LuweiZhou c483cdced6 Revise swish (#5983)
* Update Swish OP description.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Use RTTI to declare/define NGraph Swish OP.
Add input element type check when constructing Swish OP.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Add Swish into activation serialization test list.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Add Swish into IE CPU plugin activation single layer test suit.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Add Swish NGraph backend and visitor API tests.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Add Swish unsupported parameter data type test cases.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>

* Update the Swish OP visistor API to use typed test.

Signed-off-by: Luwei Zhou <luwei.zhou@intel.com>
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OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state 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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C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%