class_docstr: A base distribution object.
  
  This distribution is inherited by all the other distributions.
class_docstr_tok: ["A","base","distribution","object",".","This","distribution","is","inherited","by","all","the","other","distributions","."]
code: def __init__(self, inertia, frozen, check_data):
      super(Distribution, self).__init__()
      self._device = _cast_as_parameter([0.0])
  
      _check_parameter(
          inertia, "inertia", min_value=0, max_value=1, ndim=0
      )
      _check_parameter(
          frozen, "frozen", value_set=[True, False], ndim=0
      )
      _check_parameter(
          check_data, "check_data", value_set=[True, False], ndim=0
      )
  
      self.register_buffer("inertia", _cast_as_tensor(inertia))
      self.register_buffer("frozen", _cast_as_tensor(frozen))
      self.register_buffer("check_data", _cast_as_tensor(check_data))
  
      self._initialized = False
  
imports: import torch
  from .._utils import _cast_as_tensor
  from .._utils import _update_parameter
  from .._utils import _cast_as_parameter
  from .._utils import _check_parameter
  from .._utils import _reshape_weights
label_desc: Use image node_id 1 to create a new Distribution object from inherited base classes: torch.nn with example: obj = Distribution(inertia, frozen, check_data)