



from typing import TYPE_CHECKING

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


__lowerCamelCase         =			{
    "configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
    "convert_funnel_original_tf_checkpoint_to_pytorch": [],
    "tokenization_funnel": ["FunnelTokenizer"],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase         =			["FunnelTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase         =			[
       "FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
       "FunnelBaseModel",
       "FunnelForMaskedLM",
       "FunnelForMultipleChoice",
       "FunnelForPreTraining",
       "FunnelForQuestionAnswering",
       "FunnelForSequenceClassification",
       "FunnelForTokenClassification",
       "FunnelModel",
       "FunnelPreTrainedModel",
       "load_tf_weights_in_funnel",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase         =			[
       "TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TFFunnelBaseModel",
       "TFFunnelForMaskedLM",
       "TFFunnelForMultipleChoice",
       "TFFunnelForPreTraining",
       "TFFunnelForQuestionAnswering",
       "TFFunnelForSequenceClassification",
       "TFFunnelForTokenClassification",
       "TFFunnelModel",
       "TFFunnelPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
   from .tokenization_funnel import FunnelTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_funnel_fast import FunnelTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_funnel import (
          FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
          FunnelBaseModel,
          FunnelForMaskedLM,
          FunnelForMultipleChoice,
          FunnelForPreTraining,
          FunnelForQuestionAnswering,
          FunnelForSequenceClassification,
          FunnelForTokenClassification,
          FunnelModel,
          FunnelPreTrainedModel,
          load_tf_weights_in_funnel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_funnel import (
          TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFFunnelBaseModel,
          TFFunnelForMaskedLM,
          TFFunnelForMultipleChoice,
          TFFunnelForPreTraining,
          TFFunnelForQuestionAnswering,
          TFFunnelForSequenceClassification,
          TFFunnelForTokenClassification,
          TFFunnelModel,
          TFFunnelPreTrainedModel,
      )

else:
   import sys

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











import logging

from transformers import PretrainedConfig


__lowerCamelCase         =			logging.getLogger(__name__)


__lowerCamelCase         =			{
    '''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}


class   snake_case_ (lowercase__  ):




       """simple docstring"""






       _lowerCamelCase			    =				"""bertabs"""



       def __init__(     self     ,lowercase=30522     ,lowercase=512     ,lowercase=6     ,lowercase=512     ,lowercase=8     ,lowercase=512     ,lowercase=0.2     ,lowercase=6     ,lowercase=768     ,lowercase=8     ,lowercase=2048     ,lowercase=0.2     ,**lowercase     ,):

             """simple docstring"""





             super().__init__(**lowercase)

             UpperCAmelCase_  :	Any				      =		vocab_size
             UpperCAmelCase_  :	int				      =		max_pos

             UpperCAmelCase_  :	List[str]				      =		enc_layers
             UpperCAmelCase_  :	List[str]				      =		enc_hidden_size
             UpperCAmelCase_  :	Any				      =		enc_heads
             UpperCAmelCase_  :	Any				      =		enc_ff_size
             UpperCAmelCase_  :	Optional[int]				      =		enc_dropout

             UpperCAmelCase_  :	List[str]				      =		dec_layers
             UpperCAmelCase_  :	List[Any]				      =		dec_hidden_size
             UpperCAmelCase_  :	List[str]				      =		dec_heads
             UpperCAmelCase_  :	List[Any]				      =		dec_ff_size
             UpperCAmelCase_  :	List[str]				      =		dec_dropout
