




'''simple docstring'''







from ... import PretrainedConfig


A									={
    'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}


class     _a						(			__lowerCamelCase				):
       __a       :  Dict            =      NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
       __a       :  Dict            =      'nezha'
       def __init__(			self		:			Dict     ,       lowercase		:			Any=21_128     ,       lowercase		:			Optional[int]=768     ,       lowercase		:			Optional[int]=12     ,       lowercase		:			List[str]=12     ,       lowercase		:			Optional[int]=3_072     ,       lowercase		:			Optional[int]="gelu"     ,       lowercase		:			Optional[Any]=0.1     ,       lowercase		:			str=0.1     ,       lowercase		:			Union[str, Any]=512     ,       lowercase		:			Any=64     ,       lowercase		:			Dict=2     ,       lowercase		:			int=0.02     ,       lowercase		:			Optional[Any]=1E-12     ,       lowercase		:			Tuple=0.1     ,       lowercase		:			Any=0     ,       lowercase		:			str=2     ,       lowercase		:			Optional[int]=3     ,       lowercase		:			str=True     ,       **lowercase		:			Any     ,       ):



           '''simple docstring'''

           super().__init__(pad_token_id=UpperCamelCase_     ,       bos_token_id=UpperCamelCase_     ,       eos_token_id=UpperCamelCase_     ,       **UpperCamelCase_       )

           UpperCAmelCase     =	vocab_size
           UpperCAmelCase     =	hidden_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     =	max_relative_position
           UpperCAmelCase     =	type_vocab_size
           UpperCAmelCase     =	initializer_range
           UpperCAmelCase     =	layer_norm_eps
           UpperCAmelCase     =	classifier_dropout
           UpperCAmelCase     =	use_cache







'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A									={
    'configuration_table_transformer': [
        'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TableTransformerConfig',
        'TableTransformerOnnxConfig',
    ]
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A									=[
       'TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TableTransformerForObjectDetection',
       'TableTransformerModel',
       'TableTransformerPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_table_transformer import (
       TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       TableTransformerConfig,
       TableTransformerOnnxConfig,
   )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_table_transformer import (
          TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          TableTransformerForObjectDetection,
          TableTransformerModel,
          TableTransformerPreTrainedModel,
      )

else:
   import sys

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




