





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):







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						str:



        '''simple docstring'''




        a__     : Dict  =3
        a__     : Optional[int]  =2_5_0

        a__     : Union[str, Any]  =ids_tensor((batch_size, length)		,				lowerCAmelCase__							)
        a__     : List[Any]  =torch.ones((batch_size, length)		,				device=lowerCAmelCase__		,				dtype=torch.float							) / length
        return input_ids, scores







      def        _lowercase  (   self							)       ->						Union[str, Any]:



        '''simple docstring'''




        a__     : Tuple  =self._get_tensors(5							)

        a__     : Any  =StoppingCriteriaList(
            [
                MaxLengthCriteria(max_length=1_0							),
                MaxTimeCriteria(max_time=0.1							),
            ]							)

        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : Tuple  =self._get_tensors(9							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : Union[str, Any]  =self._get_tensors(1_0							)
        self.assertTrue(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)







      def        _lowercase  (   self							)       ->						Optional[Any]:



        '''simple docstring'''




        a__     : str  =MaxLengthCriteria(max_length=1_0							)

        a__     : Optional[int]  =self._get_tensors(5							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : List[Any]  =self._get_tensors(9							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

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







      def        _lowercase  (   self							)       ->						Union[str, Any]:



        '''simple docstring'''




        a__     : Any  =MaxNewTokensCriteria(start_length=5		,				max_new_tokens=5							)

        a__     : Tuple  =self._get_tensors(5							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : Optional[Any]  =self._get_tensors(9							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : int  =self._get_tensors(1_0							)
        self.assertTrue(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

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







      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




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

        a__     : Tuple  =MaxTimeCriteria(max_time=0.1							)
        self.assertFalse(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)

        a__     : Optional[int]  =MaxTimeCriteria(max_time=0.1		,				initial_timestamp=time.time() - 0.2							)
        self.assertTrue(criteria(lowerCAmelCase__		,				lowerCAmelCase__							)							)







      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




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

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

        a__     : Union[str, Any]  =validate_stopping_criteria(StoppingCriteriaList()		,				1_1							)

        self.assertEqual(len(lowerCAmelCase__							)		,				1							)













UpperCAmelCase     :     Dict							=	[0, 2, 4, 6, 8]
UpperCAmelCase     :     Tuple							=	[1, 3, 5, 7, 9]
def 					_A	(		SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       list[int]	,	SCREAMING_SNAKE_CASE					:       int						):





  """simple docstring"""



  if remaining_length == 0:
    if digits[0] == 0 or digits[-1] == 0:
      return 0

    for i in range(length // 2 - 1	,	-1	,	-1						):
      remainder += digits[i] + digits[length - i - 1]

      if remainder % 2 == 0:
        return 0

      remainder //= 10

    return 1

  if remaining_length == 1:
    if remainder % 2 == 0:
      return 0

    a__     : str  =0
    for digit in range(10						):
      a__     : int  =digit
      result += reversible_numbers(
          0	,	(remainder + 2 * digit) // 10	,	SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						)
    return result

  a__     : List[str]  =0
  for digita in range(10						):
    a__     : Optional[int]  =digita

    if (remainder + digita) % 2 == 0:
      a__     : Dict  =ODD_DIGITS
    else:
      a__     : Any  =EVEN_DIGITS

    for digita in other_parity_digits:
      a__     : Union[str, Any]  =digita
      result += reversible_numbers(
          remaining_length - 2	,	(remainder + digita + digita) // 10	,	SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE	,	)
  return result
def 					_A	(		SCREAMING_SNAKE_CASE					:       int = 9						):





  """simple docstring"""



  a__     : List[str]  =0
  for length in range(1	,	max_power + 1						):
    result += reversible_numbers(SCREAMING_SNAKE_CASE	,	0	,	[0] * length	,	SCREAMING_SNAKE_CASE						)
  return result


if __name__ == "__main__":
     print(F"""{solution() = }""")






