code: def test_tensor_train_tensorly_3(shape, rank, tol):
      tensor = ivy.random_uniform(shape=shape)
      factors = ivy.tensor_train(tensor, rank)
      reconstructed_tensor = ivy.TTTensor.tt_to_tensor(factors)
      error = ivy.vector_norm(
          ivy.matrix_norm(tensor - reconstructed_tensor, ord=2)
      )
      error /= ivy.vector_norm(ivy.matrix_norm(tensor, ord=2))
      np.testing.assert_(
          error < tol, "norm 2 of reconstruction higher than tol"
      )
  
imports: import math
  from hypothesis import strategies
  from hypothesis import assume
  import numpy
  import pytest
  import itertools
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
  import ivy
label_desc: Use image node_id 54 for calling a global function with example usage: test_tensor_train_tensorly_3(shape, rank, tol) without return types