|
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agent_id, training_length=self.policy.sequence_length |
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) |
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self.trainer.process_trajectory(trajectory) |
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self.processing_buffer[agent_id].reset_agent() |
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elif not next_info.local_done[next_idx]: |
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if agent_id not in self.episode_steps: |
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self.episode_steps[agent_id] = 0 |
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|