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* Add NGRAPH_EVALUATE_ENABLE flag and disable all reference implementations * Enable some evaluate methods * Added dynamic library with reference implementations * Fixed tests * Enabled unsqueeze CF * Removed nGraph test library * Disable all nGraph tests to check * Enable some reference implementations * Added debug message * EVALUATE true * Revert "Disable all nGraph tests to check" This reverts commit 38bca3ed3dfed029e892fe609ea7e48c5cfadb67. * Enable some implementations * Removed some TYPE_CASE reference implementations * Fixed reshape * Revert types for Broadcast and Add * Disabled failing gpu_engine.user_context test * Disabled failed nGraph tests * Add u8 for non_zero * Revert "Added debug message" This reverts commit 4b9f4894f5ae9963426830ac5e5eb833af8847aa. * Revert "Enable some reference implementations" This reverts commit d2001a636df7504e0ad5abe5c98725ef0be07379. Revert "Enabled unsqueeze CF" This reverts commit 814a8e52cb2b673446d24e54ed11af1dd3d80fad. Revert "Enable some evaluate methods" This reverts commit 73767b8942d857bf60317f29120c98c528344a04. * Revert "Add NGRAPH_EVALUATE_ENABLE flag and disable all reference implementations" This reverts commit cfaa7d7e7bf34b617f53a556d24fea2189372592.
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 two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU 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.
Documentation
- OpenVINO™ Release Notes
- OpenVINO™ Inference Engine Build Instructions
- Get Started with Deep Learning Deployment Toolkit on Linux*
- Introduction to Deep Learning Deployment Toolkit
- Inference Engine Developer Guide
- Model Optimizer Developer Guide
How to Contribute
See CONTRIBUTING for details. Thank you!
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.