

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 						__magic_name__    (       unittest.TestCase    ):


 def _UpperCamelCase	(						self		: List[str]			,						lowerCAmelCase__		: Union[str, Any]    )    ->      Union[str, Any]:
   UpperCAmelCase					      =  3
   UpperCAmelCase					      =  2_5_0

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


 def _UpperCamelCase	(						self		: Optional[int]    )    ->      List[Any]:
   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(5    )

   UpperCAmelCase					      =  StoppingCriteriaList(
       [
           MaxLengthCriteria(max_length=1_0    ),
           MaxTimeCriteria(max_time=0.1    ),
       ]    )

   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(9    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(1_0    )
   self.assertTrue(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )


 def _UpperCamelCase	(						self		: List[str]    )    ->      List[Any]:
   UpperCAmelCase					      =  MaxLengthCriteria(max_length=1_0    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(5    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(9    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(1_0    )
   self.assertTrue(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )


 def _UpperCamelCase	(						self		: Any    )    ->      Union[str, Any]:
   UpperCAmelCase					      =  MaxNewTokensCriteria(start_length=5			,						max_new_tokens=5    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(5    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(9    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(1_0    )
   self.assertTrue(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

   UpperCAmelCase					      =  StoppingCriteriaList([criteria]    )
   self.assertEqual(criteria_list.max_length			,						1_0    )


 def _UpperCamelCase	(						self		: Dict    )    ->      Any:
   UpperCAmelCase      ,	UpperCAmelCase					      =  self._get_tensors(5    )

   UpperCAmelCase					      =  MaxTimeCriteria(max_time=0.1    )
   self.assertFalse(criteria(lowerCAmelCase__			,						lowerCAmelCase__    )    )

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


 def _UpperCamelCase	(						self		: Tuple    )    ->      Union[str, Any]:
   validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0    )]    )			,						1_0    )

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

   UpperCAmelCase					      =  validate_stopping_criteria(StoppingCriteriaList()			,						1_1    )

   self.assertEqual(len(lowerCAmelCase__    )			,						1    )






def      _lowerCAmelCase(	__A   ,       __A   ,       __A			):
  if n == 0:
    return 1

  elif n % 2 == 1:
    return (binary_exponentiation(__A   ,       n - 1   ,       __A			) * a) % mod

  else:
    UpperCAmelCase					      =  binary_exponentiation(__A   ,       n / 2   ,       __A			)
    return (b * b) % mod


# a prime number
lowerCAmelCase__       = 701

lowerCAmelCase__       = 1000000000
lowerCAmelCase__       = 10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)





print((a / b) % p == (a * b ** (p - 2)) % p)



