
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 import (
						    MaxLengthCriteria,
						    MaxNewTokensCriteria,
						    MaxTimeCriteria,
						    StoppingCriteriaList,
						    validate_stopping_criteria,
						)
@require_torch
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	def 						_lowercase  (       self  :			Union[str, Any]       ,							SCREAMING_SNAKE_CASE_  :			List[Any]       )       ->     str:
					lowercase_       =					3
					lowercase_       =					2_5_0

					lowercase_       =					ids_tensor((batch_size, length)       ,							SCREAMING_SNAKE_CASE_       )
					lowercase_       =					torch.ones((batch_size, length)       ,							device=SCREAMING_SNAKE_CASE_       ,							dtype=torch.float       ) / length
					return input_ids, scores
	def 						_lowercase  (       self  :			Optional[Any]       )       ->     Any:
					lowercase_  ,	lowercase_       =					self._get_tensors(5       )

					lowercase_       =					StoppingCriteriaList(
					    [
					        MaxLengthCriteria(max_length=1_0       ),
					        MaxTimeCriteria(max_time=0.1       ),
					    ]       )

					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(9       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(1_0       )
					self.assertTrue(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )
	def 						_lowercase  (       self  :			str       )       ->     Optional[int]:
					lowercase_       =					MaxLengthCriteria(max_length=1_0       )

					lowercase_  ,	lowercase_       =					self._get_tensors(5       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(9       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(1_0       )
					self.assertTrue(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )
	def 						_lowercase  (       self  :			Dict       )       ->     Optional[int]:
					lowercase_       =					MaxNewTokensCriteria(start_length=5       ,							max_new_tokens=5       )

					lowercase_  ,	lowercase_       =					self._get_tensors(5       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(9       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_  ,	lowercase_       =					self._get_tensors(1_0       )
					self.assertTrue(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_       =					StoppingCriteriaList([criteria]       )
					self.assertEqual(criteria_list.max_length       ,							1_0       )
	def 						_lowercase  (       self  :			str       )       ->     Union[str, Any]:
					lowercase_  ,	lowercase_       =					self._get_tensors(5       )

					lowercase_       =					MaxTimeCriteria(max_time=0.1       )
					self.assertFalse(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )

					lowercase_       =					MaxTimeCriteria(max_time=0.1       ,							initial_timestamp=time.time() - 0.2       )
					self.assertTrue(criteria(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )




	def 						_lowercase  (       self  :			Optional[Any]       )       ->     Union[str, Any]:
					validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0       )]       )       ,							1_0       )

					with self.assertWarns(SCREAMING_SNAKE_CASE_       ):
									validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0       )]       )       ,							1_1       )

					lowercase_       =					validate_stopping_criteria(StoppingCriteriaList()       ,							1_1       )

					self.assertEqual(len(SCREAMING_SNAKE_CASE_       )       ,							1       )






import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


__a  			=					'sshleifer/bart-tiny-random'
__a  			=					'patrickvonplaten/t5-tiny-random'
@require_torch
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	@cached_property
	def 						_lowercase  (       self  :			Any       )       ->     Tuple:
					return AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			int       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.num_hidden_layers       ,							1       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			List[str]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							self.teacher_config.encoder_layers       )
	def 						_lowercase  (       self  :			List[Any]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							1       )




	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
									create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=SCREAMING_SNAKE_CASE_       ,							d=SCREAMING_SNAKE_CASE_       )




