
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			(					lowerCamelCase_:  Union[str, Any]=None				,	lowerCamelCase_:  int=None		):



				'''simple docstring'''







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

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





def 							_lowerCamelCase			(					lowerCamelCase_:  Optional[Any]		):



				'''simple docstring'''







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





def 							_lowerCamelCase			(					lowerCamelCase_:  Union[str, Any]		):



				'''simple docstring'''







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

class     _SCREAMING_SNAKE_CASE							:





				def __init__(		self :		Dict					,      snake_case_ :		str							):


								"""simple docstring"""

								A     :  Union[str, Any]   =				args
								A     :  Union[str, Any]   =				defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}							)

								with open(self.args.csv_file					,      newline=''''''							) as csv_file:
												A     :  int   =				csv.DictReader(snake_case_							)
												for row in reader:
																A     :  Dict   =				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
																				A     :  Any   =				int(row['''result''']							)
																elif can_convert_to_float(row['''result''']							):
																				# value is not None
																				A     :  int   =				float(row['''result''']							)






				def        _UpperCAmelCase						(		self :		Optional[int]							):


								"""simple docstring"""

								A ,       A     :  Any   =				plt.subplots()
								A     :  List[str]   =				'''Time usage''' if self.args.is_time else '''Memory usage'''
								A     :  List[str]   =				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()							):
												A     :  List[Any]   =				sorted(set(self.result_dict[model_name]['''bsz''']							)							)
												A     :  Any   =				sorted(set(self.result_dict[model_name]['''seq_len''']							)							)
												A     :  Any   =				self.result_dict[model_name]['''result''']

												((A) ,       (A))     :  Dict   =				(
												    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
												)

												A     :  List[str]   =				(
												    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:
																				A     :  Optional[int]   =				np.asarray(
																				    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]					,      dtype=snake_case_					,      )
																else:
																				A     :  Union[str, Any]   =				np.asarray(
																				    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]					,      dtype=np.floataa					,      )

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

																A     :  Any   =				np.asarray(snake_case_					,      snake_case_							)[: len(snake_case_							)]
																plt.scatter(
																    snake_case_					,      snake_case_					,      label=f"""{label_model_name} - {inner_loop_label}: {inner_loop_value}"""							)
																plt.plot(snake_case_					,      snake_case_					,      '''--'''							)

												title_str += f""" {label_model_name} vs."""

								A     :  List[Any]   =				title_str[:-4]
								A     :  List[str]   =				'''Time in s''' if self.args.is_time else '''Memory in MB'''

								# plot
								plt.title(snake_case_							)
								plt.xlabel(snake_case_							)
								plt.ylabel(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'''







				A     :  List[Any]   =				HfArgumentParser(lowerCamelCase_		)
				A     :  List[Any]   =				parser.parse_args_into_dataclasses()[0]
				A     :  List[Any]   =				Plot(args=lowerCamelCase_		)
				plot.plot()


if __name__ == "__main__":
					main()

from __future__ import annotations





def 							_lowerCamelCase			(					lowerCamelCase_:  str				,	lowerCamelCase_:  dict[str, str]		):



				'''simple docstring'''







				A ,       A ,       A     :  str   =				'''''', '''''', ''''''
				A     :  Union[str, Any]   =				[]

				for character in message_part:
								tmp.append(character_to_number[character]		)

				for each in tmp:
								one += each[0]
								two += each[1]
								three += each[2]

				return one + two + three





def 							_lowerCamelCase			(					lowerCamelCase_:  str				,	lowerCamelCase_:  dict[str, str]		):



				'''simple docstring'''







				A ,       A     :  Tuple   =				'''''', ''''''
				A     :  str   =				[]

				for character in message_part:
								this_part += character_to_number[character]

				for digit in this_part:
								tmp += digit
								if len(lowerCamelCase_		) == len(lowerCamelCase_		):
												result.append(lowerCamelCase_		)
												A     :  Dict   =				''''''

				return result[0], result[1], result[2]





def 							_lowerCamelCase			(					lowerCamelCase_:  str				,	lowerCamelCase_:  str		):



				'''simple docstring'''







				A     :  Dict   =				alphabet.replace(''' '''				,	''''''		).upper()
				A     :  List[str]   =				message.replace(''' '''				,	''''''		).upper()

				# Check length and characters
				if len(lowerCamelCase_		) != 27:
								raise KeyError('''Length of alphabet has to be 27.'''		)
				for each in message:
								if each not in alphabet:
												raise ValueError('''Each message character has to be included in alphabet!'''		)

    # Generate dictionares
				A     :  str   =				(
				    '''111''',
				    '''112''',
				    '''113''',
				    '''121''',
				    '''122''',
				    '''123''',
				    '''131''',
				    '''132''',
				    '''133''',
				    '''211''',
				    '''212''',
				    '''213''',
				    '''221''',
				    '''222''',
				    '''223''',
				    '''231''',
				    '''232''',
				    '''233''',
				    '''311''',
				    '''312''',
				    '''313''',
				    '''321''',
				    '''322''',
				    '''323''',
				    '''331''',
				    '''332''',
				    '''333''',
				)
				A     :  Union[str, Any]   =				{}
				A     :  int   =				{}
				for letter, number in zip(lowerCamelCase_				,	lowerCamelCase_		):
								A     :  Optional[Any]   =				number
								A     :  Union[str, Any]   =				letter

				return message, alphabet, character_to_number, number_to_character





def 							_lowerCamelCase			(					lowerCamelCase_:  str				,	lowerCamelCase_:  str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."				,	lowerCamelCase_:  int = 5		):



				'''simple docstring'''







				A ,       A ,       A ,       A     :  Optional[int]   =				__prepare(
				    lowerCamelCase_				,	lowerCamelCase_		)
				A ,       A     :  int   =				'''''', ''''''

				for i in range(0				,	len(lowerCamelCase_		) + 1				,	lowerCamelCase_		):
								encrypted_numeric += __encrypt_part(
								    message[i : i + period]				,	lowerCamelCase_		)

				for i in range(0				,	len(lowerCamelCase_		)				,	3		):
								encrypted += number_to_character[encrypted_numeric[i : i + 3]]

				return encrypted





def 							_lowerCamelCase			(					lowerCamelCase_:  str				,	lowerCamelCase_:  str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."				,	lowerCamelCase_:  int = 5		):



				'''simple docstring'''







				A ,       A ,       A ,       A     :  Optional[int]   =				__prepare(
				    lowerCamelCase_				,	lowerCamelCase_		)
				A     :  Tuple   =				[]
				A     :  Optional[Any]   =				''''''

				for i in range(0				,	len(lowerCamelCase_		) + 1				,	lowerCamelCase_		):
								A ,       A ,       A     :  List[Any]   =				__decrypt_part(message[i : i + period]				,	lowerCamelCase_		)

								for j in range(0				,	len(lowerCamelCase_		)		):
												decrypted_numeric.append(a[j] + b[j] + c[j]		)

				for each in decrypted_numeric:
								decrypted += number_to_character[each]

				return decrypted


if __name__ == "__main__":
					UpperCamelCase_  =	"DEFEND THE EAST WALL OF THE CASTLE."
					UpperCamelCase_  =	encrypt_message(msg, "EPSDUCVWYM.ZLKXNBTFGORIJHAQ")
					UpperCamelCase_  =	decrypt_message(encrypted, "EPSDUCVWYM.ZLKXNBTFGORIJHAQ")
					print(F'''Encrypted: {encrypted}\nDecrypted: {decrypted}''')