


def     __lowerCamelCase						(			UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		Union[str, Any]						):




      """simple docstring"""





      a						:Optional[int]										=	len(UpperCAmelCase_						) + 1
      a						:Optional[Any]										=	len(UpperCAmelCase_						) + 1

      # dp is a 2d matrix where dp[i][j] denotes whether prefix string of
      # length i of input_string matches with prefix string of length j of
      # given pattern.
      # "dp" stands for dynamic programming.
      a						:int										=	[[0 for i in range(UpperCAmelCase_						)] for j in range(UpperCAmelCase_						)]

      # since string of zero length match pattern of zero length
      a						:Optional[Any]										=	1

      # since pattern of zero length will never match with string of non-zero length
      for i in range(1			,  UpperCAmelCase_						):
            a						:Optional[int]										=	0

      # since string of zero length will match with pattern where there
      # is at least one * alternatively
      for j in range(1			,  UpperCAmelCase_						):
            a						:List[Any]										=	dp[0][j - 2] if pattern[j - 1] == '''*''' else 0

      # now using bottom-up approach to find for all remaining lengths
      for i in range(1			,  UpperCAmelCase_						):
            for j in range(1			,  UpperCAmelCase_						):
                  if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
                        a						:Optional[Any]										=	dp[i - 1][j - 1]

                  elif pattern[j - 1] == "*":
                        if dp[i][j - 2] == 1:
                              a						:Any										=	1
                        elif pattern[j - 2] in (input_string[i - 1], "."):
                              a						:Optional[int]										=	dp[i - 1][j]
                        else:
                              a						:Tuple										=	0
                  else:
                        a						:List[str]										=	0

      return bool(dp[-1][-1]						)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   # inputing the strings
   # input_string = input("input a string :")
   # pattern = input("input a pattern :")

   snake_case    :   Tuple	    =					'''aab'''
   snake_case    :   List[str]	    =					'''c*a*b'''

   # using function to check whether given string matches the given pattern
   if match_pattern(input_string, pattern):
      print(F"""{input_string} matches the given pattern {pattern}""")
   else:
      print(F"""{input_string} does not match with the given pattern {pattern}""")









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


snake_case    :   Optional[Any]	    =					logging.get_logger(__name__)

snake_case    :   Dict	    =					{
    '''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__				=	'data2vec-vision'




 def __init__(		self ,  _lowerCamelCase=768 ,  _lowerCamelCase=12 ,  _lowerCamelCase=12 ,  _lowerCamelCase=3072 ,  _lowerCamelCase="gelu" ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.02 ,  _lowerCamelCase=1e-12 ,  _lowerCamelCase=224 ,  _lowerCamelCase=16 ,  _lowerCamelCase=3 ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=True ,  _lowerCamelCase=[3, 5, 7, 11] ,  _lowerCamelCase=[1, 2, 3, 6] ,  _lowerCamelCase=True ,  _lowerCamelCase=0.4 ,  _lowerCamelCase=256 ,  _lowerCamelCase=1 ,  _lowerCamelCase=False ,  _lowerCamelCase=255 ,  **_lowerCamelCase ,  ):
       super().__init__(**_lowerCamelCase   )

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

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







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	version.parse('1.11'							)




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




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return 1e-4





