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21 行
811 B
21 行
811 B
from typing import Any, Dict, List
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import numpy as np
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from mlagents.trainers.components.reward_signals import RewardSignal, RewardSignalResult
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class ExtrinsicRewardSignal(RewardSignal):
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@classmethod
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def check_config(
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cls, config_dict: Dict[str, Any], param_keys: List[str] = None
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) -> None:
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"""
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Checks the config and throw an exception if a hyperparameter is missing. Extrinsic requires strength and gamma
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at minimum.
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"""
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param_keys = ["strength", "gamma"]
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super().check_config(config_dict, param_keys)
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def evaluate_batch(self, mini_batch: Dict[str, np.array]) -> RewardSignalResult:
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env_rews = np.array(mini_batch["environment_rewards"], dtype=np.float32)
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return RewardSignalResult(self.strength * env_rews, env_rews)
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