





'''simple docstring'''






import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate




@dataclass(frozen=snake_case_  )
class 					UpperCAmelCase	(     snake_case_  ):
      # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
      _lowercase:     str			=  field(default='''text-classification'''				,						metadata={'''include_in_asdict_even_if_is_default''': True}  )
      _lowercase:     ClassVar[Features]			=  Features({'''text''': Value('''string'''  )}  )
      _lowercase:     ClassVar[Features]			=  Features({'''labels''': ClassLabel}  )
      _lowercase:     str			=  "text"
      _lowercase:     str			=  "labels"




      def 							lowercase__       (     self     :					Union[str, Any]     ,     __snake_case     :					Tuple    )							-> str:
            if self.label_column not in features:
                  raise ValueError(f"Column {self.label_column} is not present in features."    )
            if not isinstance(features[self.label_column]     ,     __snake_case    ):
                  raise ValueError(f"Column {self.label_column} is not a ClassLabel."    )
            _lowerCAmelCase					=				copy.deepcopy(self    )
            _lowerCAmelCase					=				self.label_schema.copy()
            _lowerCAmelCase					=				features[self.label_column]
            _lowerCAmelCase					=				label_schema
            return task_template




      @property
      def 							lowercase__       (     self     :					List[Any]    )							-> Dict[str, str]:
            return {
                self.text_column: "text",
                self.label_column: "labels",
            }













'''simple docstring'''






from typing import TYPE_CHECKING

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


A__							:  int    ={
    '''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Wav2Vec2Config'''],
    '''feature_extraction_wav2vec2''': ['''Wav2Vec2FeatureExtractor'''],
    '''processing_wav2vec2''': ['''Wav2Vec2Processor'''],
    '''tokenization_wav2vec2''': ['''Wav2Vec2CTCTokenizer''', '''Wav2Vec2Tokenizer'''],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__							:  str    =[
          '''WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''Wav2Vec2ForAudioFrameClassification''',
          '''Wav2Vec2ForCTC''',
          '''Wav2Vec2ForMaskedLM''',
          '''Wav2Vec2ForPreTraining''',
          '''Wav2Vec2ForSequenceClassification''',
          '''Wav2Vec2ForXVector''',
          '''Wav2Vec2Model''',
          '''Wav2Vec2PreTrainedModel''',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__							:  Union[str, Any]    =[
          '''TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TFWav2Vec2ForCTC''',
          '''TFWav2Vec2Model''',
          '''TFWav2Vec2PreTrainedModel''',
          '''TFWav2Vec2ForSequenceClassification''',
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__							:  List[str]    =[
          '''FlaxWav2Vec2ForCTC''',
          '''FlaxWav2Vec2ForPreTraining''',
          '''FlaxWav2Vec2Model''',
          '''FlaxWav2Vec2PreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
      from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
      from .processing_wavaveca import WavaVecaProcessor
      from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_wavaveca import (
                WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                WavaVecaForAudioFrameClassification,
                WavaVecaForCTC,
                WavaVecaForMaskedLM,
                WavaVecaForPreTraining,
                WavaVecaForSequenceClassification,
                WavaVecaForXVector,
                WavaVecaModel,
                WavaVecaPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_wavaveca import (
                TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFWavaVecaForCTC,
                TFWavaVecaForSequenceClassification,
                TFWavaVecaModel,
                TFWavaVecaPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_wavaveca import (
                FlaxWavaVecaForCTC,
                FlaxWavaVecaForPreTraining,
                FlaxWavaVecaModel,
                FlaxWavaVecaPreTrainedModel,
            )


else:
      import sys

      A__							:  Any    =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






