class_docstr: Euclidean metric on matrices given by Frobenius inner-product.
class_docstr_tok: ["Euclidean","metric","on","matrices","given","by","Frobenius","inner-product","."]
docstr: Compute norm of a matrix.
  
  Norm of a matrix associated to the Frobenius inner product.
  
  Parameters
  ----------
  vector : array-like, shape=[..., dim]
      Vector.
  base_point : array-like, shape=[..., dim]
      Base point.
      Optional, default: None.
  
  Returns
  -------
  norm : array-like, shape=[...,]
      Norm.
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code: def norm(self, vector, base_point=None):
      """Compute norm of a matrix.
  
      Norm of a matrix associated to the Frobenius inner product.
  
      Parameters
      ----------
      vector : array-like, shape=[..., dim]
          Vector.
      base_point : array-like, shape=[..., dim]
          Base point.
          Optional, default: None.
  
      Returns
      -------
      norm : array-like, shape=[...,]
          Norm.
      """
      norm = gs.linalg.norm(vector, axis=(-2, -1))
      return repeat_out(
          self._space.point_ndim, norm, vector, base_point
      )
  
imports: import logging
  import math
  from functools import reduce
  import geomstats.backend
  import geomstats.errors
  from geomstats.algebra_utils import flip_determinant, from_vector_to_diagonal_matrix
  from geomstats.geometry.base import MatrixVectorSpace
  from geomstats.geometry.euclidean import EuclideanMetric
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 2 for calling the MatricesMetric obj's underlying member method code with example usage: obj.norm(vector, base_point) and returns: repeat_out