

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   lowercase_   (  unittest.TestCase					):



						def 						UpperCamelCase_		(      self				:    Optional[int]      , A__				:    int		)   ->					Dict:
								_snake_case						=							3
								_snake_case						=							250

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



						def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					int:
								_snake_case,					_snake_case						=							self._get_tensors(5		)

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

								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(9		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(10		)
								self.assertTrue(criteria(A__      , A__		)		)



						def 						UpperCamelCase_		(      self				:    int		)   ->					str:
								_snake_case						=							MaxLengthCriteria(max_length=10		)

								_snake_case,					_snake_case						=							self._get_tensors(5		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(9		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(10		)
								self.assertTrue(criteria(A__      , A__		)		)



						def 						UpperCamelCase_		(      self				:    List[str]		)   ->					Any:
								_snake_case						=							MaxNewTokensCriteria(start_length=5      , max_new_tokens=5		)

								_snake_case,					_snake_case						=							self._get_tensors(5		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(9		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case,					_snake_case						=							self._get_tensors(10		)
								self.assertTrue(criteria(A__      , A__		)		)

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



						def 						UpperCamelCase_		(      self				:    int		)   ->					Optional[Any]:
								_snake_case,					_snake_case						=							self._get_tensors(5		)

								_snake_case						=							MaxTimeCriteria(max_time=0.1		)
								self.assertFalse(criteria(A__      , A__		)		)

								_snake_case						=							MaxTimeCriteria(max_time=0.1      , initial_timestamp=time.time() - 0.2		)
								self.assertTrue(criteria(A__      , A__		)		)







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

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

								_snake_case						=							validate_stopping_criteria(StoppingCriteriaList()      , 11		)

								self.assertEqual(len(A__		)      , 1		)




from ..utils import DummyObject, requires_backends



class   lowercase_   (  metaclass=__lowercase					):
      UpperCamelCase_      :		Optional[int]										=    ["speech"]



      def __init__(      self				:    str      , *A__				:    List[str]      , **A__				:    Tuple		)   ->					Optional[Any]:
        requires_backends(self      , ['''speech''']		)



class   lowercase_   (  metaclass=__lowercase					):
      UpperCamelCase_      :		Optional[Any]										=    ["speech"]



      def __init__(      self				:    Dict      , *A__				:    int      , **A__				:    int		)   ->					Tuple:
        requires_backends(self      , ['''speech''']		)

