from torchdistill.common.main_util import load_ckpt
from torchdistill.models.official import get_semantic_segmentation_model
from torchdistill.models.registry import get_model
from torchdistill.models.registry import register_model_class, register_model_func
from sc2bench.models.segmentation.base import check_if_updatable_segmentation_model
SEGMENTATION_MODEL_CLASS_DICT = dict()
SEGMENTATION_MODEL_FUNC_DICT = dict()
[docs]def register_segmentation_model_class(cls):
"""
Registers a semantic segmentation model class.
:param cls: semantic segmentation model to be registered
:type cls: class
:return: registered semantic segmentation model class
:rtype: class
"""
SEGMENTATION_MODEL_CLASS_DICT[cls.__name__] = cls
register_model_class(cls)
return cls
[docs]def register_segmentation_model_func(func):
"""
Registers a function to build a semantic segmentation model.
:param func: function to build a semantic segmentation model to be registered
:type func: typing.Callable
:return: registered function
:rtype: typing.Callable
"""
SEGMENTATION_MODEL_FUNC_DICT[func.__name__] = func
register_model_func(func)
return func
[docs]def get_segmentation_model(cls_or_func_name, **kwargs):
"""
Gets a semantic segmentation model.
:param cls_or_func_name: model class or function name
:type cls_or_func_name: str
:return: semantic segmentation model
:rtype: nn.Module or None
"""
if cls_or_func_name in SEGMENTATION_MODEL_CLASS_DICT:
return SEGMENTATION_MODEL_CLASS_DICT[cls_or_func_name](**kwargs)
elif cls_or_func_name in SEGMENTATION_MODEL_FUNC_DICT:
return SEGMENTATION_MODEL_FUNC_DICT[cls_or_func_name](**kwargs)
return None
[docs]def load_segmentation_model(model_config, device, strict=True):
"""
Loads a semantic segmentation model.
:param model_config: model configuration
:type model_config: dict
:param device: device
:type device: torch.device or str
:param strict: whether to strictly enforce that the keys in state_dict match
the keys returned by this module's `state_dict()` function.
:type strict: bool
:return: semantic segmentation model
:rtype: nn.Module
"""
model = get_semantic_segmentation_model(model_config)
model_name = model_config['name']
if model is None:
model = get_segmentation_model(model_name, **model_config['params'])
if model is None:
repo_or_dir = model_config.get('repo_or_dir', None)
model = get_model(model_name, repo_or_dir, **model_config['params'])
if model_config.get('update_before_ckpt', False) and check_if_updatable_segmentation_model(model):
model.update()
ckpt_file_path = model_config['ckpt']
load_ckpt(ckpt_file_path, model=model, strict=strict)
return model.to(device)