mindspore.ops.mean

mindspore.ops.mean(x, axis=None, keep_dims=False)[source]

Compute the mean(s) of the tensor along the specified axis(axes).

Parameters

x (Tensor[Number]) – The input tensor.
axis (Union[int, tuple(int), list(int), Tensor]) – Specify the axis(axes) for computation. If None , compute all elements in the input .
keep_dims (bool) – Whether the output tensor has dim retained. Default False .

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> input = mindspore.tensor([[9, 3, 4, 5],
...                           [5, 2, 7, 4],
...                           [8, 1, 3, 6]])
>>> # case 1: By default, compute the mean of all elements.
>>> mindspore.ops.mean(input)
Tensor(shape=[], dtype=Int64, value= 4)
>>>
>>> # case 2: Compute the mean along axis 1.
>>> mindspore.ops.mean(input, axis=1)
Tensor(shape=[3], dtype=Int64, value= [5, 4, 4])
>>>
>>> # case 3: If keep_dims=True, the output shape will be same of that of the input.
>>> mindspore.ops.mean(input, axis=1, keep_dims=True)
Tensor(shape=[3, 1], dtype=Int64, value=
[[5],
 [4],
 [4]])