

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 		__magic_name__    (		self					,  __snake_case					)   -> Tuple:




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

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





			def 		__magic_name__    (		self					)   -> List[Any]:




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

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

						self.assertFalse(criteria(__snake_case					,  __snake_case					)					)

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

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





			def 		__magic_name__    (		self					)   -> Tuple:




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

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

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

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





			def 		__magic_name__    (		self					)   -> Dict:




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

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

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

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

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





			def 		__magic_name__    (		self					)   -> str:




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

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

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





			def 		__magic_name__    (		self					)   -> Union[str, Any]:




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

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

						__a        =validate_stopping_criteria(StoppingCriteriaList()					,  11					)

						self.assertEqual(len(__snake_case					)					,  1					)









from __future__ import annotations






def        UpperCamelCase_(							_snake_case   :  int	):




			"""simple docstring"""






			__a        =str(_snake_case	)
			return len(_snake_case	) == 9 and set(_snake_case	) == set('123456789'	)






def        UpperCamelCase_(							):




			"""simple docstring"""






			for base_num in range(9999       ,     4999       ,     -1	):
						__a        =100002 * base_num
						if is_9_pandigital(_snake_case	):
									return candidate

			for base_num in range(333       ,     99       ,     -1	):
						__a        =1002003 * base_num
						if is_9_pandigital(_snake_case	):
									return candidate

			return None


if __name__ == "__main__":
						print(f'''{solution() = }''')






