OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Szymon Durawa 49cd55a5cc
Visitor api loop deserialization (#3894)
* Add on_adpater() implementation for special body parts.

* Remove NodeConverter and LayerCreator for Loop. Add WA for different number of inputs during Loop init by constructor and visit_attributes().

* Format files.

* Implement use case external_port_id=-1 for output port_map,change API for map_type_in_function.

* Replace GetStrAttr() with GetInt64Attr().

* Correct WA for input_offset when using visitorAPI. It shall search all input descriptions for duplicated indexes.

* Apply proper file format.

* Throw exception when input_offset < 0.

* Add more detailed description for input_offset WA.
2021-01-22 14:39:38 +03:00
.ci Azure CI: Add install (#3876) 2021-01-20 14:28:51 +03:00
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cmake Fixed cmake 'message' for multiple arguments (#3901) 2021-01-19 15:35:31 +03:00
docs Revise reduce mean (#3786) 2021-01-22 14:21:39 +03:00
inference-engine Visitor api loop deserialization (#3894) 2021-01-22 14:39:38 +03:00
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model-optimizer [MO] Implement TensorFlow 2 While and Keras RNN support in MO (#3573) 2021-01-21 17:39:57 +03:00
ngraph Visitor api loop deserialization (#3894) 2021-01-22 14:39:38 +03:00
openvino Added CC macros to validate, clone and visit (#3730) 2020-12-25 17:20:48 +03:00
scripts Align location to OMZ demos (#3754) 2021-01-12 17:17:47 +03:00
tests rename time test config (#3923) 2021-01-21 12:32:15 +03:00
tools Adding MYRIAD_THROUGHPUT_STREAMS support (#3723) 2020-12-29 19:02:57 +03:00
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install_build_dependencies.sh [install_dependencies.sh] install latest cmake if current version is lower 3.13 (#2695) 2020-10-16 21:03:46 +03:00
Jenkinsfile [Jenkinsfile] Disable failFast & enable propagateStatus (#3503) 2020-12-10 12:05:03 +03:00
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OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository

Stable release Apache License Version 2.0 Azure DevOps builds (branch)

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.

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