parameters: (a, axis=None, out=None, keepdims=False)
return_statement: return _mx_nd_np.argmax(a, axis, out, keepdims)
docstring: r"""
      Returns the indices of the maximum values along an axis.
  
      Parameters
      ----------
      a : ndarray
          Input array. Only support ndarrays of dtype `float16`, `float32`, and `float64`.
      axis : int, optional
          By default, the index is into the flattened array, otherwise
          along the specified axis.
      out : ndarray or None, optional
          If provided, the result will be inserted into this array. It should
          be of the appropriate shape and dtype.
      keepdims : bool
          If True, the reduced axes (dimensions) must be included in the result as
          singleton dimensions, and, accordingly, the result must be compatible with
          the input array. Otherwise, if False, the reduced axes (dimensions) must
          not be included in the result. Default: False .
  
      Returns
      -------
      index_array : ndarray of indices whose dtype is same as the input ndarray.
          Array of indices into the array. It has the same shape as `a.shape`
          with the dimension along `axis` removed.
  
      .. note::
         ``keepdims`` param is part of request in data-api-standard
         <https://data-apis.org/array-api/latest/API_specification/generated/signatures.searching_functions.argmax.html>`_,
         which is not the parameter in official NumPy
  
         In case of multiple occurrences of the maximum values, the indices
         corresponding to the first occurrence are returned.
  
         This function differs from the original `numpy.argmax
         <https://numpy.org/doc/stable/reference/generated/numpy.argmax.html>`_ in
         the following aspects:
  
         * Input type does not support Python native iterables(list, tuple, ...).
         * ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be
           the same as the expected output.
         * ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the
           same as the expected output.
         * ``out`` param does not support scalar input case.
  
      Examples
      --------
      >>> a = np.arange(6).reshape(2,3) + 10
      >>> a
      array([[10., 11., 12.],
             [13., 14., 15.]])
      >>> np.argmax(a)
      array(5.)
      >>> np.argmax(a, axis=0)
      array([1., 1., 1.])
      >>> np.argmax(a, axis=1)
      array([2., 2.])
  
      >>> b = np.arange(6)
      >>> b[1] = 5
      >>> b
      array([0., 5., 2., 3., 4., 5.])
      >>> np.argmax(b)  # Only the first occurrence is returned.
      array(1.)
  
      Specify ``out`` ndarray:
  
      >>> a = np.arange(6).reshape(2,3) + 10
      >>> b = np.zeros((2,))
      >>> np.argmax(a, axis=1, out=b)
      array([2., 2.])
      >>> b
      array([2., 2.])
docstring_summary: r"""
      Returns the indices of the maximum values along an axis.
docstring_tokens: r Returns the indices of the maximum values along an axis .
function: def argmax(a, axis=None, out=None, keepdims=False):
      r"""
      Returns the indices of the maximum values along an axis.
  
      Parameters
      ----------
      a : ndarray
          Input array. Only support ndarrays of dtype `float16`, `float32`, and `float64`.
      axis : int, optional
          By default, the index is into the flattened array, otherwise
          along the specified axis.
      out : ndarray or None, optional
          If provided, the result will be inserted into this array. It should
          be of the appropriate shape and dtype.
      keepdims : bool
          If True, the reduced axes (dimensions) must be included in the result as
          singleton dimensions, and, accordingly, the result must be compatible with
          the input array. Otherwise, if False, the reduced axes (dimensions) must
          not be included in the result. Default: False .
  
      Returns
      -------
      index_array : ndarray of indices whose dtype is same as the input ndarray.
          Array of indices into the array. It has the same shape as `a.shape`
          with the dimension along `axis` removed.
  
      .. note::
         ``keepdims`` param is part of request in data-api-standard
         <https://data-apis.org/array-api/latest/API_specification/generated/signatures.searching_functions.argmax.html>`_,
         which is not the parameter in official NumPy
  
         In case of multiple occurrences of the maximum values, the indices
         corresponding to the first occurrence are returned.
  
         This function differs from the original `numpy.argmax
         <https://numpy.org/doc/stable/reference/generated/numpy.argmax.html>`_ in
         the following aspects:
  
         * Input type does not support Python native iterables(list, tuple, ...).
         * ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape must be
           the same as the expected output.
         * ``out`` param: cannot perform auto type cast. ``out`` ndarray's dtype must be the
           same as the expected output.
         * ``out`` param does not support scalar input case.
  
      Examples
      --------
      >>> a = np.arange(6).reshape(2,3) + 10
      >>> a
      array([[10., 11., 12.],
             [13., 14., 15.]])
      >>> np.argmax(a)
      array(5.)
      >>> np.argmax(a, axis=0)
      array([1., 1., 1.])
      >>> np.argmax(a, axis=1)
      array([2., 2.])
  
      >>> b = np.arange(6)
      >>> b[1] = 5
      >>> b
      array([0., 5., 2., 3., 4., 5.])
      >>> np.argmax(b)  # Only the first occurrence is returned.
      array(1.)
  
      Specify ``out`` ndarray:
  
      >>> a = np.arange(6).reshape(2,3) + 10
      >>> b = np.zeros((2,))
      >>> np.argmax(a, axis=1, out=b)
      array([2., 2.])
      >>> b
      array([2., 2.])
      """
      return _mx_nd_np.argmax(a, axis, out, keepdims)
function_tokens: def argmax ( a , axis = None , out = None , keepdims = False ) : return _mx_nd_np . argmax ( a , axis , out , keepdims )