


"""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 						_A  (  unittest.TestCase  ):







    """simple docstring"""




    def 	__snake_case							(					self				:    Optional[Any]				, __UpperCAmelCase				:    str):
      a						:		Optional[int]      							=			3
      a						:		List[Any]      							=			250

      a						:		Optional[Any]      							=			ids_tensor((batch_size, length)				, __UpperCAmelCase)
      a						:		List[Any]      							=			torch.ones((batch_size, length)				, device=__UpperCAmelCase				, dtype=torch.float) / length
      return input_ids, scores






    def 	__snake_case							(					self				:    Union[str, Any]):
      a							,		a						:		List[Any]      							=			self._get_tensors(5)

      a						:		Union[str, Any]      							=			StoppingCriteriaList(
          [
              MaxLengthCriteria(max_length=10),
              MaxTimeCriteria(max_time=0.1),
          ])

      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		Any      							=			self._get_tensors(9)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		Any      							=			self._get_tensors(10)
      self.assertTrue(criteria(__UpperCAmelCase				, __UpperCAmelCase))






    def 	__snake_case							(					self				:    Union[str, Any]):
      a						:		Any      							=			MaxLengthCriteria(max_length=10)

      a							,		a						:		Optional[Any]      							=			self._get_tensors(5)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		List[Any]      							=			self._get_tensors(9)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		List[Any]      							=			self._get_tensors(10)
      self.assertTrue(criteria(__UpperCAmelCase				, __UpperCAmelCase))






    def 	__snake_case							(					self				:    Optional[Any]):
      a						:		str      							=			MaxNewTokensCriteria(start_length=5				, max_new_tokens=5)

      a							,		a						:		str      							=			self._get_tensors(5)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		str      							=			self._get_tensors(9)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a							,		a						:		Dict      							=			self._get_tensors(10)
      self.assertTrue(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a						:		Dict      							=			StoppingCriteriaList([criteria])
      self.assertEqual(criteria_list.max_length				, 10)






    def 	__snake_case							(					self				:    str):
      a							,		a						:		Dict      							=			self._get_tensors(5)

      a						:		List[str]      							=			MaxTimeCriteria(max_time=0.1)
      self.assertFalse(criteria(__UpperCAmelCase				, __UpperCAmelCase))

      a						:		Dict      							=			MaxTimeCriteria(max_time=0.1				, initial_timestamp=time.time() - 0.2)
      self.assertTrue(criteria(__UpperCAmelCase				, __UpperCAmelCase))






    def 	__snake_case							(					self				:    Union[str, Any]):
      validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])				, 10)

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

      a						:		Tuple      							=			validate_stopping_criteria(StoppingCriteriaList()				, 11)

      self.assertEqual(len(__UpperCAmelCase)				, 1)










"""simple docstring"""







class 						_A  :







    """simple docstring"""




    def __init__(					self				:    int				, __UpperCAmelCase				:    int):
      a						:		Tuple      							=			size
      a						:		Dict      							=			[0] * size
      a						:		Optional[int]      							=			[0] * size






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return index | (index + 1)






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return (index & (index + 1)) - 1






    def 	__snake_case							(					self				:    List[str]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      a						:		Union[str, Any]      							=			value
      while index < self.size:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase) + 1
        if current_left_border == index:
          a						:		Optional[int]      							=			value
        else:
          a						:		Any      							=			max(__UpperCAmelCase				, __UpperCAmelCase				, __UpperCAmelCase)
        a						:		Optional[int]      							=			self.get_next(__UpperCAmelCase)






    def 	__snake_case							(					self				:    Union[str, Any]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      right -= 1  # Because of right is exclusive
      a						:		List[str]      							=			0
      while left <= right:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase)
        if left <= current_left:
          a						:		Optional[int]      							=			max(__UpperCAmelCase				, self.tree[right])
          a						:		Optional[Any]      							=			current_left
        else:
          a						:		List[str]      							=			max(__UpperCAmelCase				, self.arr[right])
          right -= 1
      return result


if __name__ == "__main__":
 import doctest

 doctest.testmod()






