parameters: (self,
                 batch_ndims=None,
                 event_ndims=None,
                 parameters=None,
                 is_constant_jacobian=False,
                 validate_args=False,
                 dtype=None,
                 name=None)
docstring: Constructs Bijector.
  
      A `Bijector` transforms random variables into new random variables.
  
      Examples:
  
      ```python
      # Create the Y = g(X) = X transform which operates on 4-Tensors of vectors.
      identity = Identity(batch_ndims=4, event_ndims=1)
  
      # Create the Y = g(X) = exp(X) transform which operates on matrices.
      exp = Exp(batch_ndims=0, event_ndims=2)
      ```
  
      See `Bijector` subclass docstring for more details and specific examples.
  
      Args:
        batch_ndims: number of dimensions associated with batch coordinates.
        event_ndims: number of dimensions associated with event coordinates.
        parameters: Dictionary of parameters used by this `Bijector`
        is_constant_jacobian: `Boolean` indicating that the Jacobian is not a
          function of the input.
        validate_args: `Boolean`, default `False`.  Whether to validate input with
          asserts. If `validate_args` is `False`, and the inputs are invalid,
          correct behavior is not guaranteed.
        dtype: `tf.dtype` supported by this `Bijector`. `None` means dtype is not
          enforced.
        name: The name to give Ops created by the initializer.
docstring_summary: Constructs Bijector.
docstring_tokens: Constructs Bijector .
function: def __init__(self,
                 batch_ndims=None,
                 event_ndims=None,
                 parameters=None,
                 is_constant_jacobian=False,
                 validate_args=False,
                 dtype=None,
                 name=None):
      """Constructs Bijector.
  
      A `Bijector` transforms random variables into new random variables.
  
      Examples:
  
      ```python
      # Create the Y = g(X) = X transform which operates on 4-Tensors of vectors.
      identity = Identity(batch_ndims=4, event_ndims=1)
  
      # Create the Y = g(X) = exp(X) transform which operates on matrices.
      exp = Exp(batch_ndims=0, event_ndims=2)
      ```
  
      See `Bijector` subclass docstring for more details and specific examples.
  
      Args:
        batch_ndims: number of dimensions associated with batch coordinates.
        event_ndims: number of dimensions associated with event coordinates.
        parameters: Dictionary of parameters used by this `Bijector`
        is_constant_jacobian: `Boolean` indicating that the Jacobian is not a
          function of the input.
        validate_args: `Boolean`, default `False`.  Whether to validate input with
          asserts. If `validate_args` is `False`, and the inputs are invalid,
          correct behavior is not guaranteed.
        dtype: `tf.dtype` supported by this `Bijector`. `None` means dtype is not
          enforced.
        name: The name to give Ops created by the initializer.
      """
      if batch_ndims is None or event_ndims is None:
        self._shaper = None  # Apparently subclass will create.
      else:
        self._shaper = _DistributionShape(
            batch_ndims=batch_ndims,
            event_ndims=event_ndims,
            validate_args=validate_args)
      self._parameters = parameters or {}
      self._is_constant_jacobian = is_constant_jacobian
      self._validate_args = validate_args
      self._dtype = dtype
      self._name = name or type(self).__name__
function_tokens: def __init__ ( self , batch_ndims = None , event_ndims = None , parameters = None , is_constant_jacobian = False , validate_args = False , dtype = None , name = None ) : if batch_ndims is None or event_ndims is None : self . _shaper = None # Apparently subclass will create. else : self . _shaper = _DistributionShape ( batch_ndims = batch_ndims , event_ndims = event_ndims , validate_args = validate_args ) self . _parameters = parameters or { } self . _is_constant_jacobian = is_constant_jacobian self . _validate_args = validate_args self . _dtype = dtype self . _name = name or type ( self ) . __name__