

"""simple docstring"""


def    a__   (   __SCREAMING_SNAKE_CASE			)     ->     Optional[int]:




		if a < 0:
				raise ValueError("Input value must be a positive integer"			)
		elif isinstance(_a ,			_a			):
				raise TypeError("Input value must be a 'int' type"			)
		return bin(_a			).count("1"			)


if __name__ == "__main__":
			import doctest

			doctest.testmod()





"""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    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Union[str, Any]       				=  """data2vec-vision"""

				def __init__(     self							:    Optional[int]					,  UpperCamelCase__							:    str=7_6_8					,  UpperCamelCase__							:    Any=1_2					,  UpperCamelCase__							:    str=1_2					,  UpperCamelCase__							:    Optional[Any]=3_0_7_2					,  UpperCamelCase__							:    Union[str, Any]="gelu"					,  UpperCamelCase__							:    List[Any]=0.0					,  UpperCamelCase__							:    Dict=0.0					,  UpperCamelCase__							:    Union[str, Any]=0.02					,  UpperCamelCase__							:    str=1e-12					,  UpperCamelCase__							:    Dict=2_2_4					,  UpperCamelCase__							:    List[Any]=1_6					,  UpperCamelCase__							:    Optional[Any]=3					,  UpperCamelCase__							:    List[str]=False					,  UpperCamelCase__							:    List[Any]=False					,  UpperCamelCase__							:    str=False					,  UpperCamelCase__							:    List[str]=False					,  UpperCamelCase__							:    int=0.1					,  UpperCamelCase__							:    List[Any]=0.1					,  UpperCamelCase__							:    Optional[Any]=True					,  UpperCamelCase__							:    List[Any]=[3, 5, 7, 1_1]					,  UpperCamelCase__							:    List[str]=[1, 2, 3, 6]					,  UpperCamelCase__							:    Union[str, Any]=True					,  UpperCamelCase__							:    Any=0.4					,  UpperCamelCase__							:    Union[str, Any]=2_5_6					,  UpperCamelCase__							:    List[Any]=1					,  UpperCamelCase__							:    str=False					,  UpperCamelCase__							:    Optional[int]=2_5_5					,  **UpperCamelCase__							:    Dict					,  )->       List[str]:



						'''simple docstring'''


						super().__init__(**UpperCamelCase__)

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

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





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Dict       				=  version.parse("""1.11"""  )

				@property
				def 							lowercase_					(     self							:    Optional[Any])->       Mapping[str, Mapping[int, str]]:



						'''simple docstring'''


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




				@property
				def 							lowercase_					(     self							:    Any)->       float:



						'''simple docstring'''


						return 1e-4


