5c43765011
For b_fs_yx_fsv16 format in reference kernel features for dispatch are rounded to multiple of 16. This change adds correct check in kernel to return work-items that are inside this dispatch padding. Previously those work-items could corrupt memory expected to be filled with 0s, and for parametrized activation due to bounds checking with modulo operator they could have been corrupting actual layer output. Issue: CVS-27672
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.
This open source version includes two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as Caffe*, TensorFlow*, MXNet* and ONNX*.
Repository components:
License
Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.
Documentation
- OpenVINO™ Release Notes
- OpenVINO™ Inference Engine Build Instructions
- Get Started with Deep Learning Deployment Toolkit on Linux*
- Introduction to Deep Learning Deployment Toolkit
- Inference Engine Developer Guide
- Model Optimizer Developer Guide
How to Contribute
See CONTRIBUTING for details. Thank you!
Support
Please report questions, issues and suggestions using:
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openvinotag on StackOverflow* - GitHub* Issues
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