Gladilov, Gleb
79fa676e35
LCA (Least Common Ancestor) search procedure must take sub-graph without external connections to be able to count depths of nodes. Previously, just 2 steps of removing external connections were executed (1 time for top sub-graph and 1 time for bottom one). In case if originally top sub-graph had no external connections, but bottom one had, after removing external nodes from bottom sub-graph, some of the nodes from top sub-graph could became external. In order to prevent that, removing external connections must always be a loop until no external connections found in both top and bottom sub-graphs. Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
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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