


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowerCamelCase   	=  {
    '''auto_factory''': ['''get_values'''],
    '''configuration_auto''': ['''ALL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CONFIG_MAPPING''', '''MODEL_NAMES_MAPPING''', '''AutoConfig'''],
    '''feature_extraction_auto''': ['''FEATURE_EXTRACTOR_MAPPING''', '''AutoFeatureExtractor'''],
    '''image_processing_auto''': ['''IMAGE_PROCESSOR_MAPPING''', '''AutoImageProcessor'''],
    '''processing_auto''': ['''PROCESSOR_MAPPING''', '''AutoProcessor'''],
    '''tokenization_auto''': ['''TOKENIZER_MAPPING''', '''AutoTokenizer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase   	=  [
           '''MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_AUDIO_XVECTOR_MAPPING''',
           '''MODEL_FOR_BACKBONE_MAPPING''',
           '''MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING''',
           '''MODEL_FOR_CAUSAL_LM_MAPPING''',
           '''MODEL_FOR_CTC_MAPPING''',
           '''MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
           '''MODEL_FOR_DEPTH_ESTIMATION_MAPPING''',
           '''MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_IMAGE_SEGMENTATION_MAPPING''',
           '''MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING''',
           '''MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
           '''MODEL_FOR_MASKED_LM_MAPPING''',
           '''MODEL_FOR_MASK_GENERATION_MAPPING''',
           '''MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
           '''MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
           '''MODEL_FOR_OBJECT_DETECTION_MAPPING''',
           '''MODEL_FOR_PRETRAINING_MAPPING''',
           '''MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
           '''MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
           '''MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
           '''MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
           '''MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
           '''MODEL_FOR_TEXT_ENCODING_MAPPING''',
           '''MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING''',
           '''MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_VISION_2_SEQ_MAPPING''',
           '''MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING''',
           '''MODEL_MAPPING''',
           '''MODEL_WITH_LM_HEAD_MAPPING''',
           '''MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
           '''MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING''',
           '''AutoModel''',
           '''AutoBackbone''',
           '''AutoModelForAudioClassification''',
           '''AutoModelForAudioFrameClassification''',
           '''AutoModelForAudioXVector''',
           '''AutoModelForCausalLM''',
           '''AutoModelForCTC''',
           '''AutoModelForDepthEstimation''',
           '''AutoModelForImageClassification''',
           '''AutoModelForImageSegmentation''',
           '''AutoModelForInstanceSegmentation''',
           '''AutoModelForMaskGeneration''',
           '''AutoModelForTextEncoding''',
           '''AutoModelForMaskedImageModeling''',
           '''AutoModelForMaskedLM''',
           '''AutoModelForMultipleChoice''',
           '''AutoModelForNextSentencePrediction''',
           '''AutoModelForObjectDetection''',
           '''AutoModelForPreTraining''',
           '''AutoModelForQuestionAnswering''',
           '''AutoModelForSemanticSegmentation''',
           '''AutoModelForSeq2SeqLM''',
           '''AutoModelForSequenceClassification''',
           '''AutoModelForSpeechSeq2Seq''',
           '''AutoModelForTableQuestionAnswering''',
           '''AutoModelForTokenClassification''',
           '''AutoModelForUniversalSegmentation''',
           '''AutoModelForVideoClassification''',
           '''AutoModelForVision2Seq''',
           '''AutoModelForVisualQuestionAnswering''',
           '''AutoModelForDocumentQuestionAnswering''',
           '''AutoModelWithLMHead''',
           '''AutoModelForZeroShotImageClassification''',
           '''AutoModelForZeroShotObjectDetection''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase   	=  [
           '''TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
           '''TF_MODEL_FOR_CAUSAL_LM_MAPPING''',
           '''TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
           '''TF_MODEL_FOR_MASK_GENERATION_MAPPING''',
           '''TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
           '''TF_MODEL_FOR_MASKED_LM_MAPPING''',
           '''TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
           '''TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
           '''TF_MODEL_FOR_PRETRAINING_MAPPING''',
           '''TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
           '''TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
           '''TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
           '''TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
           '''TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
           '''TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
           '''TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
           '''TF_MODEL_FOR_TEXT_ENCODING_MAPPING''',
           '''TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
           '''TF_MODEL_FOR_VISION_2_SEQ_MAPPING''',
           '''TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
           '''TF_MODEL_MAPPING''',
           '''TF_MODEL_WITH_LM_HEAD_MAPPING''',
           '''TFAutoModel''',
           '''TFAutoModelForAudioClassification''',
           '''TFAutoModelForCausalLM''',
           '''TFAutoModelForImageClassification''',
           '''TFAutoModelForMaskedImageModeling''',
           '''TFAutoModelForMaskedLM''',
           '''TFAutoModelForMaskGeneration''',
           '''TFAutoModelForMultipleChoice''',
           '''TFAutoModelForNextSentencePrediction''',
           '''TFAutoModelForPreTraining''',
           '''TFAutoModelForDocumentQuestionAnswering''',
           '''TFAutoModelForQuestionAnswering''',
           '''TFAutoModelForSemanticSegmentation''',
           '''TFAutoModelForSeq2SeqLM''',
           '''TFAutoModelForSequenceClassification''',
           '''TFAutoModelForSpeechSeq2Seq''',
           '''TFAutoModelForTableQuestionAnswering''',
           '''TFAutoModelForTextEncoding''',
           '''TFAutoModelForTokenClassification''',
           '''TFAutoModelForVision2Seq''',
           '''TFAutoModelForZeroShotImageClassification''',
           '''TFAutoModelWithLMHead''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase   	=  [
           '''FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
           '''FLAX_MODEL_FOR_CAUSAL_LM_MAPPING''',
           '''FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
           '''FLAX_MODEL_FOR_MASKED_LM_MAPPING''',
           '''FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
           '''FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
           '''FLAX_MODEL_FOR_PRETRAINING_MAPPING''',
           '''FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
           '''FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
           '''FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
           '''FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
           '''FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
           '''FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING''',
           '''FLAX_MODEL_MAPPING''',
           '''FlaxAutoModel''',
           '''FlaxAutoModelForCausalLM''',
           '''FlaxAutoModelForImageClassification''',
           '''FlaxAutoModelForMaskedLM''',
           '''FlaxAutoModelForMultipleChoice''',
           '''FlaxAutoModelForNextSentencePrediction''',
           '''FlaxAutoModelForPreTraining''',
           '''FlaxAutoModelForQuestionAnswering''',
           '''FlaxAutoModelForSeq2SeqLM''',
           '''FlaxAutoModelForSequenceClassification''',
           '''FlaxAutoModelForSpeechSeq2Seq''',
           '''FlaxAutoModelForTokenClassification''',
           '''FlaxAutoModelForVision2Seq''',
       ]


if TYPE_CHECKING:
       from .auto_factory import get_values
       from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
       from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
       from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
       from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
       from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_auto import (
                  MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
                  MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
                  MODEL_FOR_AUDIO_XVECTOR_MAPPING,
                  MODEL_FOR_BACKBONE_MAPPING,
                  MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
                  MODEL_FOR_CAUSAL_LM_MAPPING,
                  MODEL_FOR_CTC_MAPPING,
                  MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
                  MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
                  MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
                  MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
                  MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
                  MODEL_FOR_MASK_GENERATION_MAPPING,
                  MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
                  MODEL_FOR_MASKED_LM_MAPPING,
                  MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
                  MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
                  MODEL_FOR_OBJECT_DETECTION_MAPPING,
                  MODEL_FOR_PRETRAINING_MAPPING,
                  MODEL_FOR_QUESTION_ANSWERING_MAPPING,
                  MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
                  MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
                  MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
                  MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
                  MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
                  MODEL_FOR_TEXT_ENCODING_MAPPING,
                  MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
                  MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING,
                  MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING,
                  MODEL_FOR_VISION_2_SEQ_MAPPING,
                  MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING,
                  MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
                  MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING,
                  MODEL_MAPPING,
                  MODEL_WITH_LM_HEAD_MAPPING,
                  AutoBackbone,
                  AutoModel,
                  AutoModelForAudioClassification,
                  AutoModelForAudioFrameClassification,
                  AutoModelForAudioXVector,
                  AutoModelForCausalLM,
                  AutoModelForCTC,
                  AutoModelForDepthEstimation,
                  AutoModelForDocumentQuestionAnswering,
                  AutoModelForImageClassification,
                  AutoModelForImageSegmentation,
                  AutoModelForInstanceSegmentation,
                  AutoModelForMaskedImageModeling,
                  AutoModelForMaskedLM,
                  AutoModelForMaskGeneration,
                  AutoModelForMultipleChoice,
                  AutoModelForNextSentencePrediction,
                  AutoModelForObjectDetection,
                  AutoModelForPreTraining,
                  AutoModelForQuestionAnswering,
                  AutoModelForSemanticSegmentation,
                  AutoModelForSeqaSeqLM,
                  AutoModelForSequenceClassification,
                  AutoModelForSpeechSeqaSeq,
                  AutoModelForTableQuestionAnswering,
                  AutoModelForTextEncoding,
                  AutoModelForTokenClassification,
                  AutoModelForUniversalSegmentation,
                  AutoModelForVideoClassification,
                  AutoModelForVisionaSeq,
                  AutoModelForVisualQuestionAnswering,
                  AutoModelForZeroShotImageClassification,
                  AutoModelForZeroShotObjectDetection,
                  AutoModelWithLMHead,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_auto import (
                  TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
                  TF_MODEL_FOR_CAUSAL_LM_MAPPING,
                  TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
                  TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
                  TF_MODEL_FOR_MASK_GENERATION_MAPPING,
                  TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
                  TF_MODEL_FOR_MASKED_LM_MAPPING,
                  TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
                  TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
                  TF_MODEL_FOR_PRETRAINING_MAPPING,
                  TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
                  TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
                  TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
                  TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
                  TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
                  TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
                  TF_MODEL_FOR_TEXT_ENCODING_MAPPING,
                  TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
                  TF_MODEL_FOR_VISION_2_SEQ_MAPPING,
                  TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
                  TF_MODEL_MAPPING,
                  TF_MODEL_WITH_LM_HEAD_MAPPING,
                  TFAutoModel,
                  TFAutoModelForAudioClassification,
                  TFAutoModelForCausalLM,
                  TFAutoModelForDocumentQuestionAnswering,
                  TFAutoModelForImageClassification,
                  TFAutoModelForMaskedImageModeling,
                  TFAutoModelForMaskedLM,
                  TFAutoModelForMaskGeneration,
                  TFAutoModelForMultipleChoice,
                  TFAutoModelForNextSentencePrediction,
                  TFAutoModelForPreTraining,
                  TFAutoModelForQuestionAnswering,
                  TFAutoModelForSemanticSegmentation,
                  TFAutoModelForSeqaSeqLM,
                  TFAutoModelForSequenceClassification,
                  TFAutoModelForSpeechSeqaSeq,
                  TFAutoModelForTableQuestionAnswering,
                  TFAutoModelForTextEncoding,
                  TFAutoModelForTokenClassification,
                  TFAutoModelForVisionaSeq,
                  TFAutoModelForZeroShotImageClassification,
                  TFAutoModelWithLMHead,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_auto import (
                  FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
                  FLAX_MODEL_FOR_CAUSAL_LM_MAPPING,
                  FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
                  FLAX_MODEL_FOR_MASKED_LM_MAPPING,
                  FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
                  FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
                  FLAX_MODEL_FOR_PRETRAINING_MAPPING,
                  FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
                  FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
                  FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
                  FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
                  FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
                  FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING,
                  FLAX_MODEL_MAPPING,
                  FlaxAutoModel,
                  FlaxAutoModelForCausalLM,
                  FlaxAutoModelForImageClassification,
                  FlaxAutoModelForMaskedLM,
                  FlaxAutoModelForMultipleChoice,
                  FlaxAutoModelForNextSentencePrediction,
                  FlaxAutoModelForPreTraining,
                  FlaxAutoModelForQuestionAnswering,
                  FlaxAutoModelForSeqaSeqLM,
                  FlaxAutoModelForSequenceClassification,
                  FlaxAutoModelForSpeechSeqaSeq,
                  FlaxAutoModelForTokenClassification,
                  FlaxAutoModelForVisionaSeq,
              )

else:
       import sys

       __lowerCamelCase   	=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


lowercase_      :							Optional[int]    							=					set()
lowercase_      :							List[Any]    							=					get_logger(__name__)


def 				__SCREAMING_SNAKE_CASE    (     snake_case_ = None		):

						'''simple docstring'''


						def decorator(snake_case_		):
												global _emitted_deprecation_warnings

												if inspect.isclass(snake_case_		):
																		_UpperCAmelCase						=	deprecated_class_or_function.__init__
																		_UpperCAmelCase						=	deprecated_class_or_function.__name__
												else:
																		_UpperCAmelCase						=	deprecated_class_or_function
																		_UpperCAmelCase						=	deprecated_function.__name__
																		# Support deprecating __init__ class method: class name instead
																		_UpperCAmelCase						=	name if name != "__init__" else deprecated_function.__qualname__.split("."		)[-2]

												_UpperCAmelCase						=	(
												    f"""{name} is deprecated and will be removed in the next major version of datasets.""" + f""" {help_message}"""
												    if help_message
												    else ""
												)

												@wraps(snake_case_		)
												def wrapper(*snake_case_      ,       **snake_case_		):
																		_UpperCAmelCase						=	hash(snake_case_		)
																		if func_hash not in _emitted_deprecation_warnings:
																								warnings.warn(snake_case_      ,       category=snake_case_      ,       stacklevel=2		)
																								_emitted_deprecation_warnings.add(snake_case_		)
																		return deprecated_function(*snake_case_      ,       **snake_case_		)

												_UpperCAmelCase						=	"deprecated"

												if inspect.isclass(snake_case_		):
																		_UpperCAmelCase						=	wrapper
																		return deprecated_class_or_function
												else:
																		return wrapper

						return decorator






class        __lowerCAmelCase					(			enum.EnumMeta					):







			def __getattribute__(			cls       :     str       ,       snake_case__       :     Optional[Any] ):




									"""simple docstring"""


									_UpperCAmelCase						=	super().__getattribute__(snake_case__ )
									if isinstance(snake_case__       ,       enum.Enum ) and obj._on_access:
															obj._on_access()
									return obj







			def __getitem__(			cls       :     str       ,       snake_case__       :     Union[str, Any] ):




									"""simple docstring"""


									_UpperCAmelCase						=	super().__getitem__(snake_case__ )
									if member._on_access:
															member._on_access()
									return member







			def __call__(			cls       :     Dict       ,       snake_case__       :     Any       ,       snake_case__       :     List[str]=None       ,       *, snake_case__       :     Optional[int]=None       ,       snake_case__       :     List[Any]=None       ,       snake_case__       :     Tuple=None       ,       snake_case__       :     List[Any]=1 ):




									"""simple docstring"""


									_UpperCAmelCase						=	super().__call__(snake_case__       ,       snake_case__       ,       module=snake_case__       ,       qualname=snake_case__       ,       type=snake_case__       ,       start=snake_case__ )
									if isinstance(snake_case__       ,       enum.Enum ) and obj._on_access:
															obj._on_access()
									return obj






class        __lowerCAmelCase					(			enum.Enum   ,						metaclass=UpperCAmelCase__					):







			def __new__(			cls       :     Any       ,       snake_case__       :     Dict ):




									"""simple docstring"""


									_UpperCAmelCase						=	object.__new__(cls )
									_UpperCAmelCase						=	value
									_UpperCAmelCase						=	member.deprecate
									return member







			@property
			def UpperCamelCase     (			self       :     str ):




									"""simple docstring"""


									return ""







			def UpperCamelCase     (			self       :     Optional[int] ):




									"""simple docstring"""


									_UpperCAmelCase						=	F""" {self.help_message}""" if self.help_message else ""
									warnings.warn(
									    F"""'{self.__objclass__.__name__}' is deprecated and will be removed in the next major version of datasets."""
									    + help_message       ,       snake_case__       ,       stacklevel=3       ,       )




