code: def test_torch_lstm_step():
      """Test invoking LSTMStep."""
      n_test = 5
      n_feat = 10
      y = np.random.rand(n_test, 2 * n_feat).astype(np.float32)
      state_zero = np.random.rand(n_test, n_feat).astype(np.float32)
      state_one = np.random.rand(n_test, n_feat).astype(np.float32)
      layer = torch_layers.LSTMStep(n_feat, 2 * n_feat)
      result = layer([y, state_zero, state_one])
      h_out, h_copy_out, c_out = (result[0], result[1][0], result[1][1])
      assert h_out.shape == (n_test, n_feat)
      assert h_copy_out.shape == (n_test, n_feat)
      assert c_out.shape == (n_test, n_feat)
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 42 for calling a global function with example usage: test_torch_lstm_step() without return types