mindspore.nn.Norm

class mindspore.nn.Norm(axis=(), keep_dims=False)[source]

Computes the norm of vectors, currently including Euclidean norm, i.e., \(L_2\)-norm.

\[norm(x) = \sqrt{\sum_{i=1}^{n} (x_i^2)}\]

Parameters

axis (Union[tuple, int]) – The axis over which to compute vector norms. Default: ().
keep_dims (bool) – If true, the axis indicated in axis are kept with size 1. Otherwise, the dimensions in axis are removed from the output shape. Default: False.

Inputs:

input (Tensor) - Tensor which is not empty.

Outputs:

Tensor, output tensor with dimensions in ‘axis’ reduced to 1 will be returned if ‘keep_dims’ is True; otherwise a Tensor with dimensions in ‘axis’ removed is returned.

Raises

TypeError – If axis is neither an int nor tuple.
TypeError – If keep_dims is not a bool.

Supported Platforms:: Ascend GPU CPU

Examples

>>> net = nn.Norm(axis=0)
>>> input = Tensor(np.array([[4, 4, 9, 1], [2, 1, 3, 6]]), mindspore.float32)
>>> output = net(input)
>>> print(output)
[4.472136 4.1231055 9.486833 6.0827627]