

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase           =					logging.get_logger(__name__)







class 						__magic_name__			(							lowerCamelCase__							):

   '''simple docstring'''




   lowerCamelCase__ :	List[str]    =   'encoder-decoder'
   lowerCamelCase__ :	Any    =   True



   def __init__(				self,    **lowercase_       )							->    List[str]:






     """simple docstring"""






     super().__init__(**lowercase_       )
     assert (
         "encoder" in kwargs and "decoder" in kwargs
     ), "Config has to be initialized with encoder and decoder config"
     a__  =kwargs.pop('''encoder'''       )
     a__  =encoder_config.pop('''model_type'''       )
     a__  =kwargs.pop('''decoder'''       )
     a__  =decoder_config.pop('''model_type'''       )

     from ..auto.configuration_auto import AutoConfig

     a__  =AutoConfig.for_model(lowercase_,    **lowercase_       )
     a__  =AutoConfig.for_model(lowercase_,    **lowercase_       )
     a__  =True



   @classmethod
   def  _UpperCAmelCase (				cls,    lowercase_,    lowercase_,    **lowercase_       )							->    PretrainedConfig:






     """simple docstring"""






     logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''       )
     a__  =True
     a__  =True

     return cls(encoder=encoder_config.to_dict(),    decoder=decoder_config.to_dict(),    **lowercase_       )



   def  _UpperCAmelCase (				self       )							->    int:






     """simple docstring"""






     a__  =copy.deepcopy(self.__dict__       )
     a__  =self.encoder.to_dict()
     a__  =self.decoder.to_dict()
     a__  =self.__class__.model_type
     return output



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase           =					{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase           =					[
           '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''CanineForMultipleChoice''',
           '''CanineForQuestionAnswering''',
           '''CanineForSequenceClassification''',
           '''CanineForTokenClassification''',
           '''CanineLayer''',
           '''CanineModel''',
           '''CaninePreTrainedModel''',
           '''load_tf_weights_in_canine''',
       ]


if TYPE_CHECKING:
       from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
       from .tokenization_canine import CanineTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_canine import (
                  CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  CanineForMultipleChoice,
                  CanineForQuestionAnswering,
                  CanineForSequenceClassification,
                  CanineForTokenClassification,
                  CanineLayer,
                  CanineModel,
                  CaninePreTrainedModel,
                  load_tf_weights_in_canine,
              )


else:
       import sys

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