



"""simple docstring"""







from typing import TYPE_CHECKING

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


lowercase__		:    Optional[int]				   =     {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__		:    Any				   =     [
         "FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST",
         "FocalNetForImageClassification",
         "FocalNetForMaskedImageModeling",
         "FocalNetBackbone",
         "FocalNetModel",
         "FocalNetPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_focalnet import (
              FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              FocalNetBackbone,
              FocalNetForImageClassification,
              FocalNetForMaskedImageModeling,
              FocalNetModel,
              FocalNetPreTrainedModel,
          )

else:
     import sys

     lowercase__		:    str				   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""







import logging

from transformers.configuration_utils import PretrainedConfig


lowercase__		:    List[Any]				   =     logging.getLogger(__name__)







class 				UpperCamelCase__       (     lowercase_  ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE      =					"""masked_bert"""



      def __init__(				self    :				Any   ,      SCREAMING_SNAKE_CASE_    :				Union[str, Any]=3_0_5_2_2   ,      SCREAMING_SNAKE_CASE_    :				int=7_6_8   ,      SCREAMING_SNAKE_CASE_    :				Tuple=1_2   ,      SCREAMING_SNAKE_CASE_    :				List[Any]=1_2   ,      SCREAMING_SNAKE_CASE_    :				Tuple=3_0_7_2   ,      SCREAMING_SNAKE_CASE_    :				List[str]="gelu"   ,      SCREAMING_SNAKE_CASE_    :				Tuple=0.1   ,      SCREAMING_SNAKE_CASE_    :				List[Any]=0.1   ,      SCREAMING_SNAKE_CASE_    :				List[Any]=5_1_2   ,      SCREAMING_SNAKE_CASE_    :				Optional[Any]=2   ,      SCREAMING_SNAKE_CASE_    :				Dict=0.02   ,      SCREAMING_SNAKE_CASE_    :				Any=1E-12   ,      SCREAMING_SNAKE_CASE_    :				List[str]=0   ,      SCREAMING_SNAKE_CASE_    :				Optional[int]="topK"   ,      SCREAMING_SNAKE_CASE_    :				Optional[int]="constant"   ,      SCREAMING_SNAKE_CASE_    :				Union[str, Any]=0.0   ,      **SCREAMING_SNAKE_CASE_    :				Any   ,      ):
        super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_   ,      **SCREAMING_SNAKE_CASE_	)

        lowerCAmelCase_       :    List[Any]								=			vocab_size
        lowerCAmelCase_       :    str								=			hidden_size
        lowerCAmelCase_       :    Optional[int]								=			num_hidden_layers
        lowerCAmelCase_       :    Dict								=			num_attention_heads
        lowerCAmelCase_       :    List[str]								=			hidden_act
        lowerCAmelCase_       :    List[Any]								=			intermediate_size
        lowerCAmelCase_       :    Any								=			hidden_dropout_prob
        lowerCAmelCase_       :    str								=			attention_probs_dropout_prob
        lowerCAmelCase_       :    Any								=			max_position_embeddings
        lowerCAmelCase_       :    Dict								=			type_vocab_size
        lowerCAmelCase_       :    Tuple								=			initializer_range
        lowerCAmelCase_       :    List[Any]								=			layer_norm_eps
        lowerCAmelCase_       :    str								=			pruning_method
        lowerCAmelCase_       :    Optional[Any]								=			mask_init
        lowerCAmelCase_       :    int								=			mask_scale





