






"""simple docstring"""
from typing import TYPE_CHECKING

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


_lowerCAmelCase         =							{
    "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         =							[
							    "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         =							[
							    "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         =							[
							    "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         =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase         =							{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCAmelCase         =							[
							    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "LukeForEntityClassification",
							    "LukeForEntityPairClassification",
							    "LukeForEntitySpanClassification",
							    "LukeForMultipleChoice",
							    "LukeForQuestionAnswering",
							    "LukeForSequenceClassification",
							    "LukeForTokenClassification",
							    "LukeForMaskedLM",
							    "LukeModel",
							    "LukePreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
							from .tokenization_luke import LukeTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_luke import (
														    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LukeForEntityClassification,
														    LukeForEntityPairClassification,
														    LukeForEntitySpanClassification,
														    LukeForMaskedLM,
														    LukeForMultipleChoice,
														    LukeForQuestionAnswering,
														    LukeForSequenceClassification,
														    LukeForTokenClassification,
														    LukeModel,
														    LukePreTrainedModel,
														)

else:
							import sys

							_lowerCAmelCase         =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

