maxframe.tensor.linalg.matrix_norm#

maxframe.tensor.linalg.matrix_norm(x, *, keepdims=False, ord='fro')[source]#

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