Roman Kazantsev b1d1f9287f Implement nGraph transformation to decompose Einsum-7 operation (#5529)
* Implement nGraph transformation to decompose Einsum-7 operation

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Use MatMul instead of Eltwise-multiplication and ReduceSum

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Add description for new methods

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix code style

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix code style #2

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove unused variables.py

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply feedback after review: fix comments, new_register_node use

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Add Reshape if needed and apply code-review feedback

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix code-style

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove unused variable

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
2021-05-18 13:17:50 +03:00
2021-05-17 21:02:56 +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

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*.

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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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Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%