parameters: (self,
                 df,
                 validate_args=False,
                 allow_nan_stats=True,
                 name="Chi2")
docstring: Construct Chi2 distributions with parameter `df`.
  
      Args:
        df: Floating point tensor, the degrees of freedom of the
          distribution(s). `df` must contain only positive values.
        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: Construct Chi2 distributions with parameter `df`.
docstring_tokens: Construct Chi2 distributions with parameter df .
function: def __init__(self,
                 df,
                 validate_args=False,
                 allow_nan_stats=True,
                 name="Chi2"):
      """Construct Chi2 distributions with parameter `df`.
  
      Args:
        df: Floating point tensor, the degrees of freedom of the
          distribution(s). `df` must contain only positive values.
        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()
      # Even though all stats of chi2 are defined for valid parameters, this is
      # not true in the parent class "gamma."  therefore, passing
      # allow_nan_stats=True
      # through to the parent class results in unnecessary asserts.
      with ops.name_scope(name, values=[df]):
        self._df = ops.convert_to_tensor(df, name="df")
        super(Chi2, self).__init__(
            concentration=0.5 * self._df,
            rate=constant_op.constant(0.5, dtype=self._df.dtype),
            validate_args=validate_args,
            allow_nan_stats=allow_nan_stats,
            name=name)
      self._parameters = parameters
function_tokens: def __init__ ( self , df , validate_args = False , allow_nan_stats = True , name = "Chi2" ) : parameters = locals ( ) # Even though all stats of chi2 are defined for valid parameters, this is # not true in the parent class "gamma."  therefore, passing # allow_nan_stats=True # through to the parent class results in unnecessary asserts. with ops . name_scope ( name , values = [ df ] ) : self . _df = ops . convert_to_tensor ( df , name = "df" ) super ( Chi2 , self ) . __init__ ( concentration = 0.5 * self . _df , rate = constant_op . constant ( 0.5 , dtype = self . _df . dtype ) , validate_args = validate_args , allow_nan_stats = allow_nan_stats , name = name ) self . _parameters = parameters