






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 a_    (    unittest.TestCase							):







   def     SCREAMING_SNAKE_CASE__					(self					,   __a)			->      Tuple:
      """simple docstring"""






      __snake_case				:      List[str]     							= 3
      __snake_case				:      Tuple     							= 2_5_0

      __snake_case				:      str     							= ids_tensor((batch_size, length)					,   UpperCamelCase_)
      __snake_case				:      Any     							= torch.ones((batch_size, length)					,   device=UpperCamelCase_					,   dtype=torch.float) / length
      return input_ids, scores







   def     SCREAMING_SNAKE_CASE__					(self)			->      Union[str, Any]:
      """simple docstring"""






      __snake_case				:      Tuple     							= self._get_tensors(5)

      __snake_case				:      Tuple     							= StoppingCriteriaList(
          [
              MaxLengthCriteria(max_length=1_0),
              MaxTimeCriteria(max_time=0.1),
          ])

      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      int     							= self._get_tensors(9)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Optional[int]     							= self._get_tensors(1_0)
      self.assertTrue(criteria(UpperCamelCase_					,   UpperCamelCase_))







   def     SCREAMING_SNAKE_CASE__					(self)			->      int:
      """simple docstring"""






      __snake_case				:      int     							= MaxLengthCriteria(max_length=1_0)

      __snake_case				:      Tuple     							= self._get_tensors(5)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Dict     							= self._get_tensors(9)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Optional[int]     							= self._get_tensors(1_0)
      self.assertTrue(criteria(UpperCamelCase_					,   UpperCamelCase_))







   def     SCREAMING_SNAKE_CASE__					(self)			->      Optional[int]:
      """simple docstring"""






      __snake_case				:      Optional[Any]     							= MaxNewTokensCriteria(start_length=5					,   max_new_tokens=5)

      __snake_case				:      List[str]     							= self._get_tensors(5)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Dict     							= self._get_tensors(9)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Optional[Any]     							= self._get_tensors(1_0)
      self.assertTrue(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      Union[str, Any]     							= StoppingCriteriaList([criteria])
      self.assertEqual(criteria_list.max_length					,   1_0)







   def     SCREAMING_SNAKE_CASE__					(self)			->      List[str]:
      """simple docstring"""






      __snake_case				:      Optional[Any]     							= self._get_tensors(5)

      __snake_case				:      str     							= MaxTimeCriteria(max_time=0.1)
      self.assertFalse(criteria(UpperCamelCase_					,   UpperCamelCase_))

      __snake_case				:      str     							= MaxTimeCriteria(max_time=0.1					,   initial_timestamp=time.time() - 0.2)
      self.assertTrue(criteria(UpperCamelCase_					,   UpperCamelCase_))







   def     SCREAMING_SNAKE_CASE__					(self)			->      List[str]:
      """simple docstring"""






      validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0)])					,   1_0)

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

      __snake_case				:      Optional[int]     							= validate_stopping_criteria(StoppingCriteriaList()					,   1_1)

      self.assertEqual(len(UpperCamelCase_)					,   1)







'''simple docstring'''






from functools import lru_cache




@lru_cache
def        _SCREAMING_SNAKE_CASE  (				A  :       int  )    -> int:







   """simple docstring"""
   if num < 0:
      raise ValueError('Number should not be negative.'  )

   return 1 if num in (0, 1) else num * factorial(num - 1  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()