ROCm/onnxruntime
Dec 2025 – Dec 2025
1 Month active
Languages Used
C++
Technical Skills
C++algorithm designdeep learningmachine learning
naomiOvadia
PROFILE
Naomiovadia
Over a two-month period, No developed and enhanced core ONNX operator functionality in the ROCm/onnxruntime and CodeLinaro/onnxruntime repositories using C++ and advanced algorithm design. No implemented full ONNX-compliant broadcasting for LayerNormalization and RMSNormalization, introducing a generic broadcasting path and fast-path optimization to support diverse input shapes while maintaining performance. Comprehensive unit tests were added to ensure robustness across all valid broadcasting scenarios. In the following month, No addressed a correctness issue in reduction operators by generalizing no-axes handling, introducing a shared helper, and updating all reduction paths for improved interoperability and alignment with ONNX specifications, demonstrating strong engineering depth.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
1,847
Activity Months2
Your Network
181 people
Work History
January 2026
1 Commits
Jan 1, 2026January 2026 monthly summary for CodeLinaro/onnxruntime: Delivered a critical correctness fix for ONNX reduction operators when no axes are provided. Introduced a shared helper to consistently handle no-axes cases and updated all Reduce paths to improve interoperability with ONNX specifications. This work enhances model reliability, cross-backend compatibility, and reduces ambiguity in edge reductions.
1 Commits
Jan 1, 2026January 2026 monthly summary for CodeLinaro/onnxruntime: Delivered a critical correctness fix for ONNX reduction operators when no axes are provided. Introduced a shared helper to consistently handle no-axes cases and updated all Reduce paths to improve interoperability with ONNX specifications. This work enhances model reliability, cross-backend compatibility, and reduces ambiguity in edge reductions.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Key focus: extend broadcasting support for normalization operators to align with ONNX specifications and broaden model compatibility. Implemented a generic broadcasting path for LayerNormalization and RMSNormalization, with a fast-path for exact-match shapes to preserve performance. Updated and added comprehensive tests (layer_norm_op_test.cc, rms_norm_op_test.cc) to cover all valid broadcasting configurations and edge cases. This work fixes gaps in previous broadcasting behavior and improves cross-framework compatibility, reducing model rejection due to shape mismatches. The changes lay groundwork for broader operator coverage in ROCm/onnxruntime.
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Key focus: extend broadcasting support for normalization operators to align with ONNX specifications and broaden model compatibility. Implemented a generic broadcasting path for LayerNormalization and RMSNormalization, with a fast-path for exact-match shapes to preserve performance. Updated and added comprehensive tests (layer_norm_op_test.cc, rms_norm_op_test.cc) to cover all valid broadcasting configurations and edge cases. This work fixes gaps in previous broadcasting behavior and improves cross-framework compatibility, reducing model rejection due to shape mismatches. The changes lay groundwork for broader operator coverage in ROCm/onnxruntime.
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
C++C++ developmentalgorithm designalgorithm optimizationdeep learningmachine learningunit testing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
CodeLinaro/onnxruntime
Jan 2026 – Jan 2026
1 Month active
Languages Used
C++
Technical Skills
C++ developmentalgorithm optimizationunit testing