



'''simple docstring'''





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


__a          =		logging.get_logger(__name__)

__a          =		{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		"swinv2"

    lowercase					=		{
        "num_attention_heads": "num_heads",
        "num_hidden_layers": "num_layers",
    }




    def __init__(    self					:     Any ,     snake_case_					:     int=224 ,     snake_case_					:     List[Any]=4 ,     snake_case_					:     List[Any]=3 ,     snake_case_					:     Optional[Any]=96 ,     snake_case_					:     str=[2, 2, 6, 2] ,     snake_case_					:     Tuple=[3, 6, 12, 24] ,     snake_case_					:     Optional[Any]=7 ,     snake_case_					:     List[str]=4.0 ,     snake_case_					:     Optional[int]=True ,     snake_case_					:     Any=0.0 ,     snake_case_					:     Tuple=0.0 ,     snake_case_					:     Union[str, Any]=0.1 ,     snake_case_					:     Any="gelu" ,     snake_case_					:     Optional[Any]=False ,     snake_case_					:     List[str]=0.02 ,     snake_case_					:     Dict=1E-5 ,     snake_case_					:     Optional[int]=32 ,     **snake_case_					:     Dict ,     ):
          super().__init__(**snake_case_						)

          snake_case__  :    Optional[int]    						=      image_size
          snake_case__  :    Union[str, Any]    						=      patch_size
          snake_case__  :    Optional[int]    						=      num_channels
          snake_case__  :    str    						=      embed_dim
          snake_case__  :    List[str]    						=      depths
          snake_case__  :    int    						=      len(snake_case_						)
          snake_case__  :    Union[str, Any]    						=      num_heads
          snake_case__  :    Tuple    						=      window_size
          snake_case__  :    str    						=      mlp_ratio
          snake_case__  :    Optional[Any]    						=      qkv_bias
          snake_case__  :    Union[str, Any]    						=      hidden_dropout_prob
          snake_case__  :    Dict    						=      attention_probs_dropout_prob
          snake_case__  :    Optional[Any]    						=      drop_path_rate
          snake_case__  :    Tuple    						=      hidden_act
          snake_case__  :    str    						=      use_absolute_embeddings
          snake_case__  :    List[str]    						=      layer_norm_eps
          snake_case__  :    Optional[int]    						=      initializer_range
          snake_case__  :    Dict    						=      encoder_stride
          # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          snake_case__  :    List[str]    						=      int(embed_dim * 2 ** (len(snake_case_						) - 1)						)
          snake_case__  :    Tuple    						=      (0, 0, 0, 0)


def   lowerCAmelCase_						(					_snake_case      :  str      ,   _snake_case      :  str   )				->		bool:







	'''simple docstring'''


	__magic_name__		:		Union[str, Any]	   =     len(_snake_case   ) + 1
	__magic_name__		:		List[str]	   =     len(_snake_case   ) + 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.
	__magic_name__		:		str	   =     [[0 for i in range(_snake_case   )] for j in range(_snake_case   )]

	# since string of zero length match pattern of zero length
	__magic_name__		:		Optional[int]	   =     1

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

	# since string of zero length will match with pattern where there
	# is at least one * alternatively
	for j in range(1      ,   _snake_case   ):
		__magic_name__		:		Union[str, 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      ,   _snake_case   ):
		for j in range(1      ,   _snake_case   ):
			if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
				__magic_name__		:		Optional[int]	   =     dp[i - 1][j - 1]

			elif pattern[j - 1] == "*":
				if dp[i][j - 2] == 1:
					__magic_name__		:		Optional[Any]	   =     1
				elif pattern[j - 2] in (input_string[i - 1], "."):
					__magic_name__		:		List[Any]	   =     dp[i - 1][j]
				else:
					__magic_name__		:		Union[str, Any]	   =     0
			else:
				__magic_name__		:		Dict	   =     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 :		Optional[Any]							      =  "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}")
