Roman Kazantsev 8e327bd2ff [MO, TF] Support Custom Wide and Deep CTR model by MO (#8505)
* [MO, TF] Support Custom Wide and Deep CTR model by MO

It implements implicit support of EmbeddingSegmentsMean operation through decomposition.
Also, this extends the current transformation to fuse TensorFlow sub-graph (for Wide and Deep model family)
containing SparseSegmentSum and SparseSegmentMean operations into EmbeddingSegmentsSum or EmbeddingSegmentsMean.

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

* Fix unit-tests after modifications of SparseToDense and EmbeddingSegmentsOperationFusing

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

* Document SparseSegmentMean support

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

* Add computation scheme for normalization coeffs and correct documentation

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
2021-11-17 11:44:04 +03:00
2021-11-17 01:22:04 +03:00
2021-11-17 01:22:04 +03:00
2021-11-17 01:22:04 +03:00
2021-11-17 01:22:04 +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*.

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.

Resources:

Support

Please report questions, issues and suggestions using:


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

Languages
C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%