code: def test_norm():
      v = T.tensor([1.0, 2.0, 3.0])
      assert_equal(T.norm(v, 1), 6)
  
      A = T.reshape(T.arange(6, dtype=T.float32), (3, 2))
      assert_equal(T.norm(A, 1), 15)
  
      column_norms1 = T.norm(A, 1, axis=0)
      row_norms1 = T.norm(A, 1, axis=1)
      assert_array_equal(column_norms1, T.tensor([6.0, 9]))
      assert_array_equal(row_norms1, T.tensor([1, 5, 9]))
  
      column_norms2 = T.norm(A, 2, axis=0)
      row_norms2 = T.norm(A, 2, axis=1)
      assert_array_almost_equal(
          column_norms2, T.tensor([4.47213602, 5.91608])
      )
      assert_array_almost_equal(
          row_norms2, T.tensor([1.0, 3.60555124, 6.40312433])
      )
  
      # limit as order->oo is the oo-norm
      column_norms10 = T.norm(A, 10, axis=0)
      row_norms10 = T.norm(A, 10, axis=1)
      assert_array_almost_equal(
          column_norms10, T.tensor([4.00039053, 5.00301552])
      )
      assert_array_almost_equal(
          row_norms10, T.tensor([1.0, 3.00516224, 5.05125666])
      )
  
      column_norms_oo = T.norm(A, "inf", axis=0)
      row_norms_oo = T.norm(A, "inf", axis=1)
      assert_array_equal(column_norms_oo, T.tensor([4, 5]))
      assert_array_equal(row_norms_oo, T.tensor([1, 3, 5]))
  
imports: from concurrent.futures import ThreadPoolExecutor
  import pytest
  from time import time
  import numpy
  from scipy.linalg import svd
  from scipy import special
  import tensorly
  from ..None import backend
  from ..testing import assert_allclose, assert_array_equal, assert_equal, assert_, assert_array_almost_equal, assert_raises
  from tensorly.tenalg.svd import SVD_FUNS, svd_interface
label_desc: Use image node_id 10 for calling a global function with example usage: test_norm() without return types