






"""simple docstring"""



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 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Optional[Any]=None		,					__snake_case			:  Tuple=None    ):





  '''simple docstring'''





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

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


def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Optional[int]    ):





  '''simple docstring'''





  try:
    int(__snake_case    )
    return True
  except ValueError:
    return False
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Tuple    ):





  '''simple docstring'''





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

class        a     :







    def __init__(			self							,		_lowerCamelCase       ):
      lowercase							    =       args
      lowercase							    =       defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}       )

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







    def 			UpperCamelCase_      (			self       ):
      lowercase    ,     lowercase							    =       plt.subplots()
      lowercase							    =       'Time usage' if self.args.is_time else 'Memory usage'
      lowercase							    =       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()       ):
        lowercase							    =       sorted(set(self.result_dict[model_name]['bsz']       )       )
        lowercase							    =       sorted(set(self.result_dict[model_name]['seq_len']       )       )
        lowercase							    =       self.result_dict[model_name]['result']

        ((lowercase)    ,     (lowercase))							    =       (
            (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
        )

        lowercase							    =       (
            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:
            lowercase							    =       np.asarray(
                [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]							,		dtype=_lowerCamelCase							,		)
          else:
            lowercase							    =       np.asarray(
                [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]							,		dtype=np.floataa							,		)

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

          lowercase							    =       np.asarray(_lowerCamelCase							,		_lowerCamelCase       )[: len(_lowerCamelCase       )]
          plt.scatter(
              _lowerCamelCase							,		_lowerCamelCase							,		label=F'{label_model_name} - {inner_loop_label}: {inner_loop_value}'       )
          plt.plot(_lowerCamelCase							,		_lowerCamelCase							,		'--'       )

        title_str += F' {label_model_name} vs.'

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

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

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


def 						_SCREAMING_SNAKE_CASE (    ):





  '''simple docstring'''





  lowercase							    =       HfArgumentParser(__snake_case    )
  lowercase							    =       parser.parse_args_into_dataclasses()[0]
  lowercase							    =       Plot(args=__snake_case    )
  plot.plot()


if __name__ == "__main__":
    main()










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  List[str]		,					__snake_case			:  List[str]    ):





  '''simple docstring'''





  lowercase							    =       ''
  for i in table:
    res += inp[i - 1]
  return res
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  str    ):





  '''simple docstring'''





  return data[1:] + data[0]
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  List[str]		,					__snake_case			:  Optional[int]    ):





  '''simple docstring'''





  lowercase							    =       ''
  for i in range(len(__snake_case    )    ):
    if a[i] == b[i]:
      res += "0"
    else:
      res += "1"
  return res
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Dict		,					__snake_case			:  Optional[Any]    ):





  '''simple docstring'''





  lowercase							    =       int('0b' + data[0] + data[-1]		,					2    )
  lowercase							    =       int('0b' + data[1:3]		,					2    )
  return bin(s[row][col]    )[2:]
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Union[str, Any]		,					__snake_case			:  Union[str, Any]		,					__snake_case			:  Dict		,					__snake_case			:  Union[str, Any]		,					__snake_case			:  Optional[int]    ):





  '''simple docstring'''





  lowercase							    =       message[:4]
  lowercase							    =       message[4:]
  lowercase							    =       apply_table(__snake_case		,					__snake_case    )
  lowercase							    =       xor(__snake_case		,					__snake_case    )
  lowercase							    =       apply_sbox(__snake_case		,					temp[:4]    )  # noqa: E741
  lowercase							    =       apply_sbox(__snake_case		,					temp[4:]    )
  lowercase							    =       '0' * (2 - len(__snake_case    )) + l  # noqa: E741
  lowercase							    =       '0' * (2 - len(__snake_case    )) + r
  lowercase							    =       apply_table(l + r		,					__snake_case    )
  lowercase							    =       xor(__snake_case		,					__snake_case    )
  return temp + right


if __name__ == "__main__":
    _UpperCamelCase		:  Dict						=		input('Enter 10 bit key: ')
    _UpperCamelCase		:  int						=		input('Enter 8 bit message: ')

    _UpperCamelCase		:  Optional[int]						=		[6, 3, 7, 4, 8, 5, 1_0, 9]
    _UpperCamelCase		:  Optional[Any]						=		[3, 5, 2, 7, 4, 1_0, 1, 9, 8, 6]
    _UpperCamelCase		:  str						=		[2, 4, 3, 1]
    _UpperCamelCase		:  List[Any]						=		[2, 6, 3, 1, 4, 8, 5, 7]
    _UpperCamelCase		:  List[str]						=		[4, 1, 3, 5, 7, 2, 8, 6]
    _UpperCamelCase		:  int						=		[4, 1, 2, 3, 2, 3, 4, 1]
    _UpperCamelCase		:  Optional[Any]						=		[[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
    _UpperCamelCase		:  Optional[int]						=		[[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

    # key generation
    _UpperCamelCase		:  str						=		apply_table(key, paa_table)
    _UpperCamelCase		:  Union[str, Any]						=		temp[:5]
    _UpperCamelCase		:  Dict						=		temp[5:]
    _UpperCamelCase		:  List[Any]						=		left_shift(left)
    _UpperCamelCase		:  str						=		left_shift(right)
    _UpperCamelCase		:  int						=		apply_table(left + right, pa_table)
    _UpperCamelCase		:  Optional[int]						=		left_shift(left)
    _UpperCamelCase		:  Any						=		left_shift(right)
    _UpperCamelCase		:  str						=		left_shift(left)
    _UpperCamelCase		:  Tuple						=		left_shift(right)
    _UpperCamelCase		:  Union[str, Any]						=		apply_table(left + right, pa_table)

    # encryption
    _UpperCamelCase		:  Tuple						=		apply_table(message, IP)
    _UpperCamelCase		:  Any						=		function(expansion, sa, sa, keya, temp)
    _UpperCamelCase		:  List[Any]						=		temp[4:] + temp[:4]
    _UpperCamelCase		:  List[str]						=		function(expansion, sa, sa, keya, temp)
    _UpperCamelCase		:  int						=		apply_table(temp, IP_inv)
    print('Cipher text is:', CT)

    # decryption
    _UpperCamelCase		:  List[Any]						=		apply_table(CT, IP)
    _UpperCamelCase		:  Optional[Any]						=		function(expansion, sa, sa, keya, temp)
    _UpperCamelCase		:  int						=		temp[4:] + temp[:4]
    _UpperCamelCase		:  str						=		function(expansion, sa, sa, keya, temp)
    _UpperCamelCase		:  List[Any]						=		apply_table(temp, IP_inv)
    print('Plain text after decypting is:', PT)


