Source code for macop.callbacks.MultiCheckpoint

"""Multi Checkpoint class implementation
"""

# main imports
import os
import logging
import numpy as np

# module imports
from .Callback import Callback
from ..utils.color import macop_text, macop_line


[docs]class MultiCheckpoint(Callback): """ MultiCheckpoint is used for loading previous computations and start again after loading checkpoint Attributes: algo: {Algorithm} -- main algorithm instance reference every: {int} -- checkpoint frequency used (based on number of evaluations) filepath: {str} -- file path where checkpoints will be saved """
[docs] def run(self): """ Check if necessary to do backup based on `every` variable """ # get current population population = self.algo.population currentEvaluation = self.algo.getGlobalEvaluation() # backup if necessary if currentEvaluation % self.every == 0: logging.info("Checkpoint is done into " + self.filepath) with open(self.filepath, 'w') as f: for solution in population: solutionData = "" solutionSize = len(solution.data) for index, val in enumerate(solution.data): solutionData += str(val) if index < solutionSize - 1: solutionData += ' ' line = str(currentEvaluation) + ';' for i in range(len(self.algo.evaluator)): line += str(solution.scores[i]) + ';' line += solutionData + ';\n' f.write(line)
[docs] def load(self): """ Load backup lines as population and set algorithm state (population and pareto front) at this backup """ if os.path.exists(self.filepath): logging.info('Load best solution from last checkpoint') with open(self.filepath) as f: # read data for each line for i, line in enumerate(f.readlines()): data = line.replace(';\n', '').split(';') # only the first time if i == 0: # get evaluation information globalEvaluation = int(data[0]) if self.algo.parent is not None: self.algo.parent.numberOfEvaluations = globalEvaluation else: self.algo.numberOfEvaluations = globalEvaluation nObjectives = len(self.algo.evaluator) scores = [float(s) for s in data[1:nObjectives + 1]] # get best solution data information solutionData = list(map(int, data[-1].split(' '))) self.algo.population[i].data = np.array(solutionData) self.algo.population[i].scores = scores self.algo.pfPop[i] = self.algo.population[i] print(macop_line()) print( macop_text('Load of available population from `{}`'.format( self.filepath))) print( macop_text('Restart algorithm from evaluation {}.'.format( self.algo.numberOfEvaluations))) else: print( macop_text( 'No backup found... Start running algorithm from evaluation 0.' )) logging.info( "Can't load backup... Backup filepath not valid in Checkpoint") print(macop_line())