# mx.symbol.norm¶

## Description¶

Computes the norm on an NDArray.

This operator computes the norm on an NDArray with the specified axis, depending on the value of the ord parameter. By default, it computes the L2 norm on the entire array. Currently only ord=2 supports sparse ndarrays.

Example:

x = [[[1, 2],
[3, 4]],
[[2, 2],
[5, 6]]]

norm(x, ord=2, axis=1) = [[3.1622777 4.472136 ]
[5.3851647 6.3245554]]

norm(x, ord=1, axis=1) = [[4., 6.],
[7., 8.]]

rsp = x.cast_storage('row_sparse')

norm(rsp) = [5.47722578]

csr = x.cast_storage('csr')

norm(csr) = [5.47722578]


## Usage¶

mx.symbol.norm(...)


## Arguments¶

Argument

Description

data

NDArray-or-Symbol.

The input

ord

int, optional, default=’2’.

Order of the norm. Currently ord=1 and ord=2 is supported.

axis

Shape or None, optional, default=None.

The axis or axes along which to perform the reduction. The default, axis=(), will compute over all elements into a scalar array with shape (1,). If axis is int, a reduction is performed on a particular axis. If axis is a 2-tuple, it specifies the axes that hold 2-D matrices, and the matrix norms of these matrices are computed.

out.dtype

{None, ‘float16’, ‘float32’, ‘float64’, ‘int32’, ‘int64’, ‘int8’},optional, default=’None’.

The data type of the output.

keepdims

boolean, optional, default=0.

If this is set to True, the reduced axis is left in the result as dimension with size one.

name

string, optional.

Name of the resulting symbol.

## Value¶

out The result mx.symbol