


"""simple docstring"""




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 					__lowerCAmelCase					(   unittest.TestCase       ):


		'''simple docstring'''



		def 			__UpperCAmelCase       (  self							, _a      ):
				__a           =			3
				__a           =			250

				__a           =			ids_tensor((batch_size, length)							, SCREAMING_SNAKE_CASE_      )
				__a           =			torch.ones((batch_size, length)							, device=SCREAMING_SNAKE_CASE_							, dtype=torch.float      ) / length
				return input_ids, scores

		def 			__UpperCAmelCase       (  self      ):
				__a      ,     __a           =			self._get_tensors(5      )

				__a           =			StoppingCriteriaList(
				    [
				        MaxLengthCriteria(max_length=10      ),
				        MaxTimeCriteria(max_time=0.1      ),
				    ]      )

				self.assertFalse(criteria(SCREAMING_SNAKE_CASE_							, SCREAMING_SNAKE_CASE_      )      )

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

				__a      ,     __a           =			self._get_tensors(10      )
				self.assertTrue(criteria(SCREAMING_SNAKE_CASE_							, SCREAMING_SNAKE_CASE_      )      )

		def 			__UpperCAmelCase       (  self      ):
				__a           =			MaxLengthCriteria(max_length=10      )

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

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

				__a      ,     __a           =			self._get_tensors(10      )
				self.assertTrue(criteria(SCREAMING_SNAKE_CASE_							, SCREAMING_SNAKE_CASE_      )      )

		def 			__UpperCAmelCase       (  self      ):
				__a           =			MaxNewTokensCriteria(start_length=5							, max_new_tokens=5      )

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

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

				__a      ,     __a           =			self._get_tensors(10      )
				self.assertTrue(criteria(SCREAMING_SNAKE_CASE_							, SCREAMING_SNAKE_CASE_      )      )

				__a           =			StoppingCriteriaList([criteria]      )
				self.assertEqual(criteria_list.max_length							, 10      )

		def 			__UpperCAmelCase       (  self      ):
				__a      ,     __a           =			self._get_tensors(5      )

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

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





		def 			__UpperCAmelCase       (  self      ):
				validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10      )]      )							, 10      )

				with self.assertWarns(SCREAMING_SNAKE_CASE_      ):
						validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10      )]      )							, 11      )

				__a           =			validate_stopping_criteria(StoppingCriteriaList()							, 11      )

				self.assertEqual(len(SCREAMING_SNAKE_CASE_      )							, 1      )








import os




def 				a						(							):


				'''simple docstring'''
				lowercase_       =					os.path.join(os.path.dirname(snake_case__					)						,   '''num.txt'''					)
				with open(snake_case__					) as file_hand:
								return str(sum(int(snake_case__					) for line in file_hand					)					)[:10]


if __name__ == "__main__":
						print(solution())




