




from typing import Any


class     UpperCamelCase_   :

    '''simple docstring'''






    def __init__(      self				:     Tuple ,			UpperCAmelCase__				:     Any)						->List[str]:





           '''simple docstring'''

           A__							=   data
           A__							=   None


class     UpperCamelCase_   :

    '''simple docstring'''






    def __init__(      self				:     Tuple)						->Optional[Any]:





           '''simple docstring'''

           A__							=   None


    def 	SCREAMING_SNAKE_CASE							(      self				:     int)						->Optional[Any]:





           '''simple docstring'''

           A__							=   self.head
           while temp is not None:
                  print(temp.data ,			end=''' ''')
                  A__							=   temp.next
           print()


    def 	SCREAMING_SNAKE_CASE							(      self				:     str ,			UpperCAmelCase__				:     Any)						->List[str]:





           '''simple docstring'''

           A__							=   Node(UpperCAmelCase__)
           A__							=   self.head
           A__							=   new_node





    def 	SCREAMING_SNAKE_CASE							(      self				:     int ,			UpperCAmelCase__				:     Tuple ,			UpperCAmelCase__				:     List[str])						->Dict:





           '''simple docstring'''

           if node_data_a == node_data_a:
                  return
           else:
                  A__							=   self.head
                  while node_a is not None and node_a.data != node_data_a:
                         A__							=   node_a.next

                  A__							=   self.head
                  while node_a is not None and node_a.data != node_data_a:
                         A__							=   node_a.next

                  if node_a is None or node_a is None:
                         return

                  A__			,							A__							=   node_a.data, node_a.data


if __name__ == "__main__":
     _lowerCamelCase     :		int								=       LinkedList()
     for i in range(5, 0, -1):
          ll.push(i)

     ll.print_list()

     ll.swap_nodes(1, 4)
     print("""After swapping""")
     ll.print_list()








from typing import TYPE_CHECKING

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


_lowerCamelCase     :		Tuple								=       {
    """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     :		Optional[int]								=       ["""Speech2TextFeatureExtractor"""]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Optional[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[Any]								=       [
      """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     :		Union[str, Any]								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


