





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 					_a   (__SCREAMING_SNAKE_CASE=None  ,      __SCREAMING_SNAKE_CASE=None   ):


  """simple docstring"""

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







@dataclass
class 		UpperCAmelCase   :


  """simple docstring"""







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




def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

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


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

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







class 		UpperCAmelCase   :


  """simple docstring"""







  def __init__(				self    :					Optional[Any]							,	UpperCamelCase__    :					Optional[int]  )     ->						str:
    _UpperCamelCase       			=args
    _UpperCamelCase       			=defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}  )

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




  def   UpperCamelCase__      (				self    :					str  )     ->						int:
    _UpperCamelCase			,     _UpperCamelCase       			=plt.subplots()
    _UpperCamelCase       			='''Time usage''' if self.args.is_time else '''Memory usage'''
    _UpperCamelCase       			=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()  ):
      _UpperCamelCase       			=sorted(set(self.result_dict[model_name]['''bsz''']  )  )
      _UpperCamelCase       			=sorted(set(self.result_dict[model_name]['''seq_len''']  )  )
      _UpperCamelCase       			=self.result_dict[model_name]['''result''']

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

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

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

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

      title_str += F''' {label_model_name} vs.'''

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

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

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




def 					_a   ():


  """simple docstring"""

  _UpperCamelCase       			=HfArgumentParser(__SCREAMING_SNAKE_CASE   )
  _UpperCamelCase       			=parser.parse_args_into_dataclasses()[0]
  _UpperCamelCase       			=Plot(args=__SCREAMING_SNAKE_CASE   )
  plot.plot()


if __name__ == "__main__":
      main()













'''simple docstring'''






from collections.abc import Generator
from math import sin


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if len(__SCREAMING_SNAKE_CASE   ) != 32:
    raise ValueError('''Input must be of length 32'''   )

  _UpperCamelCase       			=b''''''
  for i in [3, 2, 1, 0]:
    little_endian += string_aa[8 * i : 8 * i + 8]
  return little_endian


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if i < 0:
    raise ValueError('''Input must be non-negative'''   )

  _UpperCamelCase       			=format(__SCREAMING_SNAKE_CASE  ,      '''08x'''   )[-8:]
  _UpperCamelCase       			=b''''''
  for i in [3, 2, 1, 0]:
    little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('''utf-8'''   )
  return little_endian_hex


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _UpperCamelCase       			=b''''''
  for char in message:
    bit_string += format(__SCREAMING_SNAKE_CASE  ,      '''08b'''   ).encode('''utf-8'''   )
  _UpperCamelCase       			=format(len(__SCREAMING_SNAKE_CASE   )  ,      '''064b'''   ).encode('''utf-8'''   )

  # Pad bit_string to a multiple of 512 chars
  bit_string += b"1"
  while len(__SCREAMING_SNAKE_CASE   ) % 512 != 448:
    bit_string += b"0"
  bit_string += to_little_endian(start_len[32:]   ) + to_little_endian(start_len[:32]   )

  return bit_string


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if len(__SCREAMING_SNAKE_CASE   ) % 512 != 0:
    raise ValueError('''Input must have length that\'s a multiple of 512'''   )

  for pos in range(0  ,      len(__SCREAMING_SNAKE_CASE   )  ,      512   ):
    _UpperCamelCase       			=bit_string[pos : pos + 512]
    _UpperCamelCase       			=[]
    for i in range(0  ,      512  ,      32   ):
      block_words.append(int(to_little_endian(block[i : i + 32]   )  ,      2   )   )
    yield block_words


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if i < 0:
    raise ValueError('''Input must be non-negative'''   )

  _UpperCamelCase       			=format(__SCREAMING_SNAKE_CASE  ,      '''032b'''   )
  _UpperCamelCase       			=''''''
  for c in i_str:
    new_str += "1" if c == "0" else "0"
  return int(__SCREAMING_SNAKE_CASE  ,      2   )


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  return (a + b) % 2**32


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if i < 0:
    raise ValueError('''Input must be non-negative'''   )
  if shift < 0:
    raise ValueError('''Shift must be non-negative'''   )
  return ((i << shift) ^ (i >> (32 - shift))) % 2**32


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _UpperCamelCase       			=preprocess(__SCREAMING_SNAKE_CASE   )

  _UpperCamelCase       			=[int(2**32 * abs(sin(i + 1   )   )   ) for i in range(64   )]

  # Starting states
  _UpperCamelCase       			=0X6745_2301
  _UpperCamelCase       			=0Xefcd_ab89
  _UpperCamelCase       			=0X98ba_dcfe
  _UpperCamelCase       			=0X1032_5476

  _UpperCamelCase       			=[
      7,
      12,
      17,
      22,
      7,
      12,
      17,
      22,
      7,
      12,
      17,
      22,
      7,
      12,
      17,
      22,
      5,
      9,
      14,
      20,
      5,
      9,
      14,
      20,
      5,
      9,
      14,
      20,
      5,
      9,
      14,
      20,
      4,
      11,
      16,
      23,
      4,
      11,
      16,
      23,
      4,
      11,
      16,
      23,
      4,
      11,
      16,
      23,
      6,
      10,
      15,
      21,
      6,
      10,
      15,
      21,
      6,
      10,
      15,
      21,
      6,
      10,
      15,
      21,
  ]

  # Process bit string in chunks, each with 16 32-char words
  for block_words in get_block_words(__SCREAMING_SNAKE_CASE   ):
    _UpperCamelCase       			=aa
    _UpperCamelCase       			=ba
    _UpperCamelCase       			=ca
    _UpperCamelCase       			=da

    # Hash current chunk
    for i in range(64   ):
      if i <= 15:
        # f = (b & c) | (not_32(b) & d)     # Alternate definition for f
        _UpperCamelCase       			=d ^ (b & (c ^ d))
        _UpperCamelCase       			=i
      elif i <= 31:
        # f = (d & b) | (not_32(d) & c)     # Alternate definition for f
        _UpperCamelCase       			=c ^ (d & (b ^ c))
        _UpperCamelCase       			=(5 * i + 1) % 16
      elif i <= 47:
        _UpperCamelCase       			=b ^ c ^ d
        _UpperCamelCase       			=(3 * i + 5) % 16
      else:
        _UpperCamelCase       			=c ^ (b | not_aa(__SCREAMING_SNAKE_CASE   ))
        _UpperCamelCase       			=(7 * i) % 16
      _UpperCamelCase       			=(f + a + added_consts[i] + block_words[g]) % 2**32
      _UpperCamelCase       			=d
      _UpperCamelCase       			=c
      _UpperCamelCase       			=b
      _UpperCamelCase       			=sum_aa(__SCREAMING_SNAKE_CASE  ,      left_rotate_aa(__SCREAMING_SNAKE_CASE  ,      shift_amounts[i]   )   )

    # Add hashed chunk to running total
    _UpperCamelCase       			=sum_aa(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
    _UpperCamelCase       			=sum_aa(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
    _UpperCamelCase       			=sum_aa(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
    _UpperCamelCase       			=sum_aa(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )

  _UpperCamelCase       			=reformat_hex(__SCREAMING_SNAKE_CASE   ) + reformat_hex(__SCREAMING_SNAKE_CASE   ) + reformat_hex(__SCREAMING_SNAKE_CASE   ) + reformat_hex(__SCREAMING_SNAKE_CASE   )
  return digest


if __name__ == "__main__":
      import doctest

      doctest.testmod()






