* new implementation of FakeQuantize
* move FakeQuantize backend test to fake_quantize.in.cpp
* enable some test for FakeQuantize
* Add support for PDPD broadcasting and some backend tests
* arm plugin expect less attributes in function call
* try to fix arm plugin build
* try to build arm plugin
* start changing backend test
* add check for attributes number in visitor test
* fix backend test after refactoring
* add default parameter value to runtime::reference::fake_quantize
* Revert "add default parameter value to runtime::reference::fake_quantize"
This reverts commit
|
||
---|---|---|
.ci | ||
.github | ||
cmake | ||
docs | ||
inference-engine | ||
licensing | ||
model-optimizer | ||
ngraph | ||
openvino | ||
scripts | ||
tests | ||
thirdparty | ||
tools | ||
.gitattributes | ||
.gitignore | ||
.gitmodules | ||
CMakeLists.txt | ||
CODEOWNERS | ||
install_build_dependencies.sh | ||
Jenkinsfile | ||
LICENSE | ||
README.md | ||
SECURITY.md |
OpenVINO™ Toolkit
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
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ modules: https://github.com/openvinotoolkit/openvino_contrib
- Intel® Distribution of OpenVINO™ toolkit Product Page
- Intel® Distribution of OpenVINO™ toolkit Release Notes
Support
Please report questions, issues and suggestions using:
- The
openvino
tag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.