




'''simple docstring'''





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  _snake_case		(	unittest.TestCase							):




			def    lowerCAmelCase__				(					self				,							a__							)				->				List[Any]:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				Any:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				str:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				Any:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				List[str]:

										'''simple docstring'''




										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							)









'''simple docstring'''





from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


lowercase_		       =  datasets.utils.logging.get_logger(__name__)






class __A			(  folder_based_builder.FolderBasedBuilderConfig						):



 '''simple docstring'''







 __lowerCamelCase    :       bool          =       None
 __lowerCamelCase    :       bool          =       None






class __A			(  folder_based_builder.FolderBasedBuilder						):



 '''simple docstring'''







 __lowerCamelCase    :       int          =       datasets.Audio()
 __lowerCamelCase    :       str          =       'audio'
 __lowerCamelCase    :       Optional[Any]          =       AudioFolderConfig
 __lowerCamelCase    :       List[str]  # definition at the bottom of the script
 __lowerCamelCase    :       Union[str, Any]          =       AudioClassification(audio_column='audio'   ,   label_column='label'						)





lowercase_		       =  [
    ".aiff",
    ".au",
    ".avr",
    ".caf",
    ".flac",
    ".htk",
    ".svx",
    ".mat4",
    ".mat5",
    ".mpc2k",
    ".ogg",
    ".paf",
    ".pvf",
    ".raw",
    ".rf64",
    ".sd2",
    ".sds",
    ".ircam",
    ".voc",
    ".w64",
    ".wav",
    ".nist",
    ".wavex",
    ".wve",
    ".xi",
    ".mp3",
    ".opus",
]
lowercase_		       =  AUDIO_EXTENSIONS



