






"""simple docstring"""




from typing import TYPE_CHECKING

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


_snake_case          =   {
    '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:
 _snake_case          =   [
     '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:
 _snake_case          =   [
     '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:
 _snake_case          =   [
     '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

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









"""simple docstring"""




_snake_case          =   '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

_snake_case          =   [{'type': 'code', 'content': INSTALL_CONTENT}]
_snake_case          =   {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}

