code: def norm(tensor, order=2, axis=None):
      # handle difference in default axis notation
      if axis == ():
          axis = None
  
      if order == "inf":
          return np.max(np.abs(tensor), axis=axis)
      if order == 1:
          return np.sum(np.abs(tensor), axis=axis)
      elif order == 2:
          return np.sqrt(np.sum(tensor**2, axis=axis))
      else:
          return np.sum(np.abs(tensor) ** order, axis=axis) ** (
              1 / order
          )
  
imports: from copy import copy
  from packaging.version import Version
  import numpy
  import scipy
  import scipy.linalg
  import scipy.sparse.linalg
  import sparse
  from .None import register_sparse_backend
  from ....backend.core import Backend
label_desc: Use image node_id 7 for calling the NumpySparseBackend obj's underlying member method code with example usage: obj.norm(tensor, order, axis) and returns: np, np, np, unknown