parameters: (self,
                 skewness=0.,
                 tailweight=1.,
                 event_ndims=0,
                 validate_args=False,
                 name="sinh_arcsinh")
docstring: Instantiates the `SinhArcsinh` bijector.
  
      Args:
        skewness:  Skewness parameter.  Float-type `Tensor`.
        tailweight:  Tailweight parameter.  Positive `Tensor` of same `dtype` as
          `skewness`
          and broadcastable `shape`.
        event_ndims: Python scalar indicating the number of dimensions associated
          with a particular draw from the distribution.
        validate_args: Python `bool` indicating whether arguments should be
          checked for correctness.
        name: Python `str` name given to ops managed by this object.
docstring_summary: Instantiates the `SinhArcsinh` bijector.
docstring_tokens: Instantiates the SinhArcsinh bijector .
function: def __init__(self,
                 skewness=0.,
                 tailweight=1.,
                 event_ndims=0,
                 validate_args=False,
                 name="sinh_arcsinh"):
      """Instantiates the `SinhArcsinh` bijector.
  
      Args:
        skewness:  Skewness parameter.  Float-type `Tensor`.
        tailweight:  Tailweight parameter.  Positive `Tensor` of same `dtype` as
          `skewness`
          and broadcastable `shape`.
        event_ndims: Python scalar indicating the number of dimensions associated
          with a particular draw from the distribution.
        validate_args: Python `bool` indicating whether arguments should be
          checked for correctness.
        name: Python `str` name given to ops managed by this object.
      """
      self._graph_parents = []
      self._name = name
      self._validate_args = validate_args
      with self._name_scope("init", values=[skewness, tailweight]):
        self._skewness = ops.convert_to_tensor(skewness, name="skewness")
        self._tailweight = ops.convert_to_tensor(tailweight, name="tailweight")
        check_ops.assert_same_float_dtype([self._skewness, self._tailweight])
        if validate_args:
          self._tailweight = control_flow_ops.with_dependencies([
              check_ops.assert_positive(
                  self._tailweight,
                  message="Argument tailweight was not positive")
          ], self._tailweight)
      super(SinhArcsinh, self).__init__(
          event_ndims=event_ndims, validate_args=validate_args, name=name)
function_tokens: def __init__ ( self , skewness = 0. , tailweight = 1. , event_ndims = 0 , validate_args = False , name = "sinh_arcsinh" ) : self . _graph_parents = [ ] self . _name = name self . _validate_args = validate_args with self . _name_scope ( "init" , values = [ skewness , tailweight ] ) : self . _skewness = ops . convert_to_tensor ( skewness , name = "skewness" ) self . _tailweight = ops . convert_to_tensor ( tailweight , name = "tailweight" ) check_ops . assert_same_float_dtype ( [ self . _skewness , self . _tailweight ] ) if validate_args : self . _tailweight = control_flow_ops . with_dependencies ( [ check_ops . assert_positive ( self . _tailweight , message = "Argument tailweight was not positive" ) ] , self . _tailweight ) super ( SinhArcsinh , self ) . __init__ ( event_ndims = event_ndims , validate_args = validate_args , name = name )