



'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_	 =						logging.get_logger(__name__)

lowercase_	 =						{
    """facebook/data2vec-vision-base-ft""": (
        """https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"""
    ),
}






class __A    (						A		):



 '''simple docstring'''







 __lowerCamelCase					: List[Any]    = "data2vec-vision"



 def __init__(self				,     A=768				,     A=12				,     A=12				,     A=3_072				,     A="gelu"				,     A=0.0				,     A=0.0				,     A=0.02				,     A=1E-12				,     A=224				,     A=16				,     A=3				,     A=False				,     A=False				,     A=False				,     A=False				,     A=0.1				,     A=0.1				,     A=True				,     A=[3, 5, 7, 11]				,     A=[1, 2, 3, 6]				,     A=True				,     A=0.4				,     A=256				,     A=1				,     A=False				,     A=255				,     **A				,     )					->  Any:


      """simple docstring"""



      super().__init__(**A )

      _a											=						hidden_size
      _a											=						num_hidden_layers
      _a											=						num_attention_heads
      _a											=						intermediate_size
      _a											=						hidden_act
      _a											=						hidden_dropout_prob
      _a											=						attention_probs_dropout_prob
      _a											=						initializer_range
      _a											=						layer_norm_eps

      _a											=						image_size
      _a											=						patch_size
      _a											=						num_channels
      _a											=						use_mask_token
      _a											=						use_absolute_position_embeddings
      _a											=						use_relative_position_bias
      _a											=						use_shared_relative_position_bias
      _a											=						layer_scale_init_value
      _a											=						drop_path_rate
      _a											=						use_mean_pooling
      # decode head attributes (semantic segmentation)
      _a											=						out_indices
      _a											=						pool_scales
      # auxiliary head attributes (semantic segmentation)
      _a											=						use_auxiliary_head
      _a											=						auxiliary_loss_weight
      _a											=						auxiliary_channels
      _a											=						auxiliary_num_convs
      _a											=						auxiliary_concat_input
      _a											=						semantic_loss_ignore_index






class __A    (						A		):



 '''simple docstring'''







 __lowerCamelCase					: Optional[int]    = version.parse('1.11'		)



 @property
 def       a__						(self )					->  Mapping[str, Mapping[int, str]]:


      """simple docstring"""



      return OrderedDict(
          [
              ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
          ] )



 @property
 def       a__						(self )					->  float:


      """simple docstring"""



      return 1E-4










'''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



