



'''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   _A       (   _lowerCAmelCase=None  ,   _lowerCAmelCase=None					):



							"""simple docstring"""



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





@dataclass
class _UpperCamelCase		:





				'''simple docstring'''





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



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



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



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



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





class _UpperCamelCase		:





				'''simple docstring'''





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







											'''simple docstring'''

											__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 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											__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   _A       (   ):



							"""simple docstring"""



							__lowercase       	=HfArgumentParser(_lowerCAmelCase					)
							__lowercase       	=parser.parse_args_into_dataclasses()[0]
							__lowercase       	=Plot(args=_lowerCAmelCase					)
							plot.plot()


if __name__ == "__main__":
		main()








'''simple docstring'''



from functools import lru_cache



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=2
							__lowercase       	=set()
							while i * i <= n:
														if n % i:
																					i += 1
														else:
																					n //= i
																					factors.add(_lowerCAmelCase					)
							if n > 1:
														factors.add(_lowerCAmelCase					)
							return factors



@lru_cache
def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							return len(unique_prime_factors(_lowerCAmelCase					)					)



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							return len(set(_lowerCAmelCase					)					) in (0, 1)



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=2

							while True:
														# Increment each value of a generated range
														__lowercase       	=[base + i for i in range(_lowerCAmelCase					)]

														# Run elements through out unique_prime_factors function
														# Append our target number to the end.
														__lowercase       	=[upf_len(_lowerCAmelCase					) for x in group]
														checker.append(_lowerCAmelCase					)

														# If all numbers in the list are equal, return the group variable.
														if equality(_lowerCAmelCase					):
																					return group

														# Increment our base variable by 1
														base += 1



def   _A       (   _lowerCAmelCase = 4					):



							"""simple docstring"""



							__lowercase       	=run(_lowerCAmelCase					)
							return results[0] if len(_lowerCAmelCase					) else None


if __name__ == "__main__":
		print(solution())



