






'''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


__A    	=   logging.get_logger(__name__)

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




class a_    (    UpperCamelCase_							):
   _snake_case        =							"""data2vec-vision"""







   def __init__(self					,   __a=7_6_8					,   __a=1_2					,   __a=1_2					,   __a=3_0_7_2					,   __a="gelu"					,   __a=0.0					,   __a=0.0					,   __a=0.02					,   __a=1E-12					,   __a=2_2_4					,   __a=1_6					,   __a=3					,   __a=False					,   __a=False					,   __a=False					,   __a=False					,   __a=0.1					,   __a=0.1					,   __a=True					,   __a=[3, 5, 7, 1_1]					,   __a=[1, 2, 3, 6]					,   __a=True					,   __a=0.4					,   __a=2_5_6					,   __a=1					,   __a=False					,   __a=2_5_5					,   **__a					,   )			->      Dict:
      """simple docstring"""






      super().__init__(**__a)

      __snake_case				:      Dict     							= hidden_size
      __snake_case				:      List[str]     							= num_hidden_layers
      __snake_case				:      Dict     							= num_attention_heads
      __snake_case				:      Union[str, Any]     							= intermediate_size
      __snake_case				:      Union[str, Any]     							= hidden_act
      __snake_case				:      Any     							= hidden_dropout_prob
      __snake_case				:      Tuple     							= attention_probs_dropout_prob
      __snake_case				:      str     							= initializer_range
      __snake_case				:      Optional[int]     							= layer_norm_eps

      __snake_case				:      List[str]     							= image_size
      __snake_case				:      Tuple     							= patch_size
      __snake_case				:      str     							= num_channels
      __snake_case				:      Tuple     							= use_mask_token
      __snake_case				:      int     							= use_absolute_position_embeddings
      __snake_case				:      Dict     							= use_relative_position_bias
      __snake_case				:      int     							= use_shared_relative_position_bias
      __snake_case				:      Optional[Any]     							= layer_scale_init_value
      __snake_case				:      int     							= drop_path_rate
      __snake_case				:      Union[str, Any]     							= use_mean_pooling
      # decode head attributes (semantic segmentation)
      __snake_case				:      int     							= out_indices
      __snake_case				:      Union[str, Any]     							= pool_scales
      # auxiliary head attributes (semantic segmentation)
      __snake_case				:      Union[str, Any]     							= use_auxiliary_head
      __snake_case				:      int     							= auxiliary_loss_weight
      __snake_case				:      Tuple     							= auxiliary_channels
      __snake_case				:      Union[str, Any]     							= auxiliary_num_convs
      __snake_case				:      Optional[int]     							= auxiliary_concat_input
      __snake_case				:      Tuple     							= semantic_loss_ignore_index




class a_    (    UpperCamelCase_							):
   _snake_case        =							version.parse("""1.11"""							)







   @property
   def     SCREAMING_SNAKE_CASE__					(self)			->      Mapping[str, Mapping[int, str]]:
      """simple docstring"""






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







   @property
   def     SCREAMING_SNAKE_CASE__					(self)			->      float:
      """simple docstring"""






      return 1E-4







'''simple docstring'''






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


__A    	=   logging.get_logger(__name__)

__A    	=   {
    '''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}




class a_    (    UpperCamelCase_							):
   _snake_case        =							"""vit_msn"""







   def __init__(self					,   __a=7_6_8					,   __a=1_2					,   __a=1_2					,   __a=3_0_7_2					,   __a="gelu"					,   __a=0.0					,   __a=0.0					,   __a=0.02					,   __a=1E-06					,   __a=2_2_4					,   __a=1_6					,   __a=3					,   __a=True					,   **__a					,   )			->      Any:
      """simple docstring"""






      super().__init__(**__a)

      __snake_case				:      List[str]     							= hidden_size
      __snake_case				:      Optional[int]     							= num_hidden_layers
      __snake_case				:      Optional[Any]     							= num_attention_heads
      __snake_case				:      str     							= intermediate_size
      __snake_case				:      List[str]     							= hidden_act
      __snake_case				:      List[Any]     							= hidden_dropout_prob
      __snake_case				:      Tuple     							= attention_probs_dropout_prob
      __snake_case				:      List[str]     							= initializer_range
      __snake_case				:      Optional[int]     							= layer_norm_eps
      __snake_case				:      Dict     							= image_size
      __snake_case				:      int     							= patch_size
      __snake_case				:      Dict     							= num_channels
      __snake_case				:      Tuple     							= qkv_bias