


import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser






def 	lowerCamelCase_       (			_a=None      ,  _a=None			):




		"""simple docstring"""






		return field(default_factory=lambda: default      ,  metadata=_a			)





@dataclass
class    _a				:
	_a    :    str        =				field(
	    metadata={'''help''': '''The csv file to plot.'''}	,		)
	_a    :    bool        =				field(
	    default=_lowercase	,		metadata={'''help''': '''Whether to plot along batch size or sequence length. Defaults to sequence length.'''}	,		)
	_a    :    bool        =				field(
	    default=_lowercase	,		metadata={'''help''': '''Whether the csv file has time results or memory results. Defaults to memory results.'''}	,		)
	_a    :    bool        =				field(
	    default=_lowercase	,		metadata={'''help''': '''Disable logarithmic scale when plotting'''}	,		)
	_a    :    bool        =				field(
	    default=_lowercase	,		metadata={
	        '''help''': '''Whether the csv file has training results or inference results. Defaults to inference results.'''
	    }	,		)
	_a    :    Optional[str]        =				field(
	    default=_lowercase	,		metadata={'''help''': '''Filename under which the plot will be saved. If unused no plot is saved.'''}	,		)
	_a    :    Optional[List[str]]        =				list_field(
	    default=_lowercase	,		metadata={'''help''': '''List of model names that are used instead of the ones in the csv file.'''})






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		try:
				int(_a			)
				return True
		except ValueError:
				return False






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		try:
				float(_a			)
				return True
		except ValueError:
				return False





class    _a				:




	def __init__(   self		:						Dict						,   _SCREAMING_SNAKE_CASE		:						Tuple						)->			Any:
			lowerCAmelCase__  :     int       	=   args
			lowerCAmelCase__  :     Optional[Any]       	=   defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}						)

			with open(self.args.csv_file						,   newline=''''''						) as csv_file:
					lowerCAmelCase__  :     Any       	=   csv.DictReader(_SCREAMING_SNAKE_CASE						)
					for row in reader:
							lowerCAmelCase__  :     Optional[int]       	=   row['''model''']
							self.result_dict[model_name]["bsz"].append(int(row['''batch_size''']						)						)
							self.result_dict[model_name]["seq_len"].append(int(row['''sequence_length''']						)						)
							if can_convert_to_int(row['''result''']						):
									# value is not None
									lowerCAmelCase__  :     List[Any]       	=   int(row['''result''']						)
							elif can_convert_to_float(row['''result''']						):
									# value is not None
									lowerCAmelCase__  :     Any       	=   float(row['''result''']						)




	def 				UpperCAmelCase__(   self		:						int						)->			int:
			lowerCAmelCase__	,      lowerCAmelCase__  :     List[Any]       	=   plt.subplots()
			lowerCAmelCase__  :     List[Any]       	=   '''Time usage''' if self.args.is_time else '''Memory usage'''
			lowerCAmelCase__  :     Optional[Any]       	=   title_str + ''' for training''' if self.args.is_train else title_str + ''' for inference'''

			if not self.args.no_log_scale:
					# set logarithm scales
					ax.set_xscale('''log'''						)
					ax.set_yscale('''log'''						)

			for axis in [ax.xaxis, ax.yaxis]:
					axis.set_major_formatter(ScalarFormatter()						)

			for model_name_idx, model_name in enumerate(self.result_dict.keys()						):
					lowerCAmelCase__  :     Dict       	=   sorted(set(self.result_dict[model_name]['''bsz''']						)						)
					lowerCAmelCase__  :     Optional[int]       	=   sorted(set(self.result_dict[model_name]['''seq_len''']						)						)
					lowerCAmelCase__  :     Union[str, Any]       	=   self.result_dict[model_name]['''result''']

					((lowerCAmelCase__)	,      (lowerCAmelCase__))  :     str       	=   (
					    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
					)

					lowerCAmelCase__  :     List[Any]       	=   (
					    model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
					)

					for inner_loop_value in inner_loop_array:
							if self.args.plot_along_batch:
									lowerCAmelCase__  :     Dict       	=   np.asarray(
									    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]						,   dtype=_SCREAMING_SNAKE_CASE						,   )
							else:
									lowerCAmelCase__  :     Any       	=   np.asarray(
									    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]						,   dtype=np.floataa						,   )

							((lowerCAmelCase__)	,      (lowerCAmelCase__))  :     Any       	=   (
							    ('''batch_size''', '''len''') if self.args.plot_along_batch else ('''in #tokens''', '''bsz''')
							)

							lowerCAmelCase__  :     List[str]       	=   np.asarray(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						)[: len(_SCREAMING_SNAKE_CASE						)]
							plt.scatter(
							    _SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						,   label=F'{label_model_name} - {inner_loop_label}: {inner_loop_value}'						)
							plt.plot(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						,   '''--'''						)

					title_str += F' {label_model_name} vs.'

			lowerCAmelCase__  :     int       	=   title_str[:-4]
			lowerCAmelCase__  :     Optional[int]       	=   '''Time in s''' if self.args.is_time else '''Memory in MB'''

			# plot
			plt.title(_SCREAMING_SNAKE_CASE						)
			plt.xlabel(_SCREAMING_SNAKE_CASE						)
			plt.ylabel(_SCREAMING_SNAKE_CASE						)
			plt.legend()

			if self.args.figure_png_file is not None:
					plt.savefig(self.args.figure_png_file						)
			else:
					plt.show()






def 	lowerCamelCase_       (			):




		"""simple docstring"""






		lowerCAmelCase__  :     Union[str, Any]       	=   HfArgumentParser(_a			)
		lowerCAmelCase__  :     str       	=   parser.parse_args_into_dataclasses()[0]
		lowerCAmelCase__  :     Optional[int]       	=   Plot(args=_a			)
		plot.plot()


if __name__ == "__main__":
		main()








from __future__ import annotations

from string import ascii_letters






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a = None			):




		"""simple docstring"""






		lowerCAmelCase__  :     List[Any]       	=   alphabet or ascii_letters

		# The final result string
		lowerCAmelCase__  :     Optional[Any]       	=   ''''''

		for character in input_string:
				if character not in alpha:
						# Append without encryption if character is not in the alphabet
						result += character
				else:
						# Get the index of the new key and make sure it isn't too large
						lowerCAmelCase__  :     int       	=   (alpha.index(_a			) + key) % len(_a			)

						# Append the encoded character to the alphabet
						result += alpha[new_key]

		return result






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a = None			):




		"""simple docstring"""






		key *= -1

		return encrypt(_a      ,  _a      ,  _a			)






def 	lowerCamelCase_       (			_a      ,  _a = None			):




		"""simple docstring"""






		lowerCAmelCase__  :     Optional[Any]       	=   alphabet or ascii_letters

		# To store data on all the combinations
		lowerCAmelCase__  :     Optional[int]       	=   {}

		# Cycle through each combination
		for key in range(1      ,  len(_a			) + 1			):
				# Decrypt the message and store the result in the data
				lowerCAmelCase__  :     Optional[int]       	=   decrypt(_a      ,  _a      ,  _a			)

		return brute_force_data


if __name__ == "__main__":
		while True:
				print(f'''\n{"-" * 10}\n Menu\n{"-" * 10}''')
				print(*['''1.Encrypt''', '''2.Decrypt''', '''3.BruteForce''', '''4.Quit'''], sep='''\n''')

				# get user input
				lowerCamelCase		=						input('''\nWhat would you like to do?: ''').strip() or '''4'''

				# run functions based on what the user chose
				if choice not in ("1", "2", "3", "4"):
						print('''Invalid choice, please enter a valid choice''')
				elif choice == "1":
						lowerCamelCase		=						input('''Please enter the string to be encrypted: ''')
						lowerCamelCase		=						int(input('''Please enter off-set: ''').strip())

						print(encrypt(input_string, key))
				elif choice == "2":
						lowerCamelCase		=						input('''Please enter the string to be decrypted: ''')
						lowerCamelCase		=						int(input('''Please enter off-set: ''').strip())

						print(decrypt(input_string, key))
				elif choice == "3":
						lowerCamelCase		=						input('''Please enter the string to be decrypted: ''')
						lowerCamelCase		=						brute_force(input_string)

						for key, value in brute_force_data.items():
								print(f'''Key: {key} | Message: {value}''')

				elif choice == "4":
						print('''Goodbye.''')
						break




