





from typing import TYPE_CHECKING

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


a__: List[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:
       a__: Optional[Any]							   =						['Speech2TextTokenizer']

try:
       if not is_speech_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__: Any							   =						['Speech2TextFeatureExtractor']

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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__: 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

       a__: Tuple							   =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












class        SCREAMING_SNAKE_CASE__					:



 def __init__(				self,__lowerCamelCase					):
        A__		   =		size
        A__		   =		[0] * size
        A__		   =		[0] * size



 @staticmethod
 def 							UpperCamelCase     (				__lowerCamelCase					):
        return index | (index + 1)



 @staticmethod
 def 							UpperCamelCase     (				__lowerCamelCase					):
        return (index & (index + 1)) - 1



 def 							UpperCamelCase     (				self,__lowerCamelCase,__lowerCamelCase					):
        A__		   =		value
        while index < self.size:
               A__		   =		self.get_prev(__lowerCamelCase					) + 1
               if current_left_border == index:
                      A__		   =		value
               else:
                      A__		   =		max(__lowerCamelCase,__lowerCamelCase,__lowerCamelCase					)
               A__		   =		self.get_next(__lowerCamelCase					)




 def 							UpperCamelCase     (				self,__lowerCamelCase,__lowerCamelCase					):
        right -= 1  # Because of right is exclusive
        A__		   =		0
        while left <= right:
               A__		   =		self.get_prev(__lowerCamelCase					)
               if left <= current_left:
                      A__		   =		max(__lowerCamelCase,self.tree[right]					)
                      A__		   =		current_left
               else:
                      A__		   =		max(__lowerCamelCase,self.arr[right]					)
                      right -= 1
        return result


if __name__ == "__main__":
       import doctest

       doctest.testmod()





