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* [GNA] added support for per-channel FakeQuantise layer * [GNA] added quantisation types detection in FQ enabled networks, and added input scale factors detection from FQ connected to input layer * added FakeQuantize callback that will be use to cast integer values stored as float in FakeQuantized layer * fixed per-channel multiplier calculation for int8 case * precision improvements for int8 fake quantization and support for propagating scale factors to activation layers * added initial int16 support * added support for fake quantize layer with many connected output layers and support for FQ data encoded as FP16 * added support for already quantized weights * Shared single layer test * Added subgraph test * Fix comment * int8 * Enabling FQ tests on GNA Co-authored-by: Eugene Smirnov <eugene.smirnov@intel.com> Co-authored-by: Andrey Dmitriev <andrey.dmitriev@intel.com> |
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| openvino | ||
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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 several components: namely Model Optimizer, ngraph and Inference Engine, as well as CPU, GPU, MYRIAD, multi device 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.
Resources:
- Docs: https://docs.openvinotoolkit.org/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Additional OpenVINO modules: https://github.com/openvinotoolkit/openvino_contrib
- HomePage
- OpenVINO™ Release Notes
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.