parameters: (x1, x2, out=None, **kwargs)
return_statement: return _mx_nd_np.gcd(x1, x2, out=out)
docstring: Returns the greatest common divisor of ``|x1|`` and ``|x2|``
  
      Parameters
      ----------
      x1, x2 : ndarrays or scalar values
          The arrays for computing greatest common divisor. If x1.shape != x2.shape,
          they must be broadcastable to a common shape (which may be the shape of
          one or the other).
  
      out : ndarray or None, optional
          A location into which the result is stored. If provided, it must have a shape
          that the inputs broadcast to. If not provided or None, a freshly-allocated array
          is returned.
  
      Returns
      -------
      y : ndarray or scalar
          The greatest common divisor of the absolute value of the inputs
          This is a scalar if both `x1` and `x2` are scalars.
  
      See Also
      --------
      gcd : The lowest common multiple
  
      Examples
      --------
      >>> np.gcd(12, 20)
      4
      >>> np.gcd(np.arange(6, dtype=int), 20)
      array([20,  1,  2,  1,  4,  5], dtype=int64)
docstring_summary: Returns the greatest common divisor of ``|x1|`` and ``|x2|``
docstring_tokens: Returns the greatest common divisor of |x1| and |x2|
function: def gcd(x1, x2, out=None, **kwargs):
      """
      Returns the greatest common divisor of ``|x1|`` and ``|x2|``
  
      Parameters
      ----------
      x1, x2 : ndarrays or scalar values
          The arrays for computing greatest common divisor. If x1.shape != x2.shape,
          they must be broadcastable to a common shape (which may be the shape of
          one or the other).
  
      out : ndarray or None, optional
          A location into which the result is stored. If provided, it must have a shape
          that the inputs broadcast to. If not provided or None, a freshly-allocated array
          is returned.
  
      Returns
      -------
      y : ndarray or scalar
          The greatest common divisor of the absolute value of the inputs
          This is a scalar if both `x1` and `x2` are scalars.
  
      See Also
      --------
      gcd : The lowest common multiple
  
      Examples
      --------
      >>> np.gcd(12, 20)
      4
      >>> np.gcd(np.arange(6, dtype=int), 20)
      array([20,  1,  2,  1,  4,  5], dtype=int64)
      """
      return _mx_nd_np.gcd(x1, x2, out=out)
function_tokens: def gcd ( x1 , x2 , out = None , * * kwargs ) : return _mx_nd_np . gcd ( x1 , x2 , out = out )