



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 						UpperCamelCase_					(   self		:		int      ,				__lowercase		:		Dict	):

											'''simple docstring'''
											__a       =		3
											__a       =		250

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





							def 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											__a     ,					__a       =		self._get_tensors(5	)

											__a       =		StoppingCriteriaList(
											    [
											        MaxLengthCriteria(max_length=10	),
											        MaxTimeCriteria(max_time=0.1	),
											    ]	)

											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(9	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(10	)
											self.assertTrue(criteria(__lowercase      ,				__lowercase	)	)





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											__a       =		MaxLengthCriteria(max_length=10	)

											__a     ,					__a       =		self._get_tensors(5	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(9	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(10	)
											self.assertTrue(criteria(__lowercase      ,				__lowercase	)	)





							def 						UpperCamelCase_					(   self		:		Any	):

											'''simple docstring'''
											__a       =		MaxNewTokensCriteria(start_length=5      ,				max_new_tokens=5	)

											__a     ,					__a       =		self._get_tensors(5	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(9	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a     ,					__a       =		self._get_tensors(10	)
											self.assertTrue(criteria(__lowercase      ,				__lowercase	)	)

											__a       =		StoppingCriteriaList([criteria]	)
											self.assertEqual(criteria_list.max_length      ,				10	)





							def 						UpperCamelCase_					(   self		:		Dict	):

											'''simple docstring'''
											__a     ,					__a       =		self._get_tensors(5	)

											__a       =		MaxTimeCriteria(max_time=0.1	)
											self.assertFalse(criteria(__lowercase      ,				__lowercase	)	)

											__a       =		MaxTimeCriteria(max_time=0.1      ,				initial_timestamp=time.time() - 0.2	)
											self.assertTrue(criteria(__lowercase      ,				__lowercase	)	)







							def 						UpperCamelCase_					(   self		:		str	):

											'''simple docstring'''
											validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10	)]	)      ,				10	)

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

											__a       =		validate_stopping_criteria(StoppingCriteriaList()      ,				11	)

											self.assertEqual(len(__lowercase	)      ,				1	)





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if index == number_of_items:
								return 0
				__a       =		0
				__a       =		0
				__a       =		knapsack(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     index + 1    )
				if weights[index] <= max_weight:
								__a       =		values[index] + knapsack(
								    _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     max_weight - weights[index]				,     index + 1    )
				return max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
