Source code for maxframe.tensor.linalg.matrix_norm
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from .norm import norm
[docs]
def matrix_norm(x, *, keepdims=False, ord="fro"):
"""
Computes the matrix norm of a matrix (or a stack of matrices) ``x``.
This function is Array API compatible.
Parameters
----------
x : array_like
Input array having shape (..., M, N) and whose two innermost
dimensions form ``MxN`` matrices.
keepdims : bool, optional
If this is set to True, the axes which are normed over are left in
the result as dimensions with size one. Default: False.
ord : {1, -1, 2, -2, inf, -inf, 'fro', 'nuc'}, optional
The order of the norm. For details see the table under ``Notes``
in `numpy.linalg.norm`.
See Also
--------
numpy.linalg.norm : Generic norm function
Examples
--------
>>> import maxframe.tensor as mt
>>> from maxframe.tensor import linalg as LA
>>> a = mt.arange(9) - 4
>>> a.execute()
array([-4, -3, -2, ..., 2, 3, 4])
>>> b = a.reshape((3, 3))
>>> b.execute()
array([[-4, -3, -2],
[-1, 0, 1],
[ 2, 3, 4]])
>>> LA.matrix_norm(b).execute()
7.745966692414834
>>> LA.matrix_norm(b, ord='fro').execute()
7.745966692414834
>>> LA.matrix_norm(b, ord=np.inf).execute()
9.0
>>> LA.matrix_norm(b, ord=-np.inf).execute()
2.0
>>> LA.matrix_norm(b, ord=1).execute()
7.0
>>> LA.matrix_norm(b, ord=-1).execute()
6.0
>>> LA.matrix_norm(b, ord=2).execute()
7.3484692283495345
>>> LA.matrix_norm(b, ord=-2).execute()
1.8570331885190563e-016 # may vary
"""
from ..datasource.array import asarray
x = asarray(x)
return norm(x, axis=(-2, -1), keepdims=keepdims, ord=ord)