Katarzyna Mitrus c171be238f Slice-8 to StridedSlice transformation (#8295)
* SliceToStridedSlice transformation

* Slice SLT

* ONNX import

* Disable throw

* Add Slice evaluate, re-enable mkldnn graph throw

* Use ScatterUpdate instead of Gather to adjust indices

* Add CmpValues::CONST_VALUES to Slice transformation tests

* Apply smaller review comments

* Adjust indices lenght type

* Use ov namespace

* Refactor indices alignment function

* Move SliceToStridedSlice transformation to separate file

* Style alignment

* Resolve xfails

* Update tests and remove redundant const folding

* Remove evaluate and onnx changes

* Add use_shapes switch to the Slice transformation

* Style fix
2021-11-16 22:40:34 +03:00
2021-11-16 06:48:02 +03:00
2021-11-15 12:53:07 +03:00
2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +03:00
2020-11-17 16:44:44 +03:00

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*.

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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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