Apply explicit resource cleanup pattern to prevent memory accumulation between hyperopt trials. Fixes OOM crashes that occurred after 1-2 trials on RunPod GPU pods. Changes: - PPO adapter (ppo.rs:455-469): Add drop() for ppo_agent and val_trajectory_batch - TFT adapter (tft.rs:444-457): Add drop() for trainer - Both: CUDA synchronization with 100ms sleep to ensure GPU memory release - Validation: 5/5 trials completed successfully (vs 0-1 before fix) Pattern applied: 1. Explicit drop() of model/trainer objects 2. CUDA sync check + 100ms sleep 3. Resource cleanup logging Validation results (Pod b6kc3mc5lbjiro): - 5 trials completed without OOM (batch sizes 9-229) - Total runtime: 79 minutes - Best loss: 0.047 (Trial 3) - Memory cleanup working correctly between trials Note: MAMBA-2 and DQN adapters already had this fix applied. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
1.7 KiB
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1.7 KiB
Executable File