code: def test_cp_copy():
      shape = (3, 4, 5)
      rank = 4
      cp_tensor = random_cp(shape, rank)
      weights, factors = cp_tensor
      weights_normalized, factors_normalized = cp_normalize(
          cp_tensor.cp_copy()
      )
      # Check that modifying copy tensor doesn't change the original tensor
      assert_array_almost_equal(
          cp_to_tensor((weights, factors)), cp_to_tensor(cp_tensor)
      )
  
imports: import numpy
  import tensorly
  from ..tenalg import khatri_rao, mode_dot
  from ..cp_tensor import cp_to_tensor, cp_to_unfolded, cp_to_vec, _validate_cp_tensor, cp_normalize, CPTensor, cp_mode_dot, cp_norm, cp_flip_sign, _cp_n_param, validate_cp_rank, cp_lstsq_grad, cp_permute_factors
  from ..base import unfold, tensor_to_vec
  from tensorly.random import random_cp
  from tensorly.testing import assert_equal, assert_raises, assert_, assert_array_equal, assert_array_almost_equal
  import pytest
label_desc: Use image node_id 12 for calling a global function with example usage: test_cp_copy() without return types