pytorch/executorch
Oct 2024 – Jan 2026
9 Months active
Languages Used
PythonShell
Technical Skills
PyTorchPythonPython programmingTOSATorchback end development
Per Åstrand
PROFILE
Per Åstrand
Per Åstrand developed and maintained quantization, operator support, and TOSA specification handling for the pytorch/executorch repository, focusing on the Arm backend. Over nine months, he delivered features such as dynamic shape support, multi-version TOSA serialization, and robust quantization folding passes. His work involved integrating TOSA dialects, implementing operator-level optimizations, and refactoring test infrastructure for maintainability. Using Python and PyTorch, Per introduced utilities for version-agnostic operator registration and improved subprocess management, addressing backend reliability and deployment portability. The depth of his contributions is reflected in the breadth of backend improvements, enhanced test coverage, and future-proofed support for evolving TOSA standards.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
26Total
Bugs
5
Commits
26
Features
12
Lines of code
2,908
Activity Months9
Your Network
832 peopleSame Organization
@arm.com497
Work History
January 2026
5 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on strengthening the Arm backend (pytorch/executorch) with multi-version TOSA support, reliability improvements, and new dialect capabilities to future-proof for evolving TOSA specs. Key features delivered include: 1) TOSA 1.1 multi-version support and utilities in the Arm backend, introducing a new Tosa_1_1 specification class, version-agnostic operator registration, and related helpers to manage specifications across versions; 2) centralized and simplified spec handling via spec list helpers and a TosaSpecification list method to ensure consistent operator registration across all supported TOSA versions; 3) New TOSA dialect operation for CONST_SHAPE to create constant-shape tensors, enabling improved shape management in tensor operations; 4) Broader changes to support the new dialect and spec flow with a dedicated ArmPass integration for CONST_SHAPE creation; 5) Reliability improvement in command execution by fixing subprocess invocation in the VGF backend to avoid stdin/read path issues. Impact: these changes reduce maintenance cost for multi-version TOSA support, improve backend reliability and shape-aware tensor operations, and enhance overall production readiness for Arm backend workloads. Technologies/skills demonstrated: ARM backend development, TOSA dialects and specification management, Python subprocess handling, code refactoring for maintainability, and commits-based traceability in a large-scale ML backend.
5 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on strengthening the Arm backend (pytorch/executorch) with multi-version TOSA support, reliability improvements, and new dialect capabilities to future-proof for evolving TOSA specs. Key features delivered include: 1) TOSA 1.1 multi-version support and utilities in the Arm backend, introducing a new Tosa_1_1 specification class, version-agnostic operator registration, and related helpers to manage specifications across versions; 2) centralized and simplified spec handling via spec list helpers and a TosaSpecification list method to ensure consistent operator registration across all supported TOSA versions; 3) New TOSA dialect operation for CONST_SHAPE to create constant-shape tensors, enabling improved shape management in tensor operations; 4) Broader changes to support the new dialect and spec flow with a dedicated ArmPass integration for CONST_SHAPE creation; 5) Reliability improvement in command execution by fixing subprocess invocation in the VGF backend to avoid stdin/read path issues. Impact: these changes reduce maintenance cost for multi-version TOSA support, improve backend reliability and shape-aware tensor operations, and enhance overall production readiness for Arm backend workloads. Technologies/skills demonstrated: ARM backend development, TOSA dialects and specification management, Python subprocess handling, code refactoring for maintainability, and commits-based traceability in a large-scale ML backend.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for pytorch/executorch: Focused on strengthening serialization support and spec management for TOSA on the Arm backend, enabling future hardware backends and improved portability. Delivered experimental TOSA 1.1 serialization support, deprecated outdated TOSA 1.0 specs, and established a flexible spec handling approach with alignment to tosa-tools main branch.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for pytorch/executorch: Focused on strengthening serialization support and spec management for TOSA on the Arm backend, enabling future hardware backends and improved portability. Delivered experimental TOSA 1.1 serialization support, deprecated outdated TOSA 1.0 specs, and established a flexible spec handling approach with alignment to tosa-tools main branch.
October 2025
2 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on business value and technical achievement in pytorch/executorch. Deliverables center on Arm TOSA backend improvements enabling dynamic shapes and enhanced shape handling, with targeted fixes and tests to improve stability and compatibility.
2 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on business value and technical achievement in pytorch/executorch. Deliverables center on Arm TOSA backend improvements enabling dynamic shapes and enhanced shape handling, with targeted fixes and tests to improve stability and compatibility.
October 2025
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on structural improvements to the Arm testing path within executorch and laying groundwork for scalable Arm backend validation. The key change centralized in a common test harness, reducing maintenance overhead and enabling consistent test execution across Arm-related tests. No major bugs recorded this month; changes are infrastructure and maintainability oriented.
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on structural improvements to the Arm testing path within executorch and laying groundwork for scalable Arm backend validation. The key change centralized in a common test harness, reducing maintenance overhead and enabling consistent test execution across Arm-related tests. No major bugs recorded this month; changes are infrastructure and maintainability oriented.
March 2025
2 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for pytorch/executorch focused on delivering features that enhance debugging clarity and per-channel scaling flexibility, with emphasis on business value and robust technical execution.
2 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for pytorch/executorch focused on delivering features that enhance debugging clarity and per-channel scaling flexibility, with emphasis on business value and robust technical execution.
March 2025
February 2025
1 Commits
Feb 1, 2025February 2025 monthly summary focused on stabilizing quantization for the Arm backend in pytorch/executorch. Delivered a compatibility fix for module-type filtering in the quantizer when porting from xnnpack, reducing mis-filtering and improving cross-backend portability.
February 2025
1 Commits
Feb 1, 2025February 2025 monthly summary focused on stabilizing quantization for the Arm backend in pytorch/executorch. Delivered a compatibility fix for module-type filtering in the quantizer when porting from xnnpack, reducing mis-filtering and improving cross-backend portability.
December 2024
4 Commits • 1 Features
Dec 1, 2024December 2024: Delivered Quantization Folding Pass Enhancements and Testing for pytorch/executorch. Implemented input/output quantization parameter retrieval helpers, expanded tests to validate folding and annotation during quantization, and relaxed quantization parameter requirements for TOSA tests to improve robustness and deployment reliability of quantized models. Also introduced helper functions for the Q/DQ folding pass and updated tests to reflect a sequence of ops, increasing test coverage, reliability, and regression safety across backends. This work enhances model quantization fidelity across backends, accelerates QA, and supports broader hardware compatibility.
4 Commits • 1 Features
Dec 1, 2024December 2024: Delivered Quantization Folding Pass Enhancements and Testing for pytorch/executorch. Implemented input/output quantization parameter retrieval helpers, expanded tests to validate folding and annotation during quantization, and relaxed quantization parameter requirements for TOSA tests to improve robustness and deployment reliability of quantized models. Also introduced helper functions for the Q/DQ folding pass and updated tests to reflect a sequence of ops, increasing test coverage, reliability, and regression safety across backends. This work enhances model quantization fidelity across backends, accelerates QA, and supports broader hardware compatibility.
December 2024
November 2024
4 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on delivering quantization and stability improvements in pytorch/executorch, highlighting business value and technical achievements.
November 2024
4 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on delivering quantization and stability improvements in pytorch/executorch, highlighting business value and technical achievements.
October 2024
6 Commits • 3 Features
Oct 1, 2024October 2024: Delivered major TOSA-based enhancements and quantization improvements in executorch. Key features include TOSA Specification integration in ArmPartitioner to guide operator support, implementation of TOSA.MIN and TOSA.MAX with tests, and DQ/Q folding rescaling; addressed critical qdq ADD handling, and improved dequantization safety and TOSA reference model output handling. These changes extend operator coverage, improve quantization accuracy, prevent overflow in BI workloads, and strengthen path for deployment and performance.
6 Commits • 3 Features
Oct 1, 2024October 2024: Delivered major TOSA-based enhancements and quantization improvements in executorch. Key features include TOSA Specification integration in ArmPartitioner to guide operator support, implementation of TOSA.MIN and TOSA.MAX with tests, and DQ/Q folding rescaling; addressed critical qdq ADD handling, and improved dequantization safety and TOSA reference model output handling. These changes extend operator coverage, improve quantization accuracy, prevent overflow in BI workloads, and strengthen path for deployment and performance.
October 2024
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Quality Metrics
Correctness88.4%
Maintainability83.0%
Architecture86.2%
Performance83.0%
AI Usage27.0%
Skills & Technologies
Programming Languages
PythonShell
Technical Skills
Backend DevelopmentDeep LearningMachine LearningPyTorchPythonPython programmingTOSATOSA dialectTOSA dialect integrationTOSA specification handlingTensor operationsTorchback end developmentbackend developmentdata processing
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