

'''simple docstring'''




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


_a					:			Union[str, Any]							=    logging.get_logger(__name__)

_a					:			Optional[int]							=    {
    'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
    'studio-ousia/luke-large': 'https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json',
}



class 							lowercase_						(		__A			):

  '''simple docstring'''





  __lowerCAmelCase       :			int     	= "luke"
  def __init__(  self ,			a_=5_0_2_6_7 ,			a_=5_0_0_0_0_0 ,			a_=7_6_8 ,			a_=2_5_6 ,			a_=1_2 ,			a_=1_2 ,			a_=3_0_7_2 ,			a_="gelu" ,			a_=0.1 ,			a_=0.1 ,			a_=5_1_2 ,			a_=2 ,			a_=0.02 ,			a_=1E-12 ,			a_=True ,			a_=None ,			a_=1 ,			a_=0 ,			a_=2 ,			**a_ ,			)				->					Tuple:


    """simple docstring"""
    super().__init__(pad_token_id=__A ,			bos_token_id=__A ,			eos_token_id=__A ,			**__A  )

    UpperCAmelCase    				=						vocab_size
    UpperCAmelCase    				=						entity_vocab_size
    UpperCAmelCase    				=						hidden_size
    UpperCAmelCase    				=						entity_emb_size
    UpperCAmelCase    				=						num_hidden_layers
    UpperCAmelCase    				=						num_attention_heads
    UpperCAmelCase    				=						hidden_act
    UpperCAmelCase    				=						intermediate_size
    UpperCAmelCase    				=						hidden_dropout_prob
    UpperCAmelCase    				=						attention_probs_dropout_prob
    UpperCAmelCase    				=						max_position_embeddings
    UpperCAmelCase    				=						type_vocab_size
    UpperCAmelCase    				=						initializer_range
    UpperCAmelCase    				=						layer_norm_eps
    UpperCAmelCase    				=						use_entity_aware_attention
    UpperCAmelCase    				=						classifier_dropout






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE							    =							{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE							    =							[
      'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
      'AutoformerForPrediction',
      'AutoformerModel',
      'AutoformerPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_autoformer import (
      AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      AutoformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_autoformer import (
        AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        AutoformerForPrediction,
        AutoformerModel,
        AutoformerPreTrainedModel,
    )

else:
  import sys

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



