#!/bin/bash
set -e

echo "========================================="
echo "TFT Hyperopt Deployment"
echo "========================================="
echo ""

# Set PYTHONPATH
export PYTHONPATH="/home/jgrusewski/Work/foxhunt:$PYTHONPATH"

# Activate venv
source .venv/bin/activate

# Deploy TFT hyperopt with optimal batch size for RTX 4090 (24GB VRAM)
# Higher batch sizes possible due to increased memory (128 → 192)
python3 scripts/runpod_deploy.py \
    --gpu-type "RTX 4090" \
    --image "jgrusewski/foxhunt-hyperopt:latest" \
    --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"

echo ""
echo "✅ TFT hyperopt deployment initiated"
echo "Monitor logs: python3 scripts/python/runpod/monitor_logs.py <pod_id>"
echo "Expected duration: 30-40 hours (faster with RTX 4090)"
echo "Expected cost: \$17.70-\$23.60 @ \$0.59/hr (RTX 4090 24GB)"
echo ""
echo "Success Criteria:"
echo "  - Validation loss decreasing"
echo "  - Attention weights converging"
echo "  - Quantile predictions balanced (0.1, 0.5, 0.9)"
echo "  - Final backtest: > 10% return, Sharpe > 1.5"