





from string import ascii_uppercase


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ,			__a = False ,			__a = ascii_uppercase ):
	snake_case_		:      List[str]           =						keyword.upper()
	snake_case_		:      Tuple           =						plaintext.upper()
	snake_case_		:      List[str]           =						set(__a )

	# create a list of unique characters in the keyword - their order matters
	# it determines how we will map plaintext characters to the ciphertext
	snake_case_		:      List[Any]           =						[]
	for char in keyword:
		if char in alphabet_set and char not in unique_chars:
			unique_chars.append(__a )
    # the number of those unique characters will determine the number of rows
	snake_case_		:      str           =						len(__a )

	# create a shifted version of the alphabet
	snake_case_		:      Tuple           =						unique_chars + [
	    char for char in alphabet if char not in unique_chars
	]

	# create a modified alphabet by splitting the shifted alphabet into rows
	snake_case_		:      Tuple           =						[
	    shifted_alphabet[k : k + num_unique_chars_in_keyword]
	    for k in range(0 ,			26 ,			__a )
	]

	# map the alphabet characters to the modified alphabet characters
	# going 'vertically' through the modified alphabet - consider columns first
	snake_case_		:      List[Any]           =						{}
	snake_case_		:      Dict           =						0
	for column in range(__a ):
		for row in modified_alphabet:
			# if current row (the last one) is too short, break out of loop
			if len(__a ) <= column:
				break

			# map current letter to letter in modified alphabet
			snake_case_		:      Optional[int]           =						row[column]
			letter_index += 1

	if verbose:
		print(__a )
	# create the encrypted text by mapping the plaintext to the modified alphabet
	return "".join(mapping[char] if char in mapping else char for char in plaintext )


if __name__ == "__main__":
						# example use
						print(mixed_keyword("""college""", """UNIVERSITY"""))




"""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


SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    {
    'MBZUAI/swiftformer-xs': 'https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json',
}



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    UpperCAmelCase    			=       "swiftformer"

    def __init__(  self:			Tuple     ,    UpperCamelCase:			int=3     ,    UpperCamelCase:			Union[str, Any]=[3, 3, 6, 4]     ,    UpperCamelCase:			List[str]=[48, 56, 1_12, 2_20]     ,    UpperCamelCase:			List[Any]=4     ,    UpperCamelCase:			List[Any]=[True, True, True, True]     ,    UpperCamelCase:			str="gelu"     ,    UpperCamelCase:			Tuple=3     ,    UpperCamelCase:			Dict=2     ,    UpperCamelCase:			int=1     ,    UpperCamelCase:			List[Any]=0.0     ,    UpperCamelCase:			Any=True     ,    UpperCamelCase:			List[Any]=1e-5     ,    UpperCamelCase:			List[Any]=1e-5     ,    **UpperCamelCase:			Any     ,    ):






         """simple docstring"""


         super().__init__(**UpperCamelCase							)
         A__				      =	num_channels
         A__				      =	depths
         A__				      =	embed_dims
         A__				      =	mlp_ratio
         A__				      =	downsamples
         A__				      =	hidden_act
         A__				      =	down_patch_size
         A__				      =	down_stride
         A__				      =	down_pad
         A__				      =	drop_path_rate
         A__				      =	use_layer_scale
         A__				      =	layer_scale_init_value
         A__				      =	batch_norm_eps



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    UpperCAmelCase    			=       version.parse("1.11"					)

    @property
    def 					UpperCamelCase						(  self:			int							):






         """simple docstring"""


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





    @property
    def 					UpperCamelCase						(  self:			Any							):






         """simple docstring"""


         return 1e-4






