






from typing import TYPE_CHECKING

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


__magic_name__   :  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:
       __magic_name__   :  List[str]        =							['''Speech2TextTokenizer''']

try:
       if not is_speech_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __magic_name__   :  Optional[int]        =							['''Speech2TextFeatureExtractor''']

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __magic_name__   :  List[str]        =							[
           '''TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''TFSpeech2TextForConditionalGeneration''',
           '''TFSpeech2TextModel''',
           '''TFSpeech2TextPreTrainedModel''',
       ]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __magic_name__   :  Optional[int]        =							[
           '''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

       __magic_name__   :  Any        =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











__magic_name__   :  str        =							8.314_4598
def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase) ->			float:
      """simple docstring"""

      if temperature < 0:
            raise Exception('Temperature cannot be less than 0 K')
      if molar_mass <= 0:
            raise Exception('Molar mass cannot be less than or equal to 0 kg/mol')
      else:
            return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
       import doctest

       # run doctest
       doctest.testmod()

       # example
       __magic_name__   :  List[Any]        =							300
       __magic_name__   :  Union[str, Any]        =							28
       __magic_name__   :  str        =							rms_speed_of_molecule(temperature, molar_mass)
       print(F'Vrms of Nitrogen gas at 300 K is {vrms} m/s')



