



'''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  ,__UpperCAmelCase				)   ->		Optional[int]:
      lowerCAmelCase__			:  Optional[int]											= 3
      lowerCAmelCase__			:  Dict											= 250

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




  def 							UpperCAmelCase_     (   self				)   ->		Tuple:
      lowerCAmelCase__				,       lowerCAmelCase__			:  List[str]											= self._get_tensors(5				)

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

      self.assertFalse(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

      lowerCAmelCase__				,       lowerCAmelCase__			:  List[str]											= self._get_tensors(9				)
      self.assertFalse(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

      lowerCAmelCase__				,       lowerCAmelCase__			:  Tuple											= self._get_tensors(10				)
      self.assertTrue(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)




  def 							UpperCAmelCase_     (   self				)   ->		List[str]:
      lowerCAmelCase__			:  Union[str, Any]											= MaxLengthCriteria(max_length=10				)

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

      lowerCAmelCase__				,       lowerCAmelCase__			:  int											= self._get_tensors(9				)
      self.assertFalse(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

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




  def 							UpperCAmelCase_     (   self				)   ->		str:
      lowerCAmelCase__			:  str											= MaxNewTokensCriteria(start_length=5  ,max_new_tokens=5				)

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

      lowerCAmelCase__				,       lowerCAmelCase__			:  Dict											= self._get_tensors(9				)
      self.assertFalse(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

      lowerCAmelCase__				,       lowerCAmelCase__			:  int											= self._get_tensors(10				)
      self.assertTrue(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

      lowerCAmelCase__			:  Optional[int]											= StoppingCriteriaList([criteria]				)
      self.assertEqual(criteria_list.max_length  ,10				)




  def 							UpperCAmelCase_     (   self				)   ->		List[str]:
      lowerCAmelCase__				,       lowerCAmelCase__			:  str											= self._get_tensors(5				)

      lowerCAmelCase__			:  int											= MaxTimeCriteria(max_time=0.1				)
      self.assertFalse(criteria(__UpperCAmelCase  ,__UpperCAmelCase				)				)

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






  def 							UpperCAmelCase_     (   self				)   ->		Union[str, Any]:
      validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10				)]				)  ,10				)

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

      lowerCAmelCase__			:  Union[str, Any]											= validate_stopping_criteria(StoppingCriteriaList()  ,11				)

      self.assertEqual(len(__UpperCAmelCase				)  ,1				)







'''simple docstring'''





def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    if any(not isinstance(UpperCamelCase							,   UpperCamelCase      ) or x < 0 for x in sequence      ):
        raise TypeError("""Sequence must be list of non-negative integers"""      )
    for _ in range(len(UpperCamelCase      )      ):
        for i, (rod_upper, rod_lower) in enumerate(zip(UpperCamelCase							,   sequence[1:]      )      ):
            if rod_upper > rod_lower:
                sequence[i] -= rod_upper - rod_lower
                sequence[i + 1] += rod_upper - rod_lower
    return sequence


if __name__ == "__main__":
 assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
 assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]


