import os import json import math from .exception import CurriculumError import logging logger = logging.getLogger("mlagents.trainers") class Curriculum(object): def __init__(self, location, default_reset_parameters): """ Initializes a Curriculum object. :param location: Path to JSON defining curriculum. :param default_reset_parameters: Set of reset parameters for environment. """ self.max_lesson_num = 0 self.measure = None self._lesson_num = 0 # The name of the brain should be the basename of the file without the # extension. self._brain_name = os.path.basename(location).split(".")[0] try: with open(location) as data_file: self.data = json.load(data_file) except IOError: raise CurriculumError("The file {0} could not be found.".format(location)) except UnicodeDecodeError: raise CurriculumError("There was an error decoding {}".format(location)) self.smoothing_value = 0 for key in [ "parameters", "measure", "thresholds", "min_lesson_length", "signal_smoothing", ]: if key not in self.data: raise CurriculumError( "{0} does not contain a " "{1} field.".format(location, key) ) self.smoothing_value = 0 self.measure = self.data["measure"] self.min_lesson_length = self.data["min_lesson_length"] self.max_lesson_num = len(self.data["thresholds"]) parameters = self.data["parameters"] for key in parameters: if key not in default_reset_parameters: raise CurriculumError( "The parameter {0} in Curriculum {1} is not present in " "the Environment".format(key, location) ) if len(parameters[key]) != self.max_lesson_num + 1: raise CurriculumError( "The parameter {0} in Curriculum {1} must have {2} values " "but {3} were found".format( key, location, self.max_lesson_num + 1, len(parameters[key]) ) ) @property def lesson_num(self): return self._lesson_num @lesson_num.setter def lesson_num(self, lesson_num): self._lesson_num = max(0, min(lesson_num, self.max_lesson_num)) def increment_lesson(self, measure_val): """ Increments the lesson number depending on the progress given. :param measure_val: Measure of progress (either reward or percentage steps completed). :return Whether the lesson was incremented. """ if not self.data or not measure_val or math.isnan(measure_val): return False if self.data["signal_smoothing"]: measure_val = self.smoothing_value * 0.25 + 0.75 * measure_val self.smoothing_value = measure_val if self.lesson_num < self.max_lesson_num: if measure_val > self.data["thresholds"][self.lesson_num]: self.lesson_num += 1 config = {} parameters = self.data["parameters"] for key in parameters: config[key] = parameters[key][self.lesson_num] logger.info( "{0} lesson changed. Now in lesson {1}: {2}".format( self._brain_name, self.lesson_num, ", ".join([str(x) + " -> " + str(config[x]) for x in config]), ) ) return True return False def get_config(self, lesson=None): """ Returns reset parameters which correspond to the lesson. :param lesson: The lesson you want to get the config of. If None, the current lesson is returned. :return: The configuration of the reset parameters. """ if not self.data: return {} if lesson is None: lesson = self.lesson_num lesson = max(0, min(lesson, self.max_lesson_num)) config = {} parameters = self.data["parameters"] for key in parameters: config[key] = parameters[key][lesson] return config