:
             if isinstance(transform, dict):
-                transform = build_from_cfg(transform, PIPELINES)
+                transform = TRANSFORMS.build(transform)
                 self.transforms.append(transform)
             elif callable(transform):
                 self.transforms.append(transform)