






'''simple docstring'''

import logging

from transformers.configuration_utils import PretrainedConfig


SCREAMING_SNAKE_CASE__											=     logging.getLogger(__name__)






class        a_		(    lowerCamelCase       ):
  lowercase  	=   """masked_bert"""

  def __init__(   self    ,	_SCREAMING_SNAKE_CASE=30522    ,	_SCREAMING_SNAKE_CASE=768    ,	_SCREAMING_SNAKE_CASE=12    ,	_SCREAMING_SNAKE_CASE=12    ,	_SCREAMING_SNAKE_CASE=3072    ,	_SCREAMING_SNAKE_CASE="gelu"    ,	_SCREAMING_SNAKE_CASE=0.1    ,	_SCREAMING_SNAKE_CASE=0.1    ,	_SCREAMING_SNAKE_CASE=512    ,	_SCREAMING_SNAKE_CASE=2    ,	_SCREAMING_SNAKE_CASE=0.0_2    ,	_SCREAMING_SNAKE_CASE=1e-12    ,	_SCREAMING_SNAKE_CASE=0    ,	_SCREAMING_SNAKE_CASE="topK"    ,	_SCREAMING_SNAKE_CASE="constant"    ,	_SCREAMING_SNAKE_CASE=0.0    ,	**_SCREAMING_SNAKE_CASE    ,	)						->   Tuple:



        """simple docstring"""






        super().__init__(pad_token_id=lowercase_    ,	**lowercase_   )

        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       						=      type_vocab_size
        UpperCamelCase       						=      initializer_range
        UpperCamelCase       						=      layer_norm_eps
        UpperCamelCase       						=      pruning_method
        UpperCamelCase       						=      mask_init
        UpperCamelCase       						=      mask_scale












'''simple docstring'''

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__											=     {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__											=     [
         'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'SwiftFormerForImageClassification',
         'SwiftFormerModel',
         'SwiftFormerPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_swiftformer import (
         SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SwiftFormerConfig,
         SwiftFormerOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swiftformer import (
              SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwiftFormerForImageClassification,
              SwiftFormerModel,
              SwiftFormerPreTrainedModel,
          )

else:
     import sys

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