test2 / mmseg /models /builder.py
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import warnings
from mmcv.utils import Registry, build_from_cfg
from torch import nn
BACKBONES = Registry('backbone')
NECKS = Registry('neck')
HEADS = Registry('head')
LOSSES = Registry('loss')
SEGMENTORS = Registry('segmentor')
def build(cfg, registry, default_args=None):
"""Build a module.
Args:
cfg (dict, list[dict]): The config of modules, is is either a dict
or a list of configs.
registry (:obj:`Registry`): A registry the module belongs to.
default_args (dict, optional): Default arguments to build the module.
Defaults to None.
Returns:
nn.Module: A built nn module.
"""
if isinstance(cfg, list):
modules = [
build_from_cfg(cfg_, registry, default_args) for cfg_ in cfg
]
return nn.Sequential(*modules)
else:
return build_from_cfg(cfg, registry, default_args)
def build_backbone(cfg):
"""Build backbone."""
return build(cfg, BACKBONES)
def build_neck(cfg):
"""Build neck."""
return build(cfg, NECKS)
def build_head(cfg):
"""Build head."""
return build(cfg, HEADS)
def build_loss(cfg):
"""Build loss."""
return build(cfg, LOSSES)
def build_segmentor(cfg, train_cfg=None, test_cfg=None):
"""Build segmentor."""
if train_cfg is not None or test_cfg is not None:
warnings.warn(
'train_cfg and test_cfg is deprecated, '
'please specify them in model', UserWarning)
assert cfg.get('train_cfg') is None or train_cfg is None, \
'train_cfg specified in both outer field and model field '
assert cfg.get('test_cfg') is None or test_cfg is None, \
'test_cfg specified in both outer field and model field '
return build(cfg, SEGMENTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))