from typing import TYPE_CHECKING

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


_lowerCamelCase       : str      					=		{
    "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       : int      					=		[
							    "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       : int      					=		[
							    "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       : Union[str, Any]      					=		[
							    "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       : Any      					=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import pyarrow as pa


if TYPE_CHECKING:
							from .features import FeatureType




@dataclass
class 		__A   :
						UpperCamelCase      =       42
						UpperCamelCase      =       None
						# Automatically constructed
						UpperCamelCase      =       "dict"
						UpperCamelCase      =       None
						UpperCamelCase      =       field(default="""Translation"""       ,    init=UpperCamelCase__       ,    repr=UpperCamelCase__      )

						def __call__(		self :Union[str, Any]			):
										'''simple docstring'''

										return pa.struct({lang: pa.string() for lang in sorted(self.languages			)}			)


						def      A__    (		self :List[Any]			):
										'''simple docstring'''

										from .features import Value

										return {k: Value("""string"""			) for k in sorted(self.languages			)}




@dataclass
class 		__A   :
						UpperCamelCase      =       None
						UpperCamelCase      =       None
						UpperCamelCase      =       None
						# Automatically constructed
						UpperCamelCase      =       "dict"
						UpperCamelCase      =       None
						UpperCamelCase      =       field(default="""TranslationVariableLanguages"""       ,    init=UpperCamelCase__       ,    repr=UpperCamelCase__      )

						def      A__    (		self :Optional[Any]			):
										'''simple docstring'''

										__magic_name__						:						List[Any]										=sorted(set(self.languages			)			) if self.languages else None
										__magic_name__						:						Optional[int]										=len(self.languages			) if self.languages else None

						def __call__(		self :List[str]			):
										'''simple docstring'''

										return pa.struct({"""language""": pa.list_(pa.string()			), """translation""": pa.list_(pa.string()			)}			)

						def      A__    (		self :str     ,			__snake_case :str			):
										'''simple docstring'''

										__magic_name__						:						Optional[int]										=set(self.languages			)
										if self.languages and set(__snake_case			) - lang_set:
														raise ValueError(
														    f"Some languages in example ({', '.join(sorted(set(__snake_case			) - lang_set			)			)}) are not in valid set ({', '.join(__snake_case			)})."			)

										# Convert dictionary into tuples, splitting out cases where there are
										# multiple translations for a single language.
										__magic_name__						:						Any										=[]
										for lang, text in translation_dict.items():
														if isinstance(__snake_case     ,			__snake_case			):
																		translation_tuples.append((lang, text)			)
														else:
																		translation_tuples.extend([(lang, el) for el in text]			)

        # Ensure translations are in ascending order by language code.
										__magic_name__					,			__magic_name__						:						List[str]										=zip(*sorted(__snake_case			)			)

										return {"language": languages, "translation": translations}


						def      A__    (		self :List[Any]			):
										'''simple docstring'''

										from .features import Sequence, Value

										return {
										    "language": Sequence(Value("""string"""			)			),
										    "translation": Sequence(Value("""string"""			)			),
										}




