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import copy |
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import torch |
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from easydict import EasyDict |
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from ding.utils import import_module, MODEL_REGISTRY |
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def create_model(cfg: EasyDict) -> torch.nn.Module: |
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""" |
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Overview: |
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Create a neural network model according to the given EasyDict-type ``cfg``. |
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Arguments: |
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- cfg: (:obj:`EasyDict`): User's model config. The key ``import_name`` is \ |
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used to import modules, and they key ``type`` is used to indicate the model. |
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Returns: |
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- (:obj:`torch.nn.Module`): The created neural network model. |
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Examples: |
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>>> cfg = EasyDict({ |
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>>> 'import_names': ['ding.model.template.q_learning'], |
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>>> 'type': 'dqn', |
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>>> 'obs_shape': 4, |
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>>> 'action_shape': 2, |
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>>> }) |
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>>> model = create_model(cfg) |
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.. tip:: |
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This method will not modify the ``cfg`` , it will deepcopy the ``cfg`` and then modify it. |
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""" |
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cfg = copy.deepcopy(cfg) |
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import_module(cfg.pop('import_names', [])) |
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return MODEL_REGISTRY.build(cfg.pop("type"), **cfg) |
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