TF generate refactor - Beam Search (#16374)

* refactor TF beam search

* refactored generate can now properly use attention masks

* add force bos/eos logit processors

tests/generation/test_generation_logits_process.py

@@ -472,14 +472,14 @@ class LogitsProcessorTest(unittest.TestCase):
 
         logits_processor = ForcedEOSTokenLogitsProcessor(max_length=max_length, eos_token_id=eos_token_id)
 
-        # check that all scores are -inf except the eos_token_id when max_length is reached
+        # check that all scores are -inf except the eos_token_id when max_length-1 is reached
         input_ids = ids_tensor((batch_size, 4), vocab_size=20)
         scores = self._get_uniform_logits(batch_size, vocab_size)
         scores = logits_processor(input_ids, scores)
         self.assertTrue(torch.isneginf(scores[:, eos_token_id + 1 :]).all())
         self.assertListEqual(scores[:, eos_token_id].tolist(), 4 * [0])  # score for eos_token_id should be zero
 
-        # check that eos_token_id is not forced if max_length is not reached
+        # check that eos_token_id is not forced if max_length-1 is not reached
         input_ids = ids_tensor((batch_size, 3), vocab_size=20)
         scores = self._get_uniform_logits(batch_size, vocab_size)
         scores = logits_processor(input_ids, scores)