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from typing import Dict, Any, Optional |
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import os |
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import sys |
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if not os.getcwd() in sys.path: |
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sys.path.append(os.getcwd()) |
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from torch.nn import Sequential |
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from register.register import Registry, build_from_cfg |
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def build_model_from_cfg(cfg, registry, default_args=None): |
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"""Build a PyTorch model from config dict(s). Different from |
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``build_from_cfg``, if cfg is a list, a ``nn.Sequential`` will be built. |
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Args: |
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cfg (dict, list[dict]): The config of modules, is is either a config |
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dict or a list of config dicts. If cfg is a list, a |
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the built modules will be wrapped with ``nn.Sequential``. |
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registry (:obj:`Registry`): A registry the module belongs to. |
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default_args (dict, optional): Default arguments to build the module. |
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Defaults to None. |
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Returns: |
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nn.Module: A built nn module. |
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""" |
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if isinstance(cfg, list): |
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modules = [ |
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build_from_cfg(cfg_, registry, default_args) for cfg_ in cfg |
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] |
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return Sequential(*modules) |
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else: |
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return build_from_cfg(cfg, registry, default_args) |
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MODELS = Registry('model', build_func=build_model_from_cfg) |
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HEADS = MODELS |
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BACKBONES = MODELS |
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def build_model(cfg: Dict, |
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model: Registry, |
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build_func=build_model_from_cfg, |
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default_args: Optional[Dict] = None) -> Any: |
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return build_func(cfg, model, default_args) |
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