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91 行
3.4 KiB
91 行
3.4 KiB
import math
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from typing import Dict, Any
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from mlagents.trainers.exception import CurriculumConfigError
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from mlagents_envs.logging_util import get_logger
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from mlagents.trainers.settings import CurriculumSettings
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logger = get_logger(__name__)
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class Curriculum:
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def __init__(self, brain_name: str, settings: CurriculumSettings):
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"""
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Initializes a Curriculum object.
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:param brain_name: Name of the brain this Curriculum is associated with
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:param config: Dictionary of fields needed to configure the Curriculum
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"""
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self.max_lesson_num = 0
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self.measure = None
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self._lesson_num = 0
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self.brain_name = brain_name
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self.settings = settings
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self.smoothing_value = 0.0
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self.measure = self.settings.measure
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self.min_lesson_length = self.settings.min_lesson_length
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self.max_lesson_num = len(self.settings.thresholds)
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parameters = self.settings.parameters
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for key in parameters:
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if len(parameters[key]) != self.max_lesson_num + 1:
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raise CurriculumConfigError(
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f"The parameter {key} in {brain_name}'s curriculum must have {self.max_lesson_num + 1} values "
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f"but {len(parameters[key])} were found"
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)
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@property
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def lesson_num(self) -> int:
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return self._lesson_num
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@lesson_num.setter
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def lesson_num(self, lesson_num: int) -> None:
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self._lesson_num = max(0, min(lesson_num, self.max_lesson_num))
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def increment_lesson(self, measure_val: float) -> bool:
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"""
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Increments the lesson number depending on the progress given.
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:param measure_val: Measure of progress (either reward or percentage
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steps completed).
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:return Whether the lesson was incremented.
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"""
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if not self.settings or not measure_val or math.isnan(measure_val):
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return False
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if self.settings.signal_smoothing:
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measure_val = self.smoothing_value * 0.25 + 0.75 * measure_val
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self.smoothing_value = measure_val
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if self.lesson_num < self.max_lesson_num:
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if measure_val > self.settings.thresholds[self.lesson_num]:
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self.lesson_num += 1
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config = {}
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parameters = self.settings.parameters
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for key in parameters:
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config[key] = parameters[key][self.lesson_num]
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logger.info(
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"{0} lesson changed. Now in lesson {1}: {2}".format(
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self.brain_name,
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self.lesson_num,
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", ".join([str(x) + " -> " + str(config[x]) for x in config]),
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)
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)
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return True
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return False
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def get_config(self, lesson: int = None) -> Dict[str, Any]:
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"""
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Returns reset parameters which correspond to the lesson.
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:param lesson: The lesson you want to get the config of. If None, the
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current lesson is returned.
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:return: The configuration of the reset parameters.
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"""
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if not self.settings:
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return {}
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if lesson is None:
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lesson = self.lesson_num
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lesson = max(0, min(lesson, self.max_lesson_num))
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config = {}
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parameters = self.settings.parameters
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for key in parameters:
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config[key] = parameters[key][lesson]
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return config
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