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This commit adds extensive (commented-out) print statements for debugging potential memory issues and high CPU load. Logs have been added to: - train_optimized.py: Around agent model updates and target updates. - DQNAgent:_prepare_batch_for_update: Around memory sampling and tensor device moves. - DQNAgent.update_model: Bracketing key stages of the model update. - RainbowAgent.update_model: Around N-step buffer operations and TD error calculations. These logs can be uncommented by the user to provide detailed tracing information during execution to help pinpoint sources of memory pressure.
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This commit adds extensive (commented-out) print statements for debugging potential memory issues and high CPU load.
Logs have been added to:
These logs can be uncommented by the user to provide detailed tracing information during execution to help pinpoint sources of memory pressure.