parameters: (self,
                 rate,
                 validate_args=False,
                 allow_nan_stats=True,
                 name="Poisson")
docstring: Initialize a batch of Poisson distributions.
  
      Args:
        rate: Floating point tensor, the rate parameter of the
          distribution(s). `rate` must be positive.
        validate_args: Python `bool`, default `False`. When `True` distribution
          parameters are checked for validity despite possibly degrading runtime
          performance. When `False` invalid inputs may silently render incorrect
          outputs.
        allow_nan_stats: Python `bool`, default `True`. When `True`, statistics
          (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
          result is undefined. When `False`, an exception is raised if one or
          more of the statistic's batch members are undefined.
        name: Python `str` name prefixed to Ops created by this class.
docstring_summary: Initialize a batch of Poisson distributions.
docstring_tokens: Initialize a batch of Poisson distributions .
function: def __init__(self,
                 rate,
                 validate_args=False,
                 allow_nan_stats=True,
                 name="Poisson"):
      """Initialize a batch of Poisson distributions.
  
      Args:
        rate: Floating point tensor, the rate parameter of the
          distribution(s). `rate` must be positive.
        validate_args: Python `bool`, default `False`. When `True` distribution
          parameters are checked for validity despite possibly degrading runtime
          performance. When `False` invalid inputs may silently render incorrect
          outputs.
        allow_nan_stats: Python `bool`, default `True`. When `True`, statistics
          (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
          result is undefined. When `False`, an exception is raised if one or
          more of the statistic's batch members are undefined.
        name: Python `str` name prefixed to Ops created by this class.
      """
      parameters = locals()
      with ops.name_scope(name, values=[rate]):
        with ops.control_dependencies([check_ops.assert_positive(rate)] if
                                      validate_args else []):
          self._rate = array_ops.identity(rate, name="rate")
      super(Poisson, self).__init__(
          dtype=self._rate.dtype,
          reparameterization_type=distribution.NOT_REPARAMETERIZED,
          validate_args=validate_args,
          allow_nan_stats=allow_nan_stats,
          parameters=parameters,
          graph_parents=[self._rate],
          name=name)
function_tokens: def __init__ ( self , rate , validate_args = False , allow_nan_stats = True , name = "Poisson" ) : parameters = locals ( ) with ops . name_scope ( name , values = [ rate ] ) : with ops . control_dependencies ( [ check_ops . assert_positive ( rate ) ] if validate_args else [ ] ) : self . _rate = array_ops . identity ( rate , name = "rate" ) super ( Poisson , self ) . __init__ ( dtype = self . _rate . dtype , reparameterization_type = distribution . NOT_REPARAMETERIZED , validate_args = validate_args , allow_nan_stats = allow_nan_stats , parameters = parameters , graph_parents = [ self . _rate ] , name = name )