llvm/torch-mlir
Jan 2025 – Jan 2025
1 Month active
Languages Used
C++CMakeMLIRPython
Technical Skills
Build SystemsC++ developmentCMakeCompiler DesignMLIRModule management
Sagar Shelke
PROFILE
Sagar Shelke
Sagar Shelke worked on enhancing interoperability and pipeline reliability for the llvm/torch-mlir repository, focusing on integration with external StableHLO projects. He refactored Python module imports to use relative paths, improving packaging robustness and reducing import-time errors. Using CMake and C++, Sagar enabled the build system to accept external projects, supporting broader ecosystem compatibility. He also optimized seed generation in the Torch-to-MLIR conversion pipeline, ensuring seeds are only created when necessary to prevent downstream compiler issues. The work demonstrated a solid understanding of build systems, module management, and compiler design, addressing integration and reliability challenges with targeted, maintainable solutions.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
1
Lines of code
53
Activity Months1
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Work History
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025: Focused on interoperability and pipeline reliability for llvm/torch-mlir. Delivered external integration and embedding compatibility with StableHLO projects, enhanced build and import hygiene, and optimized seed handling in the Torch-to-MLIR conversion pipeline. These efforts improve business value by enabling easier integration with external ecosystems and reducing downstream build/compile risk.
3 Commits • 1 Features
Jan 1, 2025January 2025: Focused on interoperability and pipeline reliability for llvm/torch-mlir. Delivered external integration and embedding compatibility with StableHLO projects, enhanced build and import hygiene, and optimized seed handling in the Torch-to-MLIR conversion pipeline. These efforts improve business value by enabling easier integration with external ecosystems and reducing downstream build/compile risk.
January 2025
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Quality Metrics
Correctness93.4%
Maintainability86.6%
Architecture93.4%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeMLIRPython
Technical Skills
Build SystemsC++ developmentCMakeCompiler DesignMLIRModule managementPython developmentSoftware architecturecompiler designmachine learning
Repositories Contributed To
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