code: def test_torch_combine_mean_std():
      """Test invoking the Torch equivalent of CombineMeanStd."""
      mean = torch.rand((5, 3), dtype=torch.float32)
      std = torch.rand((5, 3), dtype=torch.float32)
      layer = torch_layers.CombineMeanStd(
          training_only=True, noise_epsilon=0.01
      )
      result1 = layer([mean, std], training=False)
      assert np.array_equal(result1, mean)  # No noise in test mode
      result2 = layer([mean, std], training=True)
      assert not np.array_equal(result2, mean)
      assert np.allclose(result2, mean, atol=0.1)
      assert result1.shape == mean.shape and result1.shape == std.shape
      assert result2.shape == mean.shape and result2.shape == std.shape
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 45 for calling a global function with example usage: test_torch_combine_mean_std() without return types