sum(a, axis=None, dtype=None, keepdims=False, initial=None)¶
Returns sum of array elements over a given axis.
Numpy arguments out, where, casting, order, subok, signature, and extobj are not supported.
axis (Union[None, int, tuple(int)]) – Axis or axes along which a sum is performed. Default: None. If None, sum all of the elements of the input array. If axis is negative it counts from the last to the first axis. If axis is a tuple of ints, a sum is performed on all of the axes specified in the tuple instead of a single axis or all the axes as before.
mindspore.dtype, optional) – defaults to None. Overrides the dtype of the output Tensor.
keepdims (bool) – 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-class’ method does not implement keepdims any exceptions will be raised. Default: False.
initial (scalar) – Starting value for the sum.
Tensor. An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.
- Supported Platforms:
>>> import mindspore.numpy as np >>> print(np.sum([0.5, 1.5])) 2.0 >>> x = np.arange(10).reshape(2, 5).astype('float32') >>> print(np.sum(x, axis=1)) [10. 35.]