code: def test_tt_to_tensor_random():
      """Test for tt_to_tensor
  
      Uses random tensor as input
      """
  
      # Create tensor with random elements
      tensor = tl.tensor(np.random.rand(3, 4, 5, 6, 2, 10))
      tensor_shape = tensor.shape
  
      # Find TT decomposition of the tensor
      rank = 10
      factors = tensor_train(tensor, rank)
  
      # Reconstruct the original tensor
      reconstructed_tensor = tl.tt_to_tensor(factors)
      assert_(tl.shape(reconstructed_tensor) == tensor_shape)
  
      # Check that the rank is 10
      D = len(factors)
      for k in range(D):
          (r_prev, _, r_k) = factors[k].shape
          assert r_prev <= rank, (
              "TT rank with index " + str(k) + "exceeds rank"
          )
          assert r_k <= rank, (
              "TT rank with index " + str(k + 1) + "exceeds rank"
          )
  
file_path: tensorly/tensorly/tests/test_tt_tensor.py
imports: import numpy
  import tensorly
  from ..decomposition import tensor_train
  from ..tt_tensor import _validate_tt_tensor, pad_tt_rank
  from ..tt_tensor import validate_tt_rank, _tt_n_param
  from ..testing import assert_array_almost_equal, assert_equal, assert_raises, assert_
  from ..random import random_tt, random_tr, random_tt_matrix
  import pytest
label_desc: Use image node_id 3 for calling a global function with example usage: test_tt_to_tensor_random() without return types