ROCm/tensorflow-upstream
Dec 2025 – Dec 2025
1 Month active
Languages Used
C++MLIR
Technical Skills
C++MLIRTensorFlow
Hariprasad Ravishankar
PROFILE
Hariprasad Ravishankar
Hravi Shah worked on the ROCm/tensorflow-upstream repository, focusing on stabilizing the quantized uint8 path in the MLIR-to-TOSA conversion workflow. He addressed a critical bug by implementing robust error handling in the TosaConvertTFLUInt8 pass, ensuring that tosa.const operations with quantized uint8 values now trigger explicit errors rather than silent mis-conversions. Using C++ and MLIR, Hravi updated and expanded test coverage to validate the new error path and ui8 attribute handling. His work improved model reliability in quantized deployments and demonstrated depth in MLIR integration, quantization handling, and test automation within the TensorFlow ecosystem.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
1Total
Bugs
1
Commits
1
Features
0
Lines of code
29
Activity Months1
Your Network
439 peopleSame Organization
@mathworks.com13
Work History
December 2025
1 Commits
Dec 1, 2025December 2025 monthly update for ROCm/tensorflow-upstream: focused on stabilizing the quantized uint8 path in the MLIR-to-TOSA conversion by delivering a critical bug fix and test coverage improvements. Implemented robust error handling in the TosaConvertTFLUInt8 pass to abort on tosa.const with quantized uint8 values, preventing silent mis-conversions. Updated tests to validate ui8 attribute handling and aligned changes to avoid regressions. This work enhances model reliability and predictability in quantized deployments, with traceability to commit 4c6f6242d0901eb4e152efd76dde5dc2227612cc, and demonstrates proficiency in MLIR, TOSA passes, quantization, and test automation.
1 Commits
Dec 1, 2025December 2025 monthly update for ROCm/tensorflow-upstream: focused on stabilizing the quantized uint8 path in the MLIR-to-TOSA conversion by delivering a critical bug fix and test coverage improvements. Implemented robust error handling in the TosaConvertTFLUInt8 pass to abort on tosa.const with quantized uint8 values, preventing silent mis-conversions. Updated tests to validate ui8 attribute handling and aligned changes to avoid regressions. This work enhances model reliability and predictability in quantized deployments, with traceability to commit 4c6f6242d0901eb4e152efd76dde5dc2227612cc, and demonstrates proficiency in MLIR, TOSA passes, quantization, and test automation.
December 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++MLIR
Technical Skills
C++MLIRTensorFlow
Repositories Contributed To
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