| import time |
| import unittest |
|
|
| from transformers import is_torch_available |
| from transformers.testing_utils import require_torch, torch_device |
|
|
| from .test_modeling_common import ids_tensor |
|
|
|
|
| if is_torch_available(): |
| import torch |
|
|
| from transformers.generation_stopping_criteria import ( |
| MaxLengthCriteria, |
| MaxNewTokensCriteria, |
| MaxTimeCriteria, |
| StoppingCriteriaList, |
| validate_stopping_criteria, |
| ) |
|
|
|
|
| @require_torch |
| class StoppingCriteriaTestCase(unittest.TestCase): |
| def _get_tensors(self, length): |
| batch_size = 3 |
| vocab_size = 250 |
|
|
| input_ids = ids_tensor((batch_size, length), vocab_size) |
| scores = torch.ones((batch_size, length), device=torch_device, dtype=torch.float) / length |
| return input_ids, scores |
|
|
| def test_list_criteria(self): |
| input_ids, scores = self._get_tensors(5) |
|
|
| criteria = StoppingCriteriaList( |
| [ |
| MaxLengthCriteria(max_length=10), |
| MaxTimeCriteria(max_time=0.1), |
| ] |
| ) |
|
|
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(9) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(10) |
| self.assertTrue(criteria(input_ids, scores)) |
|
|
| def test_max_length_criteria(self): |
| criteria = MaxLengthCriteria(max_length=10) |
|
|
| input_ids, scores = self._get_tensors(5) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(9) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(10) |
| self.assertTrue(criteria(input_ids, scores)) |
|
|
| def test_max_new_tokens_criteria(self): |
| criteria = MaxNewTokensCriteria(start_length=5, max_new_tokens=5) |
|
|
| input_ids, scores = self._get_tensors(5) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(9) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| input_ids, scores = self._get_tensors(10) |
| self.assertTrue(criteria(input_ids, scores)) |
|
|
| criteria_list = StoppingCriteriaList([criteria]) |
| self.assertEqual(criteria_list.max_length, 10) |
|
|
| def test_max_time_criteria(self): |
| input_ids, scores = self._get_tensors(5) |
|
|
| criteria = MaxTimeCriteria(max_time=0.1) |
| self.assertFalse(criteria(input_ids, scores)) |
|
|
| criteria = MaxTimeCriteria(max_time=0.1, initial_timestamp=time.time() - 0.2) |
| self.assertTrue(criteria(input_ids, scores)) |
|
|
| def test_validate_stopping_criteria(self): |
| validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)]), 10) |
|
|
| with self.assertWarns(UserWarning): |
| validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)]), 11) |
|
|
| stopping_criteria = validate_stopping_criteria(StoppingCriteriaList(), 11) |
|
|
| self.assertEqual(len(stopping_criteria), 1) |
|
|