




'''simple docstring'''


from __future__ import annotations
def 		snake_case_   (UpperCamelCase	:  str			,						UpperCamelCase	:  list[str] | None = None			,						UpperCamelCase	:  dict[str, float] | None = None			,						UpperCamelCase	:  bool = False			,						):





							'''simple docstring'''


							_a     					=    cipher_alphabet or [chr(UpperCamelCase				) for i in range(97			,						123				)]

							# If the argument is None or the user provided an empty dictionary
							if not frequencies_dict:
														# Frequencies of letters in the english language (how much they show up)
														_a     					=    {
														    '''a''': 0.08497,
														    '''b''': 0.01492,
														    '''c''': 0.02202,
														    '''d''': 0.04253,
														    '''e''': 0.11162,
														    '''f''': 0.02228,
														    '''g''': 0.02015,
														    '''h''': 0.06094,
														    '''i''': 0.07546,
														    '''j''': 0.00153,
														    '''k''': 0.01292,
														    '''l''': 0.04025,
														    '''m''': 0.02406,
														    '''n''': 0.06749,
														    '''o''': 0.07507,
														    '''p''': 0.01929,
														    '''q''': 0.00095,
														    '''r''': 0.07587,
														    '''s''': 0.06327,
														    '''t''': 0.09356,
														    '''u''': 0.02758,
														    '''v''': 0.00978,
														    '''w''': 0.02560,
														    '''x''': 0.00150,
														    '''y''': 0.01994,
														    '''z''': 0.00077,
														}
							else:
														# Custom frequencies dictionary
														_a     					=    frequencies_dict

							if not case_sensitive:
														_a     					=    ciphertext.lower()

							# Chi squared statistic values
							_a     					=    {}

							# cycle through all of the shifts
							for shift in range(len(UpperCamelCase				)				):
														_a     					=    ''''''

														# decrypt the message with the shift
														for letter in ciphertext:
																					try:
																												# Try to index the letter in the alphabet
																												_a     					=    (alphabet_letters.index(letter.lower()				) - shift) % len(
																												    UpperCamelCase				)
																												decrypted_with_shift += (
																												    alphabet_letters[new_key].upper()
																												    if case_sensitive and letter.isupper()
																												    else alphabet_letters[new_key]
																												)
																					except ValueError:
																												# Append the character if it isn't in the alphabet
																												decrypted_with_shift += letter

														_a     					=    0.0

														# Loop through each letter in the decoded message with the shift
														for letter in decrypted_with_shift:
																					if case_sensitive:
																												_a     					=    letter.lower()
																												if letter in frequencies:
																																			# Get the amount of times the letter occurs in the message
																																			_a     					=    decrypted_with_shift.lower().count(UpperCamelCase				)

																																			# Get the excepcted amount of times the letter should appear based
																																			# on letter frequencies
																																			_a     					=    frequencies[letter] * occurrences

																																			# Complete the chi squared statistic formula
																																			_a     					=    ((occurrences - expected) ** 2) / expected

																																			# Add the margin of error to the total chi squared statistic
																																			chi_squared_statistic += chi_letter_value
																					else:
																												if letter.lower() in frequencies:
																																			# Get the amount of times the letter occurs in the message
																																			_a     					=    decrypted_with_shift.count(UpperCamelCase				)

																																			# Get the excepcted amount of times the letter should appear based
																																			# on letter frequencies
																																			_a     					=    frequencies[letter] * occurrences

																																			# Complete the chi squared statistic formula
																																			_a     					=    ((occurrences - expected) ** 2) / expected

																																			# Add the margin of error to the total chi squared statistic
																																			chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
														_a     					=    (
														    chi_squared_statistic,
														    decrypted_with_shift,
														)

							# Get the most likely cipher by finding the cipher with the smallest chi squared
							# statistic
							def chi_squared_statistic_values_sorting_key(UpperCamelCase	:  int				) -> tuple[float, str]:
														return chi_squared_statistic_values[key]

							_a     					=    min(
							    UpperCamelCase			,						key=UpperCamelCase			,						)

							# Get all the data from the most likely cipher (key, decoded message)
							(
							    (
							    _a
							)					,							(
							    _a
							)					,							
							)     					=    chi_squared_statistic_values[most_likely_cipher]

							# Return the data on the most likely shift
							return (
							    most_likely_cipher,
							    most_likely_cipher_chi_squared_value,
							    decoded_most_likely_cipher,
							)







'''simple docstring'''


from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available

@dataclass
class       A   (		_a   ):
							lowercase_          =    42
							lowercase_          =    42


if is_transformers_available() and is_torch_available():
				from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline

