classicals.py 3.2 KB

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  1. """Classical Checkpoints classes implementations
  2. """
  3. # main imports
  4. import os
  5. import logging
  6. import numpy as np
  7. # module imports
  8. from .base import Callback
  9. from ..utils.progress import macop_text, macop_line
  10. class BasicCheckpoint(Callback):
  11. """
  12. BasicCheckpoint is used for loading previous computations and start again after loading checkpoint
  13. Attributes:
  14. algo: {Algorithm} -- main algorithm instance reference
  15. every: {int} -- checkpoint frequency used (based on number of evaluations)
  16. filepath: {str} -- file path where checkpoints will be saved
  17. """
  18. def run(self):
  19. """
  20. Check if necessary to do backup based on `every` variable
  21. """
  22. # get current best solution
  23. solution = self._algo._bestSolution
  24. currentEvaluation = self._algo.getGlobalEvaluation()
  25. # backup if necessary
  26. if currentEvaluation % self._every == 0:
  27. logging.info("Checkpoint is done into " + self._filepath)
  28. solutionData = ""
  29. solutionSize = len(solution._data)
  30. for index, val in enumerate(solution._data):
  31. solutionData += str(val)
  32. if index < solutionSize - 1:
  33. solutionData += ' '
  34. line = str(currentEvaluation) + ';' + solutionData + ';' + str(
  35. solution.fitness()) + ';\n'
  36. # check if file exists
  37. if not os.path.exists(self._filepath):
  38. with open(self._filepath, 'w') as f:
  39. f.write(line)
  40. else:
  41. with open(self._filepath, 'a') as f:
  42. f.write(line)
  43. def load(self):
  44. """
  45. Load last backup line of solution and set algorithm state (best solution and evaluations) at this backup
  46. """
  47. if os.path.exists(self._filepath):
  48. logging.info('Load best solution from last checkpoint')
  49. with open(self._filepath) as f:
  50. # get last line and read data
  51. lastline = f.readlines()[-1]
  52. data = lastline.split(';')
  53. # get evaluation information
  54. globalEvaluation = int(data[0])
  55. if self._algo.getParent() is not None:
  56. self._algo.getParent()._numberOfEvaluations = globalEvaluation
  57. else:
  58. self._algo._numberOfEvaluations = globalEvaluation
  59. # get best solution data information
  60. solutionData = list(map(int, data[1].split(' ')))
  61. if self._algo._bestSolution is None:
  62. self._algo._bestSolution = self._algo._initializer()
  63. self._algo._bestSolution._data = np.array(solutionData)
  64. self._algo._bestSolution._score = float(data[2])
  65. macop_line(self._algo)
  66. macop_text(self._algo, f'Checkpoint found from `{self._filepath}` file.')
  67. macop_text(self._algo, f'Restart algorithm from evaluation {self._algo._numberOfEvaluations}.')
  68. else:
  69. macop_text(self._algo, 'No backup found... Start running algorithm from evaluation 0.')
  70. logging.info("Can't load backup... Backup filepath not valid in Checkpoint")
  71. macop_line(self._algo)