import json import math from typing import Dict, Any, TextIO from .exception import CurriculumConfigError, CurriculumLoadingError from mlagents_envs.logging_util import get_logger logger = get_logger(__name__) class Curriculum: def __init__(self, brain_name: str, config: Dict): """ Initializes a Curriculum object. :param brain_name: Name of the brain this Curriculum is associated with :param config: Dictionary of fields needed to configure the Curriculum """ self.max_lesson_num = 0 self.measure = None self._lesson_num = 0 self.brain_name = brain_name self.config = config self.smoothing_value = 0.0 for key in [ "parameters", "measure", "thresholds", "min_lesson_length", "signal_smoothing", ]: if key not in self.config: raise CurriculumConfigError( f"{brain_name} curriculum config does not contain a {key} field." ) self.smoothing_value = 0 self.measure = self.config["measure"] self.min_lesson_length = self.config["min_lesson_length"] self.max_lesson_num = len(self.config["thresholds"]) parameters = self.config["parameters"] for key in parameters: if len(parameters[key]) != self.max_lesson_num + 1: raise CurriculumConfigError( f"The parameter {key} in {brain_name}'s curriculum must have {self.max_lesson_num + 1} values " f"but {len(parameters[key])} were found" ) @property def lesson_num(self) -> int: return self._lesson_num @lesson_num.setter def lesson_num(self, lesson_num: int) -> None: self._lesson_num = max(0, min(lesson_num, self.max_lesson_num)) def increment_lesson(self, measure_val: float) -> bool: """ 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.config or not measure_val or math.isnan(measure_val): return False if self.config["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.config["thresholds"][self.lesson_num]: self.lesson_num += 1 config = {} parameters = self.config["parameters"] for key in parameters: config[key] = parameters[key][self.lesson_num] logger.info( "{} lesson changed. Now in lesson {}: {}".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: int = None) -> Dict[str, Any]: """ 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.config: return {} if lesson is None: lesson = self.lesson_num lesson = max(0, min(lesson, self.max_lesson_num)) config = {} parameters = self.config["parameters"] for key in parameters: config[key] = parameters[key][lesson] return config @staticmethod def load_curriculum_file(config_path: str) -> Dict: try: with open(config_path) as data_file: return Curriculum._load_curriculum(data_file) except OSError: raise CurriculumLoadingError(f"The file {config_path} could not be found.") except UnicodeDecodeError: raise CurriculumLoadingError(f"There was an error decoding {config_path}") @staticmethod def _load_curriculum(fp: TextIO) -> Dict: try: return json.load(fp) except json.decoder.JSONDecodeError as e: raise CurriculumLoadingError( "Error parsing JSON file. Please check for formatting errors. " "A tool such as https://jsonlint.com/ can be helpful with this." ) from e