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Handle multiproc calls for now
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@@ -50,9 +50,12 @@ class TensorboardCallback(BaseCallback):
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if self.training_env is None:
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return True
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tensorboard_metrics = (
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self.training_env.envs[0].unwrapped.tensorboard_metrics # type: ignore[attr-defined]
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)
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if hasattr(self.training_env, 'envs'):
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tensorboard_metrics = self.training_env.envs[0].unwrapped.tensorboard_metrics
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else:
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# For RL-multiproc - usage of [0] might need to be evaluated
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tensorboard_metrics = self.training_env.get_attr("tensorboard_metrics")[0]
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for metric in local_info:
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if metric not in ["episode", "terminal_observation"]:
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