from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class   _lowercase:



   """simple docstring"""





   def __init__(							self:    str			,a:    Any	):
    __UpperCAmelCase         =					data
    __UpperCAmelCase         =					None





   def __str__(							self:    Union[str, Any]	):
    return f"""{self.data}"""




class   _lowercase:



   """simple docstring"""





   def __init__(							self:    Optional[int]	):
    __UpperCAmelCase         =					None
    __UpperCAmelCase         =					None





   def __iter__(							self:    str	):
    __UpperCAmelCase         =					self.front
    while node:
     yield node.data
     __UpperCAmelCase         =					node.next





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





   def __str__(							self:    Union[str, Any]	):
    return " <- ".join(str(a	) for item in self	)





   def 			snake_case	(							self:    List[str]	):
    return len(self	) == 0





   def 			snake_case	(							self:    Union[str, Any]			,a:    Any	):
    __UpperCAmelCase         =					Node(a	)
    if self.is_empty():
     __UpperCAmelCase         =					node
    else:
     assert isinstance(self.rear			,a	)
     __UpperCAmelCase         =					node
     __UpperCAmelCase         =					node





   def 			snake_case	(							self:    Dict	):






    if self.is_empty():
     raise IndexError('dequeue from empty queue'	)
    assert isinstance(self.front			,a	)
    __UpperCAmelCase         =					self.front
    __UpperCAmelCase         =					self.front.next
    if self.front is None:
     __UpperCAmelCase         =					None
    return node.data





   def 			snake_case	(							self:    str	):
    __UpperCAmelCase         =					None


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

     testmod()




'''simple docstring'''




from typing import TYPE_CHECKING

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


_UpperCamelCase				:		Dict       			=		{
    'configuration_marian': ['MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarianConfig', 'MarianOnnxConfig'],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Optional[int]       			=		['MarianTokenizer']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Dict       			=		[
         'MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST',
         'MarianForCausalLM',
         'MarianModel',
         'MarianMTModel',
         'MarianPreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Dict       			=		['TFMarianModel', 'TFMarianMTModel', 'TFMarianPreTrainedModel']

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Any       			=		['FlaxMarianModel', 'FlaxMarianMTModel', 'FlaxMarianPreTrainedModel']

if TYPE_CHECKING:
     from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_marian import MarianTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_marian import (
              MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
              MarianForCausalLM,
              MarianModel,
              MarianMTModel,
              MarianPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
     import sys

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



