OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Mateusz Bencer ccdd0e61d5
Fixed expanding ONNX function (#7747)
* fix expand_onnx_functions

* refactor + unit test

* fixed function in function case

* fixed expand_onnx_functions

* fixed default value of shape in ValueInfo

* enable xpass model

* changed MergeFrom to Swap

* added xfail with missing test data

* added more unit tests

* styles applied

* used std::rotate, review remarks

* removed debug code

* after offline discussion remarks

* fix checking input/output names on Windows

* names comparator refactor

* replace regex with custom comparison

* review remarks
2021-10-15 13:40:28 +03:00
.ci Fix coverity linux pipeline (#7879) 2021-10-07 22:00:39 +03:00
.github [Python API] Move samples and docs to the new directory (#7851) 2021-10-14 14:49:35 +03:00
cmake Added remote objects type check (#7606) 2021-10-14 11:32:19 +03:00
docs Slice-8 Reference implementation (#7749) 2021-10-15 12:41:39 +03:00
inference-engine [GPU] transformations pipeline is extracted to separate class (#7954) 2021-10-15 12:39:57 +03:00
licensing [Speech sample] Added numpy array support (#5479) 2021-06-03 12:22:06 +03:00
model-optimizer [MO] IR Reader updates for support IR generated by PDPD FE (#7646) 2021-10-15 09:29:07 +03:00
ngraph Fixed expanding ONNX function (#7747) 2021-10-15 13:40:28 +03:00
openvino Added OpenVINO runtime macro (#7586) 2021-09-23 10:39:20 +03:00
runtime Fixed expanding ONNX function (#7747) 2021-10-15 13:40:28 +03:00
samples [Python API] Move samples and docs to the new directory (#7851) 2021-10-14 14:49:35 +03:00
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OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch) PyPI Downloads

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:

Support

Please report questions, issues and suggestions using:


* Other names and brands may be claimed as the property of others.