
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_tf_available,
    is_torch_available,
)


lowerCamelCase__    :		Optional[Any]          =   {
    """configuration_speech_to_text""": ["""SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Speech2TextConfig"""],
    """processing_speech_to_text""": ["""Speech2TextProcessor"""],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__    :		int          =   ["""Speech2TextTokenizer"""]

try:
     if not is_speech_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__    :		Union[str, Any]          =   ["""Speech2TextFeatureExtractor"""]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__    :		List[Any]          =   [
         """TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TFSpeech2TextForConditionalGeneration""",
         """TFSpeech2TextModel""",
         """TFSpeech2TextPreTrainedModel""",
     ]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__    :		List[str]          =   [
         """SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """Speech2TextForConditionalGeneration""",
         """Speech2TextModel""",
         """Speech2TextPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
     from .processing_speech_to_text import SpeechaTextProcessor

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_speech_to_text import SpeechaTextTokenizer

     try:
          if not is_speech_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_speech_to_text import (
              TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFSpeechaTextForConditionalGeneration,
              TFSpeechaTextModel,
              TFSpeechaTextPreTrainedModel,
          )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_speech_to_text import (
              SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
              SpeechaTextForConditionalGeneration,
              SpeechaTextModel,
              SpeechaTextPreTrainedModel,
          )

else:
     import sys

     lowerCamelCase__    :		int          =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








from abc import ABC, abstractmethod
from argparse import ArgumentParser



class       _snake_case   (	UpperCAmelCase_							):


 @staticmethod
 @abstractmethod
 def      lowercase__     (					SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   raise NotImplementedError()



 @abstractmethod
 def      lowercase__     (					self):


   '''simple docstring'''




   raise NotImplementedError()






