3853988af7
- Fixed PSO budget calculation bug in ml/src/hyperopt/optimizer.rs - Root cause: Division by n_particles in sequential execution - Now correctly calculates max_iters = remaining_trials (no division) - Result: 50 trials complete instead of 23 (100% vs 46%) - Added comprehensive DQN hyperopt results analysis - 39/50 trials analyzed across 2 RunPod deployments - Best hyperparameters identified: LR 4.89e-5 (ultra-low) - Created DQN_HYPEROPT_RESULTS_SUMMARY.md with expert validation - GitLab CI/CD pipeline operational (48 lines fixed) - Fixed YAML syntax errors (unquoted colons) - All 7 jobs validated and working - Warning cleanup complete (136 → 0 warnings) - Removed 143 lines dead code - Fixed visibility, unused imports, Debug traits - Archived Wave D reports to docs/archive/ - 8 early stopping reports moved - Root directory cleaned up 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
33 lines
1.2 KiB
Bash
Executable File
33 lines
1.2 KiB
Bash
Executable File
#!/bin/bash
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set -e
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echo "========================================="
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echo "TFT Hyperopt Deployment"
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echo "========================================="
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echo ""
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# Set PYTHONPATH
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export PYTHONPATH="/home/jgrusewski/Work/foxhunt:$PYTHONPATH"
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# Activate venv
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source .venv/bin/activate
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# Deploy TFT hyperopt with optimal batch size for RTX 4090 (24GB VRAM)
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# Higher batch sizes possible due to increased memory (128 → 192)
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python3 scripts/runpod_deploy.py \
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--gpu-type "RTX 4090" \
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--image "jgrusewski/foxhunt-hyperopt:latest" \
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--command "hyperopt_tft_demo --parquet-file /runpod-volume/test_data/ES_FUT_180d.parquet --trials 50 --epochs 100 --batch-size-min 16 --batch-size-max 192 --base-dir /runpod-volume/ml_training/tft_hyperopt --early-stopping-patience 10"
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echo ""
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echo "✅ TFT hyperopt deployment initiated"
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echo "Monitor logs: python3 scripts/python/runpod/monitor_logs.py <pod_id>"
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echo "Expected duration: 30-40 hours (faster with RTX 4090)"
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echo "Expected cost: \$17.70-\$23.60 @ \$0.59/hr (RTX 4090 24GB)"
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echo ""
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echo "Success Criteria:"
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echo " - Validation loss decreasing"
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echo " - Attention weights converging"
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echo " - Quantile predictions balanced (0.1, 0.5, 0.9)"
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echo " - Final backtest: > 10% return, Sharpe > 1.5"
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