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