text: import unittest
  import torch
  
  from machine_translation.model import Transformer
  
  
  class TestTransformer(unittest.TestCase):
      def test_transformer_inference(self):
          BATCH_SIZE = 3
          SEQ_LENGTH = 10
          MAX_LENGTH = 32
          TARGET_VOCAB_SIZE = 320
  
          model = Transformer(80, 320, d_model=64, num_encoder_layers=2, num_decoder_layers=2, max_length=MAX_LENGTH)
          inputs = torch.zeros(BATCH_SIZE, SEQ_LENGTH).long()
          input_lengths = torch.LongTensor([10, 9, 8])
  
          outputs = model.forward(inputs, input_lengths)
  
          assert len(outputs.size()) == 3
          assert outputs.size(0) == 3
          assert outputs.size(1) == MAX_LENGTH - 1
          assert outputs.size(2) == TARGET_VOCAB_SIZE
          print("test_transformer_inference Success ==")
  
  
  if __name__ == '__main__':
      unittest.main()
  