Files
foxhunt/scripts/archive/backtest_runpod_225.sh
jgrusewski e61e8f54da feat(ml): Complete hyperopt infrastructure + documentation
Changes:
- CLAUDE.md: Update OOM fix validation status
- Add comprehensive documentation (30+ markdown reports)
- LSTM encoder varmap bug fix (tft/lstm_encoder.rs:290)
- Quantized LSTM layer matching fix (tft/quantized_lstm.rs)
- Hyperopt paths module (ml/src/hyperopt/paths.rs)
- Training path tests for all adapters (DQN, MAMBA-2, PPO, TFT)
- Checkpoint integrity tests
- Script cleanup: Remove 29 obsolete deployment scripts
- Archive old scripts to scripts/archive/
- New deployment utilities: check_gpu_availability.py, monitor_hyperopt.sh

Validation:
- OOM fixes validated: 5/5 trials successful (pod b6kc3mc5lbjiro)
- Batch-size-max 256 tested successfully
- All hyperopt adapters working correctly

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-29 19:52:21 +01:00

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#!/bin/bash
# Runpod 225-Feature Backtesting Script
# Tests trained TFT model against Wave D targets
# Targets: Sharpe ≥2.0, Win Rate ≥60%, Drawdown ≤15%
set -euo pipefail
# Color output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
# Configuration
MODEL_PATH="models/runpod_trained/tft_225_fp32.safetensors"
DATA_PATH="test_data/ES_FUT_180d.parquet"
INITIAL_CAPITAL=100000
SYMBOLS="ES.FUT,NQ.FUT"
STRATEGY="ml_adaptive_225"
START_DATE="2024-01-01"
END_DATE="2024-06-30"
echo -e "${BLUE}========================================${NC}"
echo -e "${BLUE}Runpod 225-Feature Backtesting${NC}"
echo -e "${BLUE}========================================${NC}"
echo ""
# Step 1: Verify model exists
echo -e "${YELLOW}Step 1/4: Verifying trained model...${NC}"
if [ ! -f "${MODEL_PATH}" ]; then
# Try to find any safetensors file
FOUND_MODEL=$(find models/runpod_trained -name "*.safetensors" -type f | head -1)
if [ -z "$FOUND_MODEL" ]; then
echo -e "${RED}❌ No trained model found in models/runpod_trained/${NC}"
echo "Expected: ${MODEL_PATH}"
echo ""
echo "Available files:"
ls -lh models/runpod_trained/ 2>/dev/null || echo "Directory does not exist"
exit 1
fi
echo -e "${YELLOW}⚠️ Using found model: ${FOUND_MODEL}${NC}"
MODEL_PATH="$FOUND_MODEL"
fi
MODEL_SIZE=$(du -h "${MODEL_PATH}" | cut -f1)
echo -e "${GREEN}✅ Model found: ${MODEL_SIZE}${NC}"
# Step 2: Verify data
echo -e "\n${YELLOW}Step 2/4: Verifying training data...${NC}"
if [ ! -f "${DATA_PATH}" ]; then
echo -e "${RED}❌ Training data not found: ${DATA_PATH}${NC}"
exit 1
fi
DATA_SIZE=$(du -h "${DATA_PATH}" | cut -f1)
ROW_COUNT=$(parquet-tools rowcount "${DATA_PATH}" 2>/dev/null || echo "unknown")
echo -e "${GREEN}✅ Data found: ${DATA_SIZE}, Rows: ${ROW_COUNT}${NC}"
# Step 3: Run backtest
echo -e "\n${YELLOW}Step 3/4: Running backtest...${NC}"
echo "Configuration:"
echo " • Model: ${MODEL_PATH}"
echo " • Data: ${DATA_PATH}"
echo " • Initial Capital: \$${INITIAL_CAPITAL}"
echo " • Symbols: ${SYMBOLS}"
echo " • Strategy: ${STRATEGY}"
echo " • Period: ${START_DATE} to ${END_DATE}"
echo ""
BACKTEST_START=$(date +%s)
# Run backtest (adjust command based on actual backtesting CLI)
cargo run -p backtesting --release --features cuda --example feature_comparison_backtest -- \
--model-path "${MODEL_PATH}" \
--parquet-file "${DATA_PATH}" \
--initial-capital ${INITIAL_CAPITAL} \
--symbols "${SYMBOLS}" \
--strategy "${STRATEGY}" \
--start-date "${START_DATE}" \
--end-date "${END_DATE}" \
2>&1 | tee backtest_225.log
BACKTEST_END=$(date +%s)
BACKTEST_DURATION=$((BACKTEST_END - BACKTEST_START))
echo -e "\n${GREEN}✅ Backtest completed in ${BACKTEST_DURATION}s${NC}"
# Step 4: Extract and validate metrics
echo -e "\n${YELLOW}Step 4/4: Extracting Wave D metrics...${NC}"
# Extract key metrics from backtest output
SHARPE=$(grep -oP "Sharpe Ratio[:\s]+\K[0-9.]+" backtest_225.log | tail -1 || echo "N/A")
WIN_RATE=$(grep -oP "Win Rate[:\s]+\K[0-9.]+" backtest_225.log | tail -1 || echo "N/A")
DRAWDOWN=$(grep -oP "Max Drawdown[:\s]+\K[0-9.]+" backtest_225.log | tail -1 || echo "N/A")
TOTAL_PNL=$(grep -oP "Total PnL[:\s]+\$?\K[0-9.]+" backtest_225.log | tail -1 || echo "N/A")
TOTAL_TRADES=$(grep -oP "Total Trades[:\s]+\K[0-9]+" backtest_225.log | tail -1 || echo "N/A")
echo ""
echo -e "${BLUE}========================================${NC}"
echo -e "${BLUE}Wave D Backtest Results${NC}"
echo -e "${BLUE}========================================${NC}"
echo ""
# Sharpe Ratio validation
echo -e "${BLUE}Sharpe Ratio:${NC} ${SHARPE}"
if [ "$SHARPE" != "N/A" ] && [ "$(echo "${SHARPE} >= 2.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
echo -e " ${GREEN}✅ Target: ≥2.0 (PASSED)${NC}"
else
echo -e " ${RED}❌ Target: ≥2.0 (FAILED)${NC}"
fi
echo ""
# Win Rate validation
echo -e "${BLUE}Win Rate:${NC} ${WIN_RATE}%"
if [ "$WIN_RATE" != "N/A" ] && [ "$(echo "${WIN_RATE} >= 60.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
echo -e " ${GREEN}✅ Target: ≥60% (PASSED)${NC}"
else
echo -e " ${RED}❌ Target: ≥60% (FAILED)${NC}"
fi
echo ""
# Drawdown validation
echo -e "${BLUE}Max Drawdown:${NC} ${DRAWDOWN}%"
if [ "$DRAWDOWN" != "N/A" ] && [ "$(echo "${DRAWDOWN} <= 15.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
echo -e " ${GREEN}✅ Target: ≤15% (PASSED)${NC}"
else
echo -e " ${RED}❌ Target: ≤15% (FAILED)${NC}"
fi
echo ""
# Additional metrics
echo -e "${BLUE}Additional Metrics:${NC}"
echo " • Total PnL: \$${TOTAL_PNL}"
echo " • Total Trades: ${TOTAL_TRADES}"
echo " • Backtest Duration: ${BACKTEST_DURATION}s"
echo ""
# Overall assessment
echo -e "${BLUE}========================================${NC}"
PASSED_COUNT=0
if [ "$SHARPE" != "N/A" ] && [ "$(echo "${SHARPE} >= 2.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
PASSED_COUNT=$((PASSED_COUNT + 1))
fi
if [ "$WIN_RATE" != "N/A" ] && [ "$(echo "${WIN_RATE} >= 60.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
PASSED_COUNT=$((PASSED_COUNT + 1))
fi
if [ "$DRAWDOWN" != "N/A" ] && [ "$(echo "${DRAWDOWN} <= 15.0" | bc -l 2>/dev/null || echo 0)" -eq 1 ]; then
PASSED_COUNT=$((PASSED_COUNT + 1))
fi
if [ $PASSED_COUNT -eq 3 ]; then
echo -e "${GREEN}✅ All Wave D Targets PASSED (3/3)${NC}"
echo ""
echo "Model is ready for production deployment!"
elif [ $PASSED_COUNT -ge 2 ]; then
echo -e "${YELLOW}⚠️ Partial Success: ${PASSED_COUNT}/3 Targets Passed${NC}"
echo ""
echo "Model shows promise but may need fine-tuning."
else
echo -e "${RED}❌ Wave D Targets NOT MET (${PASSED_COUNT}/3 Passed)${NC}"
echo ""
echo "Model requires additional training or hyperparameter tuning."
fi
echo -e "${BLUE}========================================${NC}"
echo ""
echo "Next Steps:"
echo " 1. Review detailed backtest log: backtest_225.log"
echo " 2. Generate results report: see RUNPOD_225_FEATURE_TRAINING_RESULTS.md"
echo " 3. Train additional models: DQN, PPO, MAMBA-2"
echo " 4. Multi-asset validation: NQ.FUT, 6E.FUT, ZN.FUT"
echo ""