



'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_	 =						{
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_	 =						[
      'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
      'Swinv2ForImageClassification',
      'Swinv2ForMaskedImageModeling',
      'Swinv2Model',
      'Swinv2PreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_swinva import (
        SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwinvaForImageClassification,
        SwinvaForMaskedImageModeling,
        SwinvaModel,
        SwinvaPreTrainedModel,
    )


else:
  import sys

  lowercase_	 =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










'''simple docstring'''





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


lowercase_	 =						logging.get_logger(__name__)

# TODO: upload to AWS
lowercase_	 =						{
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}






class __A    (						A		):



 '''simple docstring'''







 __lowerCamelCase					: Optional[Any]    = 'retribert'



 def __init__(self				,     A=30_522				,     A=768				,     A=8				,     A=12				,     A=3_072				,     A="gelu"				,     A=0.1				,     A=0.1				,     A=512				,     A=2				,     A=0.02				,     A=1E-12				,     A=True				,     A=128				,     A=0				,     **A				,     )					->  Any:


      """simple docstring"""



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

      _a											=						vocab_size
      _a											=						hidden_size
      _a											=						num_hidden_layers
      _a											=						num_attention_heads
      _a											=						hidden_act
      _a											=						intermediate_size
      _a											=						hidden_dropout_prob
      _a											=						attention_probs_dropout_prob
      _a											=						max_position_embeddings
      _a											=						type_vocab_size
      _a											=						initializer_range
      _a											=						layer_norm_eps
      _a											=						share_encoders
      _a											=						projection_dim



