code: def matrix_norm(x, ord="fro", axis=(-2, -1), keepdims=False):
      r"""
      Computes the matrix norm of a matrix (or a stack of matrices) `x`.
  
      Parameters
      ----------
      x : ndarray
          Input array. Should have a floating-point data type.
      ord : {non-zero int, inf, -inf, ‘fro’, ‘nuc’}, optional
          Order of the norm.
      axis : {2-tuple of ints}
          a 2-tuple which specifies the axes (dimensions) defining two-dimensional
          matrices for which to compute matrix norms.
      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.  With this option the result will
          broadcast correctly against the original `x`.
  
      Returns
      -------
      n : float or ndarray
          Norm of the matrix.
  
      Notes
      -----
      `matrix_norm` is a standard API in
      https://data-apis.org/array-api/latest/extensions/linear_algebra_functions.html#linalg-matrix-norm-x-axis-2-1-keepdims-false-ord-fro
      instead of an official NumPy operator.
  
      """
      if isinstance(axis, tuple) and len(axis) == 2:
          return _mx_nd_np.linalg.norm(
              x, axis=axis, keepdims=keepdims, ord=ord
          )
      raise ValueError(
          "The axis of matrix_norm must be a 2-tuple of ints"
      )
  
imports: from functools import reduce
  from ..ndarray import numpy
  from ..util import wrap_data_api_linalg_func
  from .fallback_linalg import *
  from .None import fallback_linalg
label_desc: Use image node_id 13 for calling a global function with example usage: matrix_norm(x, ord, axis, keepdims) and returns: _mx_nd_np