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from typing import Any, Optional, Union
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import inspect
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import torch.nn as nn
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import torch
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from ..configs.config.config import Config, ConfigDict
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from .registry import Registry
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from ..utils.manager import ManagerMixin
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TORCH_VERSION = torch.__version__
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def build_from_cfg(
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cfg: Union[dict, ConfigDict, Config],
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registry: Registry,
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default_args: Optional[Union[dict, ConfigDict, Config]] = None) -> Any:
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"""Build a module from config dict when it is a class configuration, or
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call a function from config dict when it is a function configuration.
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If the global variable default scope (:obj:`DefaultScope`) exists,
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:meth:`build` will firstly get the responding registry and then call
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its own :meth:`build`.
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At least one of the ``cfg`` and ``default_args`` contains the key "type",
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which should be either str or class. If they all contain it, the key
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in ``cfg`` will be used because ``cfg`` has a high priority than
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``default_args`` that means if a key exists in both of them, the value of
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the key will be ``cfg[key]``. They will be merged first and the key "type"
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will be popped up and the remaining keys will be used as initialization
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arguments.
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Args:
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cfg (dict or ConfigDict or Config): Config dict. It should at least
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contain the key "type".
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registry (:obj:`Registry`): The registry to search the type from.
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default_args (dict or ConfigDict or Config, optional): Default
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initialization arguments. Defaults to None.
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Returns:
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object: The constructed object.
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"""
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if not isinstance(cfg, (dict, ConfigDict, Config)):
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raise TypeError(
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f'cfg should be a dict, ConfigDict or Config, but got {type(cfg)}')
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if 'type' not in cfg:
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if default_args is None or 'type' not in default_args:
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raise KeyError(
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'`cfg` or `default_args` must contain the key "type", '
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f'but got {cfg}\n{default_args}')
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if not isinstance(registry, Registry):
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raise TypeError('registry must be a mmengine.Registry object, '
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f'but got {type(registry)}')
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if not (isinstance(default_args,
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(dict, ConfigDict, Config)) or default_args is None):
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raise TypeError(
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'default_args should be a dict, ConfigDict, Config or None, '
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f'but got {type(default_args)}')
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args = cfg.copy()
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if default_args is not None:
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for name, value in default_args.items():
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args.setdefault(name, value)
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scope = args.pop('_scope_', None)
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with registry.switch_scope_and_registry(scope) as registry:
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obj_type = args.pop('type')
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if isinstance(obj_type, str):
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obj_cls = registry.get(obj_type)
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if obj_cls is None:
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raise KeyError(
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f'{obj_type} is not in the {registry.scope}::{registry.name} registry. '
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f'Please check whether the value of `{obj_type}` is '
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)
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elif callable(obj_type):
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obj_cls = obj_type
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else:
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raise TypeError(
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f'type must be a str or valid type, but got {type(obj_type)}')
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if inspect.isclass(obj_cls) and \
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issubclass(obj_cls, ManagerMixin):
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obj = obj_cls.get_instance(**args)
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else:
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obj = obj_cls(**args)
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return obj
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def build_model_from_cfg(
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cfg: Union[dict, ConfigDict, Config],
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registry: Registry,
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default_args: Optional[Union[dict, 'ConfigDict', 'Config']] = None
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) -> 'nn.Module':
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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, which is either a config
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dict or a list of config dicts. If cfg is a list, the built
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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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from ..model.base_module import Sequential
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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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class SyncBatchNorm(torch.nn.SyncBatchNorm):
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def _check_input_dim(self, input):
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if TORCH_VERSION == 'parrots':
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if input.dim() < 2:
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raise ValueError(
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f'expected at least 2D input (got {input.dim()}D input)')
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else:
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super()._check_input_dim(input) |
