

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 				SCREAMING_SNAKE_CASE__ (unittest.TestCase					):





    def 				snake_case_    (				self						,       a):
         lowercase__   :       Dict				=	3
         lowercase__   :       Optional[Any]				=	250

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





    def 				snake_case_    (				self):
         lowercase__				,			lowercase__   :       Any				=	self._get_tensors(5)

         lowercase__   :       Tuple				=	StoppingCriteriaList(
             [
                 MaxLengthCriteria(max_length=10),
                 MaxTimeCriteria(max_time=0.1),
             ])

         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Optional[Any]				=	self._get_tensors(9)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Optional[int]				=	self._get_tensors(10)
         self.assertTrue(criteria(UpperCamelCase__						,       UpperCamelCase__))





    def 				snake_case_    (				self):
         lowercase__   :       Optional[int]				=	MaxLengthCriteria(max_length=10)

         lowercase__				,			lowercase__   :       List[Any]				=	self._get_tensors(5)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Dict				=	self._get_tensors(9)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Tuple				=	self._get_tensors(10)
         self.assertTrue(criteria(UpperCamelCase__						,       UpperCamelCase__))





    def 				snake_case_    (				self):
         lowercase__   :       Optional[Any]				=	MaxNewTokensCriteria(start_length=5						,       max_new_tokens=5)

         lowercase__				,			lowercase__   :       Union[str, Any]				=	self._get_tensors(5)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Union[str, Any]				=	self._get_tensors(9)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__				,			lowercase__   :       Tuple				=	self._get_tensors(10)
         self.assertTrue(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__   :       Tuple				=	StoppingCriteriaList([criteria])
         self.assertEqual(criteria_list.max_length						,       10)





    def 				snake_case_    (				self):
         lowercase__				,			lowercase__   :       List[str]				=	self._get_tensors(5)

         lowercase__   :       List[Any]				=	MaxTimeCriteria(max_time=0.1)
         self.assertFalse(criteria(UpperCamelCase__						,       UpperCamelCase__))

         lowercase__   :       Optional[Any]				=	MaxTimeCriteria(max_time=0.1						,       initial_timestamp=time.time() - 0.2)
         self.assertTrue(criteria(UpperCamelCase__						,       UpperCamelCase__))





    def 				snake_case_    (				self):
         validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])						,       10)

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

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

         self.assertEqual(len(UpperCamelCase__)						,       1)




def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   float      ):



     '''simple docstring'''





     if edge <= 0 or not isinstance(SCREAMING_SNAKE_CASE_     ,					SCREAMING_SNAKE_CASE_      ):
          raise ValueError('Length must be a positive.'      )
     return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   float      ):



     '''simple docstring'''





     if edge <= 0 or not isinstance(SCREAMING_SNAKE_CASE_     ,					SCREAMING_SNAKE_CASE_      ):
          raise ValueError('Length must be a positive.'      )
     return ((15 + (7 * (5 ** (1 / 2)))) / 4) * (edge**3)


if __name__ == "__main__":
       import doctest

       doctest.testmod()

