





import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


snake_case_							=			logging.get_logger(__name__)


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     int:
		lowerCamelCase   : Dict								=set()
		lowerCamelCase   : Any								=[]

		def parse_line(SCREAMING_SNAKE_CASE_		):
				for line in fp:
						if isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		):
								lowerCamelCase   : Optional[Any]								=line.decode('''UTF-8'''		)
						if "warnings summary (final)" in line:
								continue
						# This means we are outside the body of a warning
						elif not line.startswith(''' '''		):
								# process a single warning and move it to `selected_warnings`.
								if len(SCREAMING_SNAKE_CASE_		) > 0:
										lowerCamelCase   : Tuple								='''\n'''.join(SCREAMING_SNAKE_CASE_		)
										# Only keep the warnings specified in `targets`
										if any(F": {x}: " in warning for x in targets		):
												selected_warnings.add(SCREAMING_SNAKE_CASE_		)
										buffer.clear()
								continue
						else:
								lowerCamelCase   : Tuple								=line.strip()
								buffer.append(SCREAMING_SNAKE_CASE_		)

		if from_gh:
				for filename in os.listdir(SCREAMING_SNAKE_CASE_		):
						lowerCamelCase   : Dict								=os.path.join(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)
						if not os.path.isdir(SCREAMING_SNAKE_CASE_		):
								# read the file
								if filename != "warnings.txt":
										continue
								with open(SCREAMING_SNAKE_CASE_		) as fp:
										parse_line(SCREAMING_SNAKE_CASE_		)
		else:
				try:
						with zipfile.ZipFile(SCREAMING_SNAKE_CASE_		) as z:
								for filename in z.namelist():
										if not os.path.isdir(SCREAMING_SNAKE_CASE_		):
												# read the file
												if filename != "warnings.txt":
														continue
												with z.open(SCREAMING_SNAKE_CASE_		) as fp:
														parse_line(SCREAMING_SNAKE_CASE_		)
				except Exception:
						logger.warning(
						    F"{artifact_path} is either an invalid zip file or something else wrong. This file is skipped."		)

		return selected_warnings


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Dict:
		lowerCamelCase   : Dict								=set()

		lowerCamelCase   : Optional[Any]								=[os.path.join(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) for p in os.listdir(SCREAMING_SNAKE_CASE_		) if (p.endswith('''.zip'''		) or from_gh)]
		for p in paths:
				selected_warnings.update(extract_warnings_from_single_artifact(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)		)

		return selected_warnings


if __name__ == "__main__":


				def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     Tuple:
						return values.split(''','''		)

				snake_case_							=			argparse.ArgumentParser()
				# Required parameters
				parser.add_argument('''--workflow_run_id''', type=str, required=True, help='''A GitHub Actions workflow run id.''')
				parser.add_argument(
				    '''--output_dir''',
				    type=str,
				    required=True,
				    help='''Where to store the downloaded artifacts and other result files.''',
				)
				parser.add_argument('''--token''', default=None, type=str, help='''A token that has actions:read permission.''')
				# optional parameters
				parser.add_argument(
				    '''--targets''',
				    default='''DeprecationWarning,UserWarning,FutureWarning''',
				    type=list_str,
				    help='''Comma-separated list of target warning(s) which we want to extract.''',
				)
				parser.add_argument(
				    '''--from_gh''',
				    action='''store_true''',
				    help='''If running from a GitHub action workflow and collecting warnings from its artifacts.''',
				)

				snake_case_							=			parser.parse_args()

				snake_case_							=			args.from_gh
				if from_gh:
								# The artifacts have to be downloaded using `actions/download-artifact@v3`
								pass
				else:
								os.makedirs(args.output_dir, exist_ok=True)

								# get download links
								snake_case_							=			get_artifacts_links(args.workflow_run_id, token=args.token)
								with open(os.path.join(args.output_dir, '''artifacts.json'''), '''w''', encoding='''UTF-8''') as fp:
												json.dump(artifacts, fp, ensure_ascii=False, indent=4)

								# download artifacts
								for idx, (name, url) in enumerate(artifacts.items()):
												print(name)
												print(url)
												print('''=''' * 8_0)
												download_artifact(name, url, args.output_dir, args.token)
												# Be gentle to GitHub
												time.sleep(1)

    # extract warnings from artifacts
				snake_case_							=			extract_warnings(args.output_dir, args.targets)
				snake_case_							=			sorted(selected_warnings)
				with open(os.path.join(args.output_dir, '''selected_warnings.json'''), '''w''', encoding='''UTF-8''') as fp:
								json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)








import math
import random
from typing import Any

from .hill_climbing import SearchProblem


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = True							,       SCREAMING_SNAKE_CASE_ = math.inf							,       SCREAMING_SNAKE_CASE_ = -math.inf							,       SCREAMING_SNAKE_CASE_ = math.inf							,       SCREAMING_SNAKE_CASE_ = -math.inf							,       SCREAMING_SNAKE_CASE_ = False							,       SCREAMING_SNAKE_CASE_ = 1_0_0							,       SCREAMING_SNAKE_CASE_ = 0.0_1							,       SCREAMING_SNAKE_CASE_ = 1							,       )   ->     Any:
		lowerCamelCase   : Union[str, Any]								=False
		lowerCamelCase   : int								=search_prob
		lowerCamelCase   : int								=start_temperate
		lowerCamelCase   : Any								=[]
		lowerCamelCase   : Any								=0
		lowerCamelCase   : Union[str, Any]								=None

		while not search_end:
				lowerCamelCase   : Dict								=current_state.score()
				if best_state is None or current_score > best_state.score():
						lowerCamelCase   : Tuple								=current_state
				scores.append(SCREAMING_SNAKE_CASE_		)
				iterations += 1
				lowerCamelCase   : Union[str, Any]								=None
				lowerCamelCase   : int								=current_state.get_neighbors()
				while (
				    next_state is None and neighbors
				):  # till we do not find a neighbor that we can move to
						lowerCamelCase   : Union[str, Any]								=random.randint(0							,       len(SCREAMING_SNAKE_CASE_		) - 1		)  # picking a random neighbor
						lowerCamelCase   : List[str]								=neighbors.pop(SCREAMING_SNAKE_CASE_		)
						lowerCamelCase   : Any								=picked_neighbor.score() - current_score

						if (
						    picked_neighbor.x > max_x
						    or picked_neighbor.x < min_x
						    or picked_neighbor.y > max_y
						    or picked_neighbor.y < min_y
						):
								continue  # neighbor outside our bounds

						if not find_max:
								lowerCamelCase   : Dict								=change * -1  # in case we are finding minimum
						if change > 0:  # improves the solution
								lowerCamelCase   : Optional[int]								=picked_neighbor
						else:
								lowerCamelCase   : Any								=(math.e) ** (
								    change / current_temp
								)  # probability generation function
								if random.random() < probability:  # random number within probability
										lowerCamelCase   : Union[str, Any]								=picked_neighbor
				lowerCamelCase   : Union[str, Any]								=current_temp - (current_temp * rate_of_decrease)

				if current_temp < threshold_temp or next_state is None:
						# temperature below threshold, or could not find a suitable neighbor
						lowerCamelCase   : Optional[int]								=True
				else:
						lowerCamelCase   : List[str]								=next_state

		if visualization:
				from matplotlib import pyplot as plt

				plt.plot(range(SCREAMING_SNAKE_CASE_		)							,       SCREAMING_SNAKE_CASE_		)
				plt.xlabel('''Iterations'''		)
				plt.ylabel('''Function values'''		)
				plt.show()
		return best_state


if __name__ == "__main__":


				def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     List[str]:
						return (x**2) + (y**2)

				# starting the problem with initial coordinates (12, 47)
				snake_case_							=			SearchProblem(x=1_2, y=4_7, step_size=1, function_to_optimize=test_fa)
				snake_case_							=			simulated_annealing(
				    prob, find_max=False, max_x=1_0_0, min_x=5, max_y=5_0, 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()}"""
				)

				# starting the problem with initial coordinates (12, 47)
				snake_case_							=			SearchProblem(x=1_2, y=4_7, step_size=1, function_to_optimize=test_fa)
				snake_case_							=			simulated_annealing(
				    prob, find_max=True, max_x=1_0_0, min_x=5, max_y=5_0, min_y=-5, visualization=True
				)
				print(
				    '''The maximum 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 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Tuple:
						return (3 * x**2) - (6 * y)

				snake_case_							=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
				snake_case_							=			simulated_annealing(prob, find_max=False, visualization=True)
				print(
				    '''The minimum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: '''
				    F"""{local_min.score()}"""
				)

				snake_case_							=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
				snake_case_							=			simulated_annealing(prob, find_max=True, visualization=True)



				print(
				    '''The maximum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: '''
				    F"""{local_min.score()}"""
				)

