class_docstr: The upcoming root base class for Model, i.e. BaseModel
  --  Designed by ZiXin Sun
class_docstr_tok: ["The","upcoming","root","base","class","for","Model",",","i.e",".","BaseModel","--","Designed","by","ZiXin","Sun"]
code: def __init__(
      self,
      model: _typing.Optional[torch.nn.Module] = None,
      initialize: bool = False,
      hyper_parameter_space: _typing.Sequence[_typing.Any] = ...,
      hyper_parameter: _typing.Dict[str, _typing.Any] = ...,
      device: _typing.Union[str, torch.device] = ...,
  ):
      if type(initialize) != bool:
          raise TypeError
      super(_BaseModel, self).__init__(model, initialize, device)
      if hyper_parameter_space != Ellipsis and isinstance(
          hyper_parameter_space, _typing.Sequence
      ):
          self.__hyper_parameter_space: _typing.Sequence[
              _typing.Dict[str, _typing.Any]
          ] = hyper_parameter_space
      else:
          self.__hyper_parameter_space: _typing.Sequence[
              _typing.Dict[str, _typing.Any]
          ] = []
      if hyper_parameter != Ellipsis and isinstance(
          hyper_parameter, dict
      ):
          self.__hyper_parameter: _typing.Dict[
              str, _typing.Any
          ] = hyper_parameter
      else:
          self.__hyper_parameter: _typing.Dict[str, _typing.Any] = {}
  
imports: import copy
  import logging
  import typing
  import torch
  import torch.nn.functional
  from copy import deepcopy
  from autogl.module.hpo.auto_module import AutoModule
label_desc: Use image node_id 9 to create a new _BaseModel object from inherited base classes: _BaseBaseModel, BaseAutoModel with example: obj = _BaseModel(model, initialize, hyper_parameter_space, hyper_parameter, device)