code: def test_svd_compression_gives_orthonormal_loadings():
      """Loading matrices should have orthonormal columns"""
      rng = tl.check_random_state(1234)
      tensor_slices = [
          tl.tensor(rng.standard_normal((25, 10)), dtype=tl.float64),
          tl.tensor(rng.standard_normal((25, 10)), dtype=tl.float64),
      ]
      _compressed_slices, loadings = svd_compress_tensor_slices(
          tensor_slices
      )
  
      for loading_matrix in loadings:
          gramian = tl.matmul(
              tl.transpose(loading_matrix), loading_matrix
          )
          assert_allclose(
              gramian, tl.eye(tl.shape(gramian)[0]), atol=1e-10
          )
  
file_path: tensorly/tensorly/tests/test_preprocessing.py
imports: import pytest
  from pytest import approx
  import numpy
  import tensorly
  from ..parafac2_tensor import parafac2_to_slices
  from ..random import random_parafac2
  from ..testing import assert_allclose
  from ..decomposition._parafac2 import parafac2, _parafac2_reconstruction_error
  from ..preprocessing import svd_compress_tensor_slices, svd_decompress_parafac2_tensor
label_desc: Use image node_id 6 for calling a global function with example usage: test_svd_compression_gives_orthonormal_loadings() without return types