parameters: (alpha=1, beta=1, shape=_Null, dtype=_Null, **kwargs)
return_statement: return _random_helper(_internal._random_gamma, _internal._sample_gamma,
                            [alpha, beta], shape, dtype, kwargs)
docstring: Draw random samples from a gamma distribution.
  
      Samples are distributed according to a gamma distribution parametrized
      by *alpha* (shape) and *beta* (scale).
  
      Parameters
      ----------
      alpha : float or Symbol, optional
          The shape of the gamma distribution. Should be greater than zero.
      beta : float or Symbol, optional
          The scale of the gamma distribution. Should be greater than zero.
          Default is equal to 1.
      shape : int or tuple of ints, optional
          The number of samples to draw. If shape is, e.g., `(m, n)` and `alpha` and
          `beta` are scalars, output shape will be `(m, n)`. If `alpha` and `beta`
          are Symbols with shape, e.g., `(x, y)`, then output will have shape
          `(x, y, m, n)`, where `m*n` samples are drawn for each `[alpha, beta)` pair.
      dtype : {'float16', 'float32', 'float64'}, optional
          Data type of output samples. Default is 'float32'
  
      Returns
      -------
      Symbol
          If input `shape` has dimensions, e.g., `(m, n)` and `alpha` and
          `beta` are scalars, returned Symbol will resolve to shape `(m, n)`. If `alpha`
          and `beta` are Symbols with shape, e.g., `(x, y)`, returned Symbol will resolve
          to shape `(x, y, m, n)`, where `m*n` samples are drawn for each `[alpha, beta)` pair.
docstring_summary: Draw random samples from a gamma distribution.
docstring_tokens: Draw random samples from a gamma distribution .
function: def gamma(alpha=1, beta=1, shape=_Null, dtype=_Null, **kwargs):
      """Draw random samples from a gamma distribution.
  
      Samples are distributed according to a gamma distribution parametrized
      by *alpha* (shape) and *beta* (scale).
  
      Parameters
      ----------
      alpha : float or Symbol, optional
          The shape of the gamma distribution. Should be greater than zero.
      beta : float or Symbol, optional
          The scale of the gamma distribution. Should be greater than zero.
          Default is equal to 1.
      shape : int or tuple of ints, optional
          The number of samples to draw. If shape is, e.g., `(m, n)` and `alpha` and
          `beta` are scalars, output shape will be `(m, n)`. If `alpha` and `beta`
          are Symbols with shape, e.g., `(x, y)`, then output will have shape
          `(x, y, m, n)`, where `m*n` samples are drawn for each `[alpha, beta)` pair.
      dtype : {'float16', 'float32', 'float64'}, optional
          Data type of output samples. Default is 'float32'
  
      Returns
      -------
      Symbol
          If input `shape` has dimensions, e.g., `(m, n)` and `alpha` and
          `beta` are scalars, returned Symbol will resolve to shape `(m, n)`. If `alpha`
          and `beta` are Symbols with shape, e.g., `(x, y)`, returned Symbol will resolve
          to shape `(x, y, m, n)`, where `m*n` samples are drawn for each `[alpha, beta)` pair.
      """
      return _random_helper(_internal._random_gamma, _internal._sample_gamma,
                            [alpha, beta], shape, dtype, kwargs)
function_tokens: def gamma ( alpha = 1 , beta = 1 , shape = _Null , dtype = _Null , * * kwargs ) : return _random_helper ( _internal . _random_gamma , _internal . _sample_gamma , [ alpha , beta ] , shape , dtype , kwargs )