ROCm/tensorflow-upstream
Apr 2025 – May 2025
2 Months active
Languages Used
C++MLIR
Technical Skills
Build SystemCompiler DevelopmentMLIRQuantizationRefactoringTensorFlow
Laura Pak
PROFILE
Laura Pak
Worked on the ROCm/tensorflow-upstream repository to unify and optimize quantization across TensorFlow and TensorFlow Lite, focusing on consistent 8-bit FakeQuant representation using an MLIR-based pass. Consolidated quantization utilities to reduce code divergence and migrated key passes for improved maintainability. In addition, simplified the build system by decoupling TensorFlow Lite dependencies and removing unused code paths, which streamlined builds and reduced maintenance overhead. Introduced a convolution fusion optimization pass to enhance runtime performance and expanded test tooling with litert-opt for more flexible MLIR optimizations. The work leveraged C++, MLIR, and build system management to improve cross-project consistency and efficiency.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
4
Lines of code
1,560
Activity Months2
Your Network
5129 peopleSame Organization
@google.com4703
Benedict OdaiMember
Craig IngramMember
KayyuriMember
Scott SuarezMember
Agent2Agent (A2A) BotMember
Andreas AbelMember
Aadi KapurMember
Aadish GoelMember
Aahil MehtaMember
Work History
May 2025
4 Commits • 3 Features
May 1, 2025May 2025 monthly summary for ROCm/tensorflow-upstream focused on build simplification, runtime-optimization readiness, and expanded test tooling for MLIR/TensorFlow quantization. The work reduces maintenance burden, accelerates build cycles, and strengthens test coverage for optimization passes.
4 Commits • 3 Features
May 1, 2025May 2025 monthly summary for ROCm/tensorflow-upstream focused on build simplification, runtime-optimization readiness, and expanded test tooling for MLIR/TensorFlow quantization. The work reduces maintenance burden, accelerates build cycles, and strengthens test coverage for optimization passes.
May 2025
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly work summary for ROCm/tensorflow-upstream focused on delivering cross-project quantization improvements and ensuring consistent optimization opportunities across TensorFlow and TensorFlow Lite. The month's work centered on a key feature: quantization unification and optimization across TF and TFLite, driven by an MLIR-based pass that unifies 8-bit FakeQuant representations to enable consistent quantization behavior and better optimization potential.
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly work summary for ROCm/tensorflow-upstream focused on delivering cross-project quantization improvements and ensuring consistent optimization opportunities across TensorFlow and TensorFlow Lite. The month's work centered on a key feature: quantization unification and optimization across TF and TFLite, driven by an MLIR-based pass that unifies 8-bit FakeQuant representations to enable consistent quantization behavior and better optimization potential.
Activity
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Quality Metrics
Correctness92.8%
Maintainability88.6%
Architecture92.8%
Performance78.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++MLIR
Technical Skills
Build SystemBuild System ManagementBuild SystemsC++Compiler DevelopmentMLIROptimizationQuantizationRefactoringTensorFlowTensorFlow Lite
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