





'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase_					:    List[Any]      	=			{
    '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:
					lowerCAmelCase_					:    Optional[Any]      	=			[
					    '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:
					lowerCAmelCase_					:    str      	=			[
					    '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:
					lowerCAmelCase_					:    Dict      	=			[
					    '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

					lowerCAmelCase_					:    List[str]      	=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







'''simple docstring'''







from ....utils import logging


lowerCAmelCase_					:    Union[str, Any]      	=			logging.get_logger(__name__)
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				def __init__(  self     :					Tuple					,				__a     :					int					,				__a     :					Any=None					,				__a     :					Optional[int]=20_48					):
								_a								= config.__dict__
								_a								= modal_hidden_size
								if num_labels:
												_a								= num_labels
