code: def test_cp_flip_sign():
      shape = (3, 4, 5)
      rank = 4
      cp_tensor = random_cp(shape, rank)
      weights, factors = cp_flip_sign(cp_tensor)
  
      assert_(tl.all(tl.mean(factors[1], axis=0) > 0))
      assert_(tl.all(tl.mean(factors[2], axis=0) > 0))
      assert_equal(cp_tensor.rank, cp_tensor.rank)
      assert_array_equal(cp_tensor.weights, weights)
      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 2 for calling a global function with example usage: test_cp_flip_sign() without return types