
from typing import List

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


_UpperCAmelCase      :				str          = logging.get_logger(__name__)

_UpperCAmelCase      :				Optional[Any]          = {
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}


class        lowercase      (	_SCREAMING_SNAKE_CASE     ):
		__lowercase : Optional[int]			  =       "efficientformer"



		def __init__(				self       ,   A_ = [3, 2, 6, 4]       ,   A_ = [48, 96, 224, 448]       ,   A_ = [True, True, True, True]       ,   A_ = 448       ,   A_ = 32       ,   A_ = 4       ,   A_ = 7       ,   A_ = 5       ,   A_ = 8       ,   A_ = 4       ,   A_ = 0.0       ,   A_ = 16       ,   A_ = 3       ,   A_ = 3       ,   A_ = 3       ,   A_ = 2       ,   A_ = 1       ,   A_ = 0.0       ,   A_ = 1       ,   A_ = True       ,   A_ = True       ,   A_ = 1e-5       ,   A_ = "gelu"       ,   A_ = 0.02       ,   A_ = 1e-12       ,   A_ = 224       ,   A_ = 1e-05       ,   **A_       ,   )						->      None:
				"""simple docstring"""
				super().__init__(**A_ )

				UpperCamelCase						=  hidden_act
				UpperCamelCase						=  hidden_dropout_prob
				UpperCamelCase						=  hidden_sizes
				UpperCamelCase						=  num_hidden_layers
				UpperCamelCase						=  num_attention_heads
				UpperCamelCase						=  initializer_range
				UpperCamelCase						=  layer_norm_eps
				UpperCamelCase						=  patch_size
				UpperCamelCase						=  num_channels
				UpperCamelCase						=  depths
				UpperCamelCase						=  mlp_expansion_ratio
				UpperCamelCase						=  downsamples
				UpperCamelCase						=  dim
				UpperCamelCase						=  key_dim
				UpperCamelCase						=  attention_ratio
				UpperCamelCase						=  resolution
				UpperCamelCase						=  pool_size
				UpperCamelCase						=  downsample_patch_size
				UpperCamelCase						=  downsample_stride
				UpperCamelCase						=  downsample_pad
				UpperCamelCase						=  drop_path_rate
				UpperCamelCase						=  num_metaad_blocks
				UpperCamelCase						=  distillation
				UpperCamelCase						=  use_layer_scale
				UpperCamelCase						=  layer_scale_init_value
				UpperCamelCase						=  image_size
				UpperCamelCase						=  batch_norm_eps


from string import ascii_uppercase

_UpperCAmelCase      :				Dict          = {char: i for i, char in enumerate(ascii_uppercase)}
_UpperCAmelCase      :				Tuple          = dict(enumerate(ascii_uppercase))


def    A (      lowercase					, lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  len(lowercase				)
		UpperCamelCase						=  0
		while True:
				if x == i:
						UpperCamelCase						=  0
				if len(lowercase				) == len(lowercase				):
						break
				key += key[i]
				i += 1
		return key


def    A (      lowercase					, lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  ''
		UpperCamelCase						=  0
		for letter in message:
				if letter == " ":
						cipher_text += " "
				else:
						UpperCamelCase						=  (dicta[letter] - dicta[key_new[i]]) % 26
						i += 1
						cipher_text += dicta[x]
		return cipher_text


def    A (      lowercase					, lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  ''
		UpperCamelCase						=  0
		for letter in cipher_text:
				if letter == " ":
						or_txt += " "
				else:
						UpperCamelCase						=  (dicta[letter] + dicta[key_new[i]] + 26) % 26
						i += 1
						or_txt += dicta[x]
		return or_txt


def    A (      )     ->						None:
		'''simple docstring'''

		UpperCamelCase						=  'THE GERMAN ATTACK'
		UpperCamelCase						=  'SECRET'
		UpperCamelCase						=  generate_key(lowercase					, lowercase				)
		UpperCamelCase						=  cipher_text(lowercase					, lowercase				)
		print(f'''Encrypted Text = {s}'''				)
		print(f'''Original Text = {original_text(lowercase					, lowercase				)}'''				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()
