





from __future__ import annotations

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

lowerCAmelCase :					List[str] 							=TypeVar('''T''')
class 				a_       (    Generic[T]							):





     def __init__(			self		: List[Any]     ,				lowercase		: T						):





        """simple docstring"""




        lowercase_      :List[Any]         =			data
        lowercase_      :Node[T] | None         =			None







     def __str__(			self		: Any						):





        """simple docstring"""




        return F'{self.data}'







class 				a_       (    Generic[T]							):





     def __init__(			self		: Any						):





        """simple docstring"""




        lowercase_      :Node[T] | None         =			None





     def __iter__(			self		: Optional[int]						):





        """simple docstring"""




        lowercase_      :Any         =			self.top
        while node:
           yield node.data
           lowercase_      :Optional[Any]         =			node.next





     def __str__(			self		: str						):





        """simple docstring"""




        return "->".join([str(lowercase						) for item in self]						)





     def __len__(			self		: Union[str, Any]						):





        """simple docstring"""




        return len(tuple(iter(self						)						)						)





     def 							lowercase__				(			self		: Optional[Any]						):





        """simple docstring"""




        return self.top is None





     def 							lowercase__				(			self		: List[str]     ,				lowercase		: T						):





        """simple docstring"""




        lowercase_      :Any         =			Node(lowercase						)
        if not self.is_empty():
           lowercase_      :Tuple         =			self.top
        lowercase_      :Optional[int]         =			node





     def 							lowercase__				(			self		: Union[str, Any]						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: Optional[Any]						):





        """simple docstring"""




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

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







     def 							lowercase__				(			self		: Dict						):





        """simple docstring"""




        lowercase_      :str         =			None


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

 testmod()









'''simple docstring'''


# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase :					Dict 							={
    '''configuration_xmod''': [
        '''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XmodConfig''',
        '''XmodOnnxConfig''',
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Union[str, Any] 							=[
     '''XMOD_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''XmodForCausalLM''',
     '''XmodForMaskedLM''',
     '''XmodForMultipleChoice''',
     '''XmodForQuestionAnswering''',
     '''XmodForSequenceClassification''',
     '''XmodForTokenClassification''',
     '''XmodModel''',
     '''XmodPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_xmod import (
      XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
      XmodForCausalLM,
      XmodForMaskedLM,
      XmodForMultipleChoice,
      XmodForQuestionAnswering,
      XmodForSequenceClassification,
      XmodForTokenClassification,
      XmodModel,
      XmodPreTrainedModel,
  )

else:
 import sys

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


