9ca5fbaf02
* Removed shape inference fr IR v7 and older * Disabled dynamic batch tests which require reshape * Fixes tests 2 * Disabled MKLDNN tests with convolution reshape * Fixed GPU tests * Disable VPU tests with batch size > 1 for old IRs * Removed most of shape infer functions for old representation * Removed most of CNNLayer validators * Fixed validators and keep only parseParams * Removed tests on invalid IR v7 * Disabled more VPU tests * Removed Backetize validator * Disable one more Myriad tests case where reshape for old IR is needed * Removed useless reshape * Need to replace GRUCell with Unique * Moved shape infer functions for experimental layers to Core IE * Fixed shape inference functions not to depend on legacy * Added missed SparseToDense * Added descriptive error message * Fixed comments |
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| cmake | ||
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| inference-engine | ||
| model-optimizer | ||
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| openvino | ||
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| tests | ||
| tools | ||
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| azure-pipelines.yml | ||
| build-instruction.md | ||
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| get-started-linux.md | ||
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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 contribution to the code. See CONTRIBUTING_DOCS for contribution to the documentation. 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.