code: def check_forward(self, diag_data, non_diag_data, gpu):
      diag = torch.tensor(diag_data, requires_grad=True)
      non_diag = torch.tensor(non_diag_data, requires_grad=True)
      if gpu >= 0:
          diag = diag.to(torch.device("cuda", gpu))
          non_diag = non_diag.to(torch.device("cuda", gpu))
  
      y = lower_triangular_matrix(diag, non_diag)
  
      correct_y = np.zeros(
          (self.batch_size, self.n, self.n), dtype=np.float32
      )
  
      tril_rows, tril_cols = np.tril_indices(self.n, -1)
      correct_y[:, tril_rows, tril_cols] = non_diag_data
  
      diag_rows, diag_cols = np.diag_indices(self.n)
      correct_y[:, diag_rows, diag_cols] = diag_data
  
      y = y.cpu() if gpu >= 0 else y
      np.testing.assert_allclose(correct_y, y.detach().numpy())
  
file_path: pfrl/tests/functions_tests/test_lower_triangular_matrix.py
imports: import numpy
  import pytest
  import torch
  from pfrl.functions.lower_triangular_matrix import lower_triangular_matrix
label_desc: Use image node_id 2 for calling the TestLowerTriangularMatrix obj's underlying member method code with example usage: obj.check_forward(diag_data, non_diag_data, gpu) without return types