






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


__lowerCamelCase      :    int   		=   logging.get_logger(__name__)

__lowerCamelCase      :    List[Any]   		=   {
    '''microsoft/beit-base-patch16-224-pt22k''': (
        '''https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json'''
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}



class 							SCREAMING_SNAKE_CASE__		(       UpperCamelCase_		):





							"""simple docstring"""






							a_			=	"beit"



							def __init__(      self  :						Optional[Any]							,	__A  :						int=8_1_9_2							,	__A  :						str=7_6_8							,	__A  :						Tuple=1_2							,	__A  :						Optional[Any]=1_2							,	__A  :						Dict=3_0_7_2							,	__A  :						Any="gelu"							,	__A  :						List[Any]=0.0							,	__A  :						Dict=0.0							,	__A  :						Tuple=0.0_2							,	__A  :						Optional[Any]=1e-1_2							,	__A  :						List[Any]=2_2_4							,	__A  :						List[str]=1_6							,	__A  :						Optional[int]=3							,	__A  :						List[str]=False							,	__A  :						str=False							,	__A  :						str=False							,	__A  :						Dict=False							,	__A  :						List[Any]=0.1							,	__A  :						str=0.1							,	__A  :						Optional[Any]=True							,	__A  :						int=[3, 5, 7, 1_1]							,	__A  :						Optional[int]=[1, 2, 3, 6]							,	__A  :						Union[str, Any]=True							,	__A  :						Tuple=0.4							,	__A  :						Optional[Any]=2_5_6							,	__A  :						Tuple=1							,	__A  :						Tuple=False							,	__A  :						Tuple=2_5_5							,	**__A  :						Union[str, Any]							,	):
								super().__init__(**UpperCamelCase_ )

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

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



class 							SCREAMING_SNAKE_CASE__		(       UpperCamelCase_		):





							"""simple docstring"""






							a_			=	version.parse("1.11"		)



							@property
							def  _lowercase  (      self  :						List[str] ):
								return OrderedDict(
								    [
								        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
								    ] )






							@property
							def  _lowercase  (      self  :						Optional[int] ):
								return 1e-4











def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	snake_case__				:   Any     =						[0] * len(snake_case_     )

	for i in range(1  ,						len(snake_case_     )     ):
		# use last results for better performance - dynamic programming
		snake_case__				:   Union[str, Any]     =						prefix_result[i - 1]
		while j > 0 and input_string[i] != input_string[j]:
			snake_case__				:   str     =						prefix_result[j - 1]

		if input_string[i] == input_string[j]:
			j += 1
		snake_case__				:   int     =						j

	return prefix_result







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	return max(prefix_function(snake_case_     )     )


if __name__ == "__main__":
	import doctest

	doctest.testmod()



