Files
foxhunt/archive/scripts/deploy_hyperopt_direct.sh
jgrusewski 2df1ea92e1 feat(ml): WAVE 29 DQN Codebase Cleanup & Refactoring Campaign
BREAKING CHANGES:
- Removed orphaned dqn.rs monolithic trainer (4,975 lines)
- Removed orphaned dqn_ensemble.rs module (816 lines)
- Removed orphaned tft.rs and tft_complete_int8_integration_test.rs
- TFT trainer split into modular directory structure

DQN Module Refactoring:
- Split trainers/dqn.rs into modular structure (config.rs, statistics.rs, trainer.rs)
- Fixed hyperopt 39D search space (continuous params only)
- Boolean flags (use_dueling, use_double_dqn, use_per, use_noisy_nets) are now FIXED architectural decisions
- use_distributional defaults to false (Candle BUG #36 - scatter_add gradient issues)

Clean Module Structure:
- ml/src/trainers/dqn/ directory with proper mod.rs exports
- ml/src/trainers/tft/ directory with config.rs, types.rs, model.rs, trainer.rs, tests.rs
- All P0 features validated: TD-error clamping, batch diversity, LR scheduler, priority staleness

Documentation:
- Added comprehensive docs in docs/codebase-cleanup/
- ADR-001 for DQN refactoring decisions
- Rainbow DQN component matrix and quick reference guides

Build Status: Compiles with zero errors

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-27 23:46:13 +01:00

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#!/bin/bash
set -e
# Load RunPod credentials
source .env.runpod
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
echo "========================================="
echo "RunPod Hyperopt Deployment (Direct REST API)"
echo "========================================="
echo ""
echo "Deploying 2 pods:"
echo " 1. DQN Hyperopt"
echo " 2. PPO Hyperopt"
echo ""
# Deploy DQN Hyperopt Pod
echo "========================================="
echo "1. DEPLOYING DQN HYPEROPT POD"
echo "========================================="
DQN_OUTPUT_DIR="dqn_hyperopt_${TIMESTAMP}"
DQN_PAYLOAD=$(cat <<EOF
{
"cloudType": "SECURE",
"computeType": "GPU",
"dataCenterIds": ["EUR-IS-1"],
"dataCenterPriority": "availability",
"gpuTypeIds": ["NVIDIA RTX A4000"],
"gpuCount": 1,
"name": "foxhunt-dqn-hyperopt-${TIMESTAMP}",
"imageName": "jgrusewski/foxhunt-hyperopt:latest",
"containerDiskInGb": 50,
"networkVolumeId": "${RUNPOD_VOLUME_ID}",
"volumeMountPath": "/runpod-volume",
"dockerStartCmd": [
"hyperopt_dqn_demo",
"--parquet-file", "/runpod-volume/test_data/ES_FUT_180d.parquet",
"--trials", "50",
"--epochs", "100",
"--base-dir", "/runpod-volume/ml_training/${DQN_OUTPUT_DIR}"
],
"containerRegistryAuthId": "${RUNPOD_CONTAINER_REGISTRY_AUTH_ID}",
"ports": ["8888/http", "22/tcp"],
"interruptible": false
}
EOF
)
echo "Deploying DQN pod..."
DQN_RESPONSE=$(curl -s -X POST https://rest.runpod.io/v1/pods \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${RUNPOD_API_KEY}" \
-d "$DQN_PAYLOAD")
DQN_POD_ID=$(echo "$DQN_RESPONSE" | jq -r '.id // "ERROR"')
if [ "$DQN_POD_ID" = "ERROR" ] || [ "$DQN_POD_ID" = "null" ]; then
echo "ERROR: Failed to deploy DQN pod"
echo "Response: $DQN_RESPONSE"
exit 1
fi
echo "✅ DQN Pod Deployed Successfully"
echo " Pod ID: $DQN_POD_ID"
echo " GPU: $(echo "$DQN_RESPONSE" | jq -r '.machine.gpuType.displayName // "RTX A4000"')"
echo " Datacenter: $(echo "$DQN_RESPONSE" | jq -r '.machine.dataCenterId // "EUR-IS-1"')"
echo " Cost: \$$(echo "$DQN_RESPONSE" | jq -r '.costPerHr // "0.25"')/hr"
echo " Output: /runpod-volume/ml_training/${DQN_OUTPUT_DIR}"
echo ""
# Deploy PPO Hyperopt Pod
echo "========================================="
echo "2. DEPLOYING PPO HYPEROPT POD"
echo "========================================="
PPO_OUTPUT_DIR="ppo_hyperopt_${TIMESTAMP}"
PPO_PAYLOAD=$(cat <<EOF
{
"cloudType": "SECURE",
"computeType": "GPU",
"dataCenterIds": ["EUR-IS-1"],
"dataCenterPriority": "availability",
"gpuTypeIds": ["NVIDIA RTX A4000"],
"gpuCount": 1,
"name": "foxhunt-ppo-hyperopt-${TIMESTAMP}",
"imageName": "jgrusewski/foxhunt-hyperopt:latest",
"containerDiskInGb": 50,
"networkVolumeId": "${RUNPOD_VOLUME_ID}",
"volumeMountPath": "/runpod-volume",
"dockerStartCmd": [
"hyperopt_ppo_demo",
"--parquet-file", "/runpod-volume/test_data/ES_FUT_180d.parquet",
"--trials", "50",
"--episodes", "2000",
"--base-dir", "/runpod-volume/ml_training/${PPO_OUTPUT_DIR}",
"--early-stopping-min-epochs", "50"
],
"containerRegistryAuthId": "${RUNPOD_CONTAINER_REGISTRY_AUTH_ID}",
"ports": ["8888/http", "22/tcp"],
"interruptible": false
}
EOF
)
echo "Deploying PPO pod..."
PPO_RESPONSE=$(curl -s -X POST https://rest.runpod.io/v1/pods \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${RUNPOD_API_KEY}" \
-d "$PPO_PAYLOAD")
PPO_POD_ID=$(echo "$PPO_RESPONSE" | jq -r '.id // "ERROR"')
if [ "$PPO_POD_ID" = "ERROR" ] || [ "$PPO_POD_ID" = "null" ]; then
echo "ERROR: Failed to deploy PPO pod"
echo "Response: $PPO_RESPONSE"
exit 1
fi
echo "✅ PPO Pod Deployed Successfully"
echo " Pod ID: $PPO_POD_ID"
echo " GPU: $(echo "$PPO_RESPONSE" | jq -r '.machine.gpuType.displayName // "RTX A4000"')"
echo " Datacenter: $(echo "$PPO_RESPONSE" | jq -r '.machine.dataCenterId // "EUR-IS-1"')"
echo " Cost: \$$(echo "$PPO_RESPONSE" | jq -r '.costPerHr // "0.25"')/hr"
echo " Output: /runpod-volume/ml_training/${PPO_OUTPUT_DIR}"
echo ""
# Summary
echo "========================================="
echo "DEPLOYMENT SUMMARY"
echo "========================================="
echo ""
echo "DQN Hyperopt:"
echo " Pod ID: $DQN_POD_ID"
echo " Output: /runpod-volume/ml_training/${DQN_OUTPUT_DIR}"
echo " Trials: 50"
echo " Epochs/trial: 100"
echo " Expected duration: 12-25 min"
echo " Expected cost: \$0.05-\$0.10"
echo ""
echo "PPO Hyperopt:"
echo " Pod ID: $PPO_POD_ID"
echo " Output: /runpod-volume/ml_training/${PPO_OUTPUT_DIR}"
echo " Trials: 50"
echo " Episodes/trial: 2000"
echo " Expected duration: 10-20 min"
echo " Expected cost: \$0.04-\$0.08"
echo ""
echo "TOTAL ESTIMATED COST: \$0.09-\$0.18"
echo ""
echo "========================================="
echo "MONITORING COMMANDS"
echo "========================================="
echo ""
echo "Monitor DQN logs:"
echo " ./monitor_dqn_hyperopt_pod.sh $DQN_POD_ID"
echo ""
echo "Monitor PPO logs:"
echo " ./monitor_ppo_hyperopt_pod.sh $PPO_POD_ID"
echo ""
echo "View pods in dashboard:"
echo " https://www.runpod.io/console/pods"
echo ""
echo "Check S3 results (after completion):"
echo " aws s3 ls s3://se3zdnb5o4/ml_training/${DQN_OUTPUT_DIR}/ --profile runpod --recursive"
echo " aws s3 ls s3://se3zdnb5o4/ml_training/${PPO_OUTPUT_DIR}/ --profile runpod --recursive"
echo ""
echo "Terminate pods (when complete):"
echo " curl -X POST https://rest.runpod.io/v1/pods/${DQN_POD_ID}/terminate \\"
echo " -H \"Authorization: Bearer \$RUNPOD_API_KEY\""
echo " curl -X POST https://rest.runpod.io/v1/pods/${PPO_POD_ID}/terminate \\"
echo " -H \"Authorization: Bearer \$RUNPOD_API_KEY\""
echo ""