code: def test_alignment_train(self, bsz, tgt_len, src_len, device):
      eps = 1e-6
  
      assume(device == "cpu" or TEST_CUDA)
      p_choose = torch.rand(bsz, tgt_len, src_len, device=device)
  
      # run the alignment with the custom operator
      alpha_act = p_choose.new_zeros([bsz, tgt_len, src_len])
      self._test_custom_alignment_train_impl(p_choose, alpha_act, eps)
  
      # runu the alignment with the ref implementation
      alpha_ref = self._test_custom_alignment_train_ref(p_choose, eps)
  
      # verify the results
      alpha_act = alpha_act.cpu().detach().numpy()
      alpha_ref = alpha_ref.cpu().detach().numpy()
      np.testing.assert_allclose(
          alpha_act,
          alpha_ref,
          atol=1e-3,
          rtol=1e-3,
      )
  
file_path: fairseq/examples/simultaneous_translation/tests/test_alignment_train.py
imports: import unittest
  import numpy
  import torch
  import hypothesis.strategies
  from hypothesis import assume, given, settings
  from torch.testing._internal.common_utils import TestCase
  from examples.simultaneous_translation.utils.functions import exclusive_cumprod
label_desc: Use image node_id 3 for calling the AlignmentTrainTest obj's underlying member method code with example usage: obj.test_alignment_train(bsz, tgt_len, src_len, device) without return types