# mean¶

paddle. mean ( x, axis=None, keepdim=False, name=None ) [source]

Computes the mean of the input tensor’s elements along `axis`.

Parameters
• x (Tensor) – The input Tensor with data type float32, float64.

• axis (int|list|tuple, optional) – The axis along which to perform mean calculations. `axis` should be int, list(int) or tuple(int). If `axis` is a list/tuple of dimension(s), mean is calculated along all element(s) of `axis` . `axis` or element(s) of `axis` should be in range [-D, D), where D is the dimensions of `x` . If `axis` or element(s) of `axis` is less than 0, it works the same way as \(axis + D\) . If `axis` is None, mean is calculated over all elements of `x`. Default is None.

• keepdim (bool, optional) – Whether to reserve the reduced dimension(s) in the output Tensor. If `keepdim` is True, the dimensions of the output Tensor is the same as `x` except in the reduced dimensions(it is of size 1 in this case). Otherwise, the shape of the output Tensor is squeezed in `axis` . Default is False.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor, results of average along `axis` of `x`, with the same data type as `x`.

Examples

```import paddle

x = paddle.to_tensor([[[1., 2., 3., 4.],
[5., 6., 7., 8.],
[9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]])
# [12.5]
# [[ 2.5  6.5 10.5]
#  [14.5 18.5 22.5]]