apache/tvm
Apr 2025 – Apr 2025
1 Month active
Languages Used
C++Python
Technical Skills
Deep Learning FrameworksFrontend DevelopmentFrontend IntegrationGraph ImporterGraph TranslationIR Transformation
Pratheesh-04-MCW
PROFILE
Pratheesh-04-mcw
Pratheeshwaran Siddhuraj enhanced the apache/tvm repository by expanding PyTorch interoperability and advancing the Relax frontend to support broader model export and deployment paths. He implemented new operator support—including stack, roll, index_put_, zeros_like, fill_, masked_fill, logical_not, and new_zeros—by developing operator implementations, integrating them into the frontend, and creating comprehensive unit tests. Using C++ and Python, he focused on frontend integration, IR transformation, and tensor manipulation to improve end-to-end model accuracy and reduce deployment iteration time. His work enabled more PyTorch models to export to Relax, reflecting a deep understanding of deep learning frameworks and model translation.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
6
Lines of code
1,782
Activity Months1
Your Network
105 people
Work History
April 2025
6 Commits • 6 Features
Apr 1, 20252025-04 Monthly Summary – Apache TVM (tvm): Focused on expanding PyTorch interoperability and Relax frontend capabilities to enable broader export/run paths and improve model throughput. Key activities included end-to-end operator support, frontend translations, and tests across Relax and Exported Program frontends, with a strong emphasis on business value: enabling more PyTorch models to export to Relax, improving end-to-end accuracy, and reducing iteration time for model deployment.
6 Commits • 6 Features
Apr 1, 20252025-04 Monthly Summary – Apache TVM (tvm): Focused on expanding PyTorch interoperability and Relax frontend capabilities to enable broader export/run paths and improve model throughput. Key activities included end-to-end operator support, frontend translations, and tests across Relax and Exported Program frontends, with a strong emphasis on business value: enabling more PyTorch models to export to Relax, improving end-to-end accuracy, and reducing iteration time for model deployment.
April 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability93.4%
Architecture96.6%
Performance93.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Deep Learning FrameworksFrontend DevelopmentFrontend IntegrationGraph ImporterGraph TranslationIR TransformationModel TranslationOperator ImplementationOperator SupportPyTorch IntegrationTVM RelaxTensor ManipulationTestingUnit Testing
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