Gladilov, Gleb 1f707610d6 [IE][nGraph][VPU]: Enables DTS for Loop (#3838)
* [IE][nGraph]: Enables const overload for SubGraphOp::get_function
* [IE][nGraph]: Deletes SubGraphOp copy constructor

SubGraphOp has clone_with_new_inputs function for
deep coping, while default copy constructor does
some kind of shallow one. In order to avoid
confusion, copy constructor is deleted since it's
unused anyway.

* [IE][nGraph]: Enables protected Loop copy constructor

Additional clone method is introduced in order to reuse
Loop::clone_with_new_inputs implementation.
Loop::clone_with_new_inputs implementation at the same
time is refactored, since there were extra job that
does not needed to be done there.

* [IE][VPU][nGraph]: Introduces StaticShapeLoop

StaticShapeLoop is a class derived from Loop
to override validate_and_infer_types method
in order to propagate upper-bounds through the
function instead of dynamic tensors.

It uses maximum_value estimation to get
upper-bound for iterations count in case if
it is dynamic.

* [IE][VPU][nGraph]: Refactors function validators in DTS

The same approach (nGraph operation to functor map) as
for DTS shape functors is used since validation is
operation type specific.

* [IE][VPU][nGraph]: Enables DTS for Loop

Only loops with inputs dynamic in batch
(iterations count) and static body are supported.
2021-02-02 13:06:34 +03:00
2020-11-19 13:59:20 +03:00
2020-07-20 17:36:08 +03:00
2018-10-16 13:45:03 +03:00
2020-11-17 16:44:44 +03:00

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*.

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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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