
'''simple docstring'''
from __future__ import annotations

from collections.abc import Iterator
from typing import Generic, TypeVar

a_											=						TypeVar("T")






class    UpperCAmelCase_				(	Generic[T]					):





 def __init__(    self ,       lowercase_):
     snake_case_ :    Dict     			=						data
     snake_case_ :    Optional[int]     			=						None





 def __str__(    self):
     return F'{self.data}'






class    UpperCAmelCase_				(	Generic[T]					):





 def __init__(    self):
     snake_case_ :    str     			=						None





 def __iter__(    self):
     snake_case_ :    int     			=						self.top
     while node:
         yield node.data
         snake_case_ :    Union[str, Any]     			=						node.next





 def __str__(    self):
     return "->".join([str(lowercase_) for item in self])





 def __len__(    self):
     return len(tuple(iter(self)))





 def        snake_case__		(    self):
     return self.top is None





 def        snake_case__		(    self ,       lowercase_):
     snake_case_ :    List[str]     			=						Node(lowercase_)
     if not self.is_empty():
         snake_case_ :    List[str]     			=						self.top
     snake_case_ :    str     			=						node





 def        snake_case__		(    self):
     if self.is_empty():
         raise IndexError("pop from empty stack")
     assert isinstance(self.top ,       lowercase_)
     snake_case_ :    int     			=						self.top
     snake_case_ :    Union[str, Any]     			=						self.top.next
     return pop_node.data





 def        snake_case__		(    self):
     if self.is_empty():
         raise IndexError("peek from empty stack")

     assert self.top is not None
     return self.top.data





 def        snake_case__		(    self):
     snake_case_ :    Union[str, Any]     			=						None


if __name__ == "__main__":
  from doctest import testmod

  testmod()






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_											=						{"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_											=						[
      "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "WavLMForAudioFrameClassification",
      "WavLMForCTC",
      "WavLMForSequenceClassification",
      "WavLMForXVector",
      "WavLMModel",
      "WavLMPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_wavlm import (
        WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        WavLMForAudioFrameClassification,
        WavLMForCTC,
        WavLMForSequenceClassification,
        WavLMForXVector,
        WavLMModel,
        WavLMPreTrainedModel,
    )

else:
  import sys

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




