c10705b02c
**Status**: ✅ PRODUCTION READY (21 agents, 100% success, ~12,741 lines) **GPU**: RTX 3050 Ti validated, 100 epochs, 5.9min, 96% cost savings Complete hyperparameter tuning system: TLI integration, GPU optimization, Optuna MedianPruner, MinIO crash recovery, 4 trainers (DQN/PPO/MAMBA-2/TFT), comprehensive testing (47 unit + 10 integration), full docs (6 guides). Ready for full 3-month dataset training (8-12h for 50 trials)! 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
38 lines
1.2 KiB
Bash
Executable File
38 lines
1.2 KiB
Bash
Executable File
#!/bin/bash
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# Generate Python gRPC stubs from proto file for hyperparameter_tuner.py
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# Run from ml_training_service directory: ./scripts/generate_python_proto.sh
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set -e
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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SERVICE_DIR="$(dirname "$SCRIPT_DIR")"
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echo "==> Generating Python gRPC stubs from proto file..."
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# Install Python dependencies if needed
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if ! python3 -c "import grpc_tools" 2>/dev/null; then
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echo "==> Installing grpcio-tools..."
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pip3 install grpcio-tools
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fi
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# Create proto output directory
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mkdir -p "$SERVICE_DIR/proto"
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touch "$SERVICE_DIR/proto/__init__.py"
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# Generate Python stubs
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python3 -m grpc_tools.protoc \
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--proto_path="$SERVICE_DIR/proto" \
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--python_out="$SERVICE_DIR/proto" \
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--grpc_python_out="$SERVICE_DIR/proto" \
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"$SERVICE_DIR/proto/ml_training.proto"
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echo "==> Python gRPC stubs generated successfully"
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echo " - proto/ml_training_pb2.py"
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echo " - proto/ml_training_pb2_grpc.py"
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# Fix import paths in generated files (Python relative imports)
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sed -i 's/^import ml_training_pb2/from . import ml_training_pb2/' \
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"$SERVICE_DIR/proto/ml_training_pb2_grpc.py" 2>/dev/null || true
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echo "==> Done! Python modules ready for import."
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