mxnet.np.sum

sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None, where=None)

Sum of array elements over a given axis.

Parameters

  • a (ndarray) – Input data.

  • axis (None or int, optional) – Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is negative it counts from the last to the first axis.

  • dtype (dtype, optional) – The type of the returned array and of the accumulator in which the elements are summed. The default type is float32.

  • keepdims (bool, optional) –

    If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

    If the default value is passed, then keepdims will not be passed through to the sum method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method does not implement keepdims any exceptions will be raised.

  • initial (Currently only supports None as input, optional) – Starting value for the sum. Currently not implemented. Please use None as input or skip this argument.

  • out (ndarray or None, optional) – Alternative output array in which to place the result. It must have the same shape and dtype as the expected output.

Returns

sum_along_axis – An ndarray with the same shape as a, with the specified axis removed. If an output array is specified, a reference to out is returned.

Return type

ndarray

Notes

  • Input type does not support Python native iterables.

  • “out” param: cannot perform auto type change. out ndarray’s dtype must be the same as the expected output.

  • “initial” param is not supported yet. Please use None as input.

  • Arithmetic is modular when using integer types, and no error is raised on overflow.

  • The sum of an empty array is the neutral element 0:

>>> a = np.empty(1)
>>> np.sum(a)
array(0.)

This function differs from the original numpy.sum in the following aspects:

  • Input type does not support Python native iterables(list, tuple, …).

  • “out” param: cannot perform auto type cast. out ndarray’s dtype must be the same as the expected output.

  • “initial” param is not supported yet. Please use None as input or skip it.

  • The default type is float32.

Examples

>>> a = np.array([0.5, 1.5])
>>> np.sum(a)
array(2.)
>>> a = np.array([0.5, 0.7, 0.2, 1.5])
>>> np.sum(a, dtype=np.int32)
array(2, dtype=int32)
>>> a = np.array([[0, 1], [0, 5]])
>>> np.sum(a)
array(6.)
>>> np.sum(a, axis=0)
array([0., 6.])
>>> np.sum(a, axis=1)
array([1., 5.])

With output ndarray:

>>> a = np.array([[0, 1], [0, 5]])
>>> b = np.ones((2,), dtype=np.float32)
>>> np.sum(a, axis = 0, out=b)
array([0., 6.])
>>> b
array([0., 6.])

If the accumulator is too small, overflow occurs:

>>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
array(-128, dtype=int8)