
"""simple docstring"""
import math
class      lowerCAmelCase_						:



							'''simple docstring'''





							def __init__(				self  ,							snake_case_  ,							snake_case_  ,							snake_case_  ,							snake_case_							)   ->       Dict:
													__lowerCAmelCase        =       x
													__lowerCAmelCase        =       y
													__lowerCAmelCase        =       step_size
													__lowerCAmelCase        =       function_to_optimize




							def  A__		(				self							)   ->       Optional[int]:
													return self.function(self.x  ,							self.y							)




							def  A__		(				self							)   ->       str:
													__lowerCAmelCase        =       self.step_size
													return [
													    SearchProblem(snake_case_  ,							snake_case_  ,							snake_case_  ,							self.function							)
													    for x, y in (
													        (self.x - step_size, self.y - step_size),
													        (self.x - step_size, self.y),
													        (self.x - step_size, self.y + step_size),
													        (self.x, self.y - step_size),
													        (self.x, self.y + step_size),
													        (self.x + step_size, self.y - step_size),
													        (self.x + step_size, self.y),
													        (self.x + step_size, self.y + step_size),
													    )
													]




							def __hash__(				self							)   ->       Any:
													return hash(str(self							)							)




							def __eq__(				self  ,							snake_case_							)   ->       str:






													if isinstance(snake_case_  ,							snake_case_							):
																			return hash(str(self							)							) == hash(str(snake_case_							)							)
													return False




							def __str__(				self							)   ->       int:
													return f"""x: {self.x} y: {self.y}"""




def 				lowercase      (_lowerCAmelCase				,  _lowerCAmelCase = True				,  _lowerCAmelCase = math.inf				,  _lowerCAmelCase = -math.inf				,  _lowerCAmelCase = math.inf				,  _lowerCAmelCase = -math.inf				,  _lowerCAmelCase = False				,  _lowerCAmelCase = 1_0000				,  ):
						__lowerCAmelCase        =       search_prob
						__lowerCAmelCase        =       []  # list to store the current score at each iteration
						__lowerCAmelCase        =       0
						__lowerCAmelCase        =       False
						__lowerCAmelCase        =       set()
						while not solution_found and iterations < max_iter:
												visited.add(_UpperCamelCase		)
												iterations += 1
												__lowerCAmelCase        =       current_state.score()
												scores.append(_UpperCamelCase		)
												__lowerCAmelCase        =       current_state.get_neighbors()
												__lowerCAmelCase        =       -math.inf
												__lowerCAmelCase        =       math.inf
												__lowerCAmelCase        =       None  # to hold the next best neighbor
												for neighbor in neighbors:
																		if neighbor in visited:
																								continue  # do not want to visit the same state again
																		if (
																		    neighbor.x > max_x
																		    or neighbor.x < min_x
																		    or neighbor.y > max_y
																		    or neighbor.y < min_y
																		):
																								continue  # neighbor outside our bounds
																		__lowerCAmelCase        =       neighbor.score() - current_score
																		if find_max:  # finding max
																								# going to direction with greatest ascent
																								if change > max_change and change > 0:
																														__lowerCAmelCase        =       change
																														__lowerCAmelCase        =       neighbor
																		else:  # finding min
																								# to direction with greatest descent
																								if change < min_change and change < 0:
																														__lowerCAmelCase        =       change
																														__lowerCAmelCase        =       neighbor
												if next_state is not None:
																		# we found at least one neighbor which improved the current state
																		__lowerCAmelCase        =       next_state
												else:
																		# since we have no neighbor that improves the solution we stop the search
																		__lowerCAmelCase        =       True

						if visualization:
												from matplotlib import pyplot as plt

												plt.plot(range(_UpperCamelCase		)				,  _UpperCamelCase		)
												plt.xlabel("""Iterations"""		)
												plt.ylabel("""Function values"""		)
												plt.show()

						return current_state


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			def 				lowercase      (_lowerCAmelCase				,  _lowerCAmelCase		):
									return (x**2) + (y**2)

			# starting the problem with initial coordinates (3, 4)
			SCREAMING_SNAKE_CASE_			      =					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
			SCREAMING_SNAKE_CASE_			      =					hill_climbing(prob, find_max=False)
			print(
			    '''The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: '''
			    F"{local_min.score()}"
			)

			# starting the problem with initial coordinates (12, 47)
			SCREAMING_SNAKE_CASE_			      =					SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
			SCREAMING_SNAKE_CASE_			      =					hill_climbing(
			    prob, find_max=False, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
			)
			print(
			    '''The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 '''
			    F"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
			)

			def 				lowercase      (_lowerCAmelCase				,  _lowerCAmelCase		):
									return (3 * x**2) - (6 * y)

			SCREAMING_SNAKE_CASE_			      =					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
			SCREAMING_SNAKE_CASE_			      =					hill_climbing(prob, find_max=True)



			print(
			    '''The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: '''
			    F"{local_min.score()}"
			)


"""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 				lowercase      (_lowerCAmelCase=None				,  _lowerCAmelCase=None		):
						return field(default_factory=lambda: default				,  metadata=_lowerCAmelCase		)
@dataclass
class      lowerCAmelCase_						:



							'''simple docstring'''





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

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

def 				lowercase      (_lowerCAmelCase		):
						try:
												float(_lowerCAmelCase		)
												return True
						except ValueError:
												return False
class      lowerCAmelCase_						:



							'''simple docstring'''





							def __init__(				self  ,							snake_case_							)   ->       List[Any]:
													__lowerCAmelCase        =       args
													__lowerCAmelCase        =       defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}							)

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




							def  A__		(				self							)   ->       List[Any]:
													__lowerCAmelCase ,      __lowerCAmelCase        =       plt.subplots()
													__lowerCAmelCase        =       """Time usage""" if self.args.is_time else """Memory usage"""
													__lowerCAmelCase        =       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        =       sorted(set(self.result_dict[model_name]["""bsz"""]							)							)
																			__lowerCAmelCase        =       sorted(set(self.result_dict[model_name]["""seq_len"""]							)							)
																			__lowerCAmelCase        =       self.result_dict[model_name]["""result"""]

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

																			__lowerCAmelCase        =       (
																			    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        =       np.asarray(
																															    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]  ,							dtype=snake_case_  ,							)
																									else:
																															__lowerCAmelCase        =       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))        =       (
																									    ("""batch_size""", """len""") if self.args.plot_along_batch else ("""in #tokens""", """bsz""")
																									)

																									__lowerCAmelCase        =       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."""

													__lowerCAmelCase        =       title_str[:-4]
													__lowerCAmelCase        =       """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 				lowercase      ():
						__lowerCAmelCase        =       HfArgumentParser(_lowerCAmelCase		)
						__lowerCAmelCase        =       parser.parse_args_into_dataclasses()[0]
						__lowerCAmelCase        =       Plot(args=_lowerCAmelCase		)
						plot.plot()


if __name__ == "__main__":
			main()
