






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a    =       {
    'configuration_dpr': ['DPR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DPRConfig'],
    'tokenization_dpr': [
        'DPRContextEncoderTokenizer',
        'DPRQuestionEncoderTokenizer',
        'DPRReaderOutput',
        'DPRReaderTokenizer',
    ],
}


try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     'DPRContextEncoderTokenizerFast',
     'DPRQuestionEncoderTokenizerFast',
     'DPRReaderTokenizerFast',
 ]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     'DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'DPRContextEncoder',
     'DPRPretrainedContextEncoder',
     'DPRPreTrainedModel',
     'DPRPretrainedQuestionEncoder',
     'DPRPretrainedReader',
     'DPRQuestionEncoder',
     'DPRReader',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     'TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFDPRContextEncoder',
     'TFDPRPretrainedContextEncoder',
     'TFDPRPretrainedQuestionEncoder',
     'TFDPRPretrainedReader',
     'TFDPRQuestionEncoder',
     'TFDPRReader',
 ]


if TYPE_CHECKING:
 from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
 from .tokenization_dpr import (
     DPRContextEncoderTokenizer,
     DPRQuestionEncoderTokenizer,
     DPRReaderOutput,
     DPRReaderTokenizer,
 )

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_dpr_fast import (
      DPRContextEncoderTokenizerFast,
      DPRQuestionEncoderTokenizerFast,
      DPRReaderTokenizerFast,
  )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_dpr import (
      DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPRContextEncoder,
      DPRPretrainedContextEncoder,
      DPRPreTrainedModel,
      DPRPretrainedQuestionEncoder,
      DPRPretrainedReader,
      DPRQuestionEncoder,
      DPRReader,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_dpr import (
      TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFDPRContextEncoder,
      TFDPRPretrainedContextEncoder,
      TFDPRPretrainedQuestionEncoder,
      TFDPRPretrainedReader,
      TFDPRQuestionEncoder,
      TFDPRReader,
  )

else:
 import sys

 a    =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










from __future__ import annotations

from collections.abc import Iterator
from typing import Any
class        __snake_case:



 def __init__(	self   :   Union[str, Any] ,		UpperCAmelCase__   :   Any	):

    """simple docstring"""






    lowercase__						:	Any         = data
    lowercase__						:	Node | None         = None







 def __str__(	self   :   Dict	):

    """simple docstring"""






    return f'''{self.data}'''
class        __snake_case:



 def __init__(	self   :   Optional[Any]	):

    """simple docstring"""






    lowercase__						:	Node | None         = None
    lowercase__						:	Node | None         = None



 def __iter__(	self   :   Any	):

    """simple docstring"""






    lowercase__						:	Any         = self.front
    while node:
       yield node.data
       lowercase__						:	List[str]         = node.next



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

    """simple docstring"""






    return len(tuple(iter(self	)	)	)



 def __str__(	self   :   Optional[Any]	):

    """simple docstring"""






    return " <- ".join(str(UpperCAmelCase__	) for item in self	)



 def 						UpperCAmelCase    (	self   :   List[str]	):

    """simple docstring"""






    return len(self	) == 0



 def 						UpperCAmelCase    (	self   :   Optional[int] ,		UpperCAmelCase__   :   Any	):

    """simple docstring"""






    lowercase__						:	List[str]         = Node(UpperCAmelCase__	)
    if self.is_empty():
       lowercase__						:	List[Any]         = node
    else:
       assert isinstance(self.rear ,		UpperCAmelCase__	)
       lowercase__						:	Any         = node
       lowercase__						:	Union[str, Any]         = node



 def 						UpperCAmelCase    (	self   :   List[Any]	):

    """simple docstring"""






    if self.is_empty():
       raise IndexError("""dequeue from empty queue"""	)
    assert isinstance(self.front ,		UpperCAmelCase__	)
    lowercase__						:	Tuple         = self.front
    lowercase__						:	Any         = self.front.next
    if self.front is None:
       lowercase__						:	List[Any]         = None
    return node.data







 def 						UpperCAmelCase    (	self   :   Optional[Any]	):

    """simple docstring"""






    lowercase__						:	List[Any]         = None


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

 testmod()


