NVIDIA/TensorRT-Incubator
Jul 2025 – Feb 2026
4 Months active
Languages Used
C++CMakeLuaMLIR
Technical Skills
Build System ConfigurationCMakeCode GenerationCompiler DevelopmentLua ScriptingMLIR
Yuan Yao
PROFILE
Yuan Yao
Worked on the NVIDIA/TensorRT-Incubator repository, focusing on compiler development and language interoperability over a four-month period. Delivered features such as MLIR-to-Lua translation for multi-branch control flow and improved Lua interoperability by mapping undefined values to nil, enhancing scripting reliability. Addressed build system stability and Python integration by refining CMake configurations and correcting symbol linkage for MLIR dialect registration. Fixed bugs in CLI parsing to ensure accurate user input handling and prevent misconfiguration. Utilized C++, Lua, and CMake to implement targeted, well-documented changes that improved translation coverage, runtime correctness, and overall build reliability for MLIR-based workflows.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
6Total
Bugs
4
Commits
6
Features
2
Lines of code
304
Activity Months4
Your Network
1761 peopleSame Organization
@nvidia.com1746
Shared Repositories
15
Salman Muin Kayser ChishtiMember
Bo WangMember
Christopher BateMember
Jhalak PatelMember
Jhalak PatelMember
lanluo-nvidiaMember
Matthew Francis-LandauMember
Matthew Francis-LandauMember
Copybara BotMember
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 Monthly Summary ( NVIDIA/TensorRT-Incubator ) Focused on strengthening Lua interoperability by ensuring correct handling of undefined values through translation of ub.poison to nil. This feature improves scripting reliability and reduces runtime surprises for users relying on Lua interop in tensor/executor pipelines.
1 Commits • 1 Features
Feb 1, 2026February 2026 Monthly Summary ( NVIDIA/TensorRT-Incubator ) Focused on strengthening Lua interoperability by ensuring correct handling of undefined values through translation of ub.poison to nil. This feature improves scripting reliability and reduces runtime surprises for users relying on Lua interop in tensor/executor pipelines.
February 2026
September 2025
1 Commits
Sep 1, 2025September 2025 monthly summary for NVIDIA/TensorRT-Incubator focused on reliability and correctness in the MLIR-TensorRT CLI parsing path. Implemented a targeted bug fix to ensure inputKind is initialized before use, preventing user inputs from being misinterpreted or defaulting to 'stablehlo' across compilation tasks. This reduces misconfiguration risk and improves downstream build reliability.
September 2025
1 Commits
Sep 1, 2025September 2025 monthly summary for NVIDIA/TensorRT-Incubator focused on reliability and correctness in the MLIR-TensorRT CLI parsing path. Implemented a targeted bug fix to ensure inputKind is initialized before use, preventing user inputs from being misinterpreted or defaulting to 'stablehlo' across compilation tasks. This reduces misconfiguration risk and improves downstream build reliability.
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, expanded the MLIR-to-Lua translation capability in NVIDIA/TensorRT-Incubator to support cf.switch, enabling multi-branch conditional control flow by translating cf.switch into Lua if-elseif chains. This expands the set of programs that can be translated and executed by the Lua executor, reducing manual adaptation and accelerating deployment of complex conditionals. No major bugs fixed this month. Overall impact: increased translation coverage, improved execution fidelity, and faster time-to-value for ML workflows. Technologies/skills demonstrated: MLIR, Lua translation, code generation for conditional logic, and strong version-control traceability (commits).
1 Commits • 1 Features
Aug 1, 2025In August 2025, expanded the MLIR-to-Lua translation capability in NVIDIA/TensorRT-Incubator to support cf.switch, enabling multi-branch conditional control flow by translating cf.switch into Lua if-elseif chains. This expands the set of programs that can be translated and executed by the Lua executor, reducing manual adaptation and accelerating deployment of complex conditionals. No major bugs fixed this month. Overall impact: increased translation coverage, improved execution fidelity, and faster time-to-value for ML workflows. Technologies/skills demonstrated: MLIR, Lua translation, code generation for conditional logic, and strong version-control traceability (commits).
August 2025
July 2025
3 Commits
Jul 1, 2025Summary for 2025-07: Stability and correctness improvements across the NVIDIA/TensorRT-Incubator repo. Focused on build reliability, language interoperability, and Python integration, with targeted fixes and accompanying tests to reduce risk in integration and runtime usage.
July 2025
3 Commits
Jul 1, 2025Summary for 2025-07: Stability and correctness improvements across the NVIDIA/TensorRT-Incubator repo. Focused on build reliability, language interoperability, and Python integration, with targeted fixes and accompanying tests to reduce risk in integration and runtime usage.
Activity
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Quality Metrics
Correctness95.0%
Maintainability83.4%
Architecture83.4%
Performance78.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeLuaMLIR
Technical Skills
Build System ConfigurationC++ programmingCMakeCode GenerationCompiler DevelopmentControl Flow AnalysisLuaLua ScriptingMLIRPython IntegrationTensorRTcompiler design
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