c1b0b03750
* Move Convolution and ConvolutionBackpropData ref impls into separate files. * Add convolution unit tests. * New convolution reference implementation. * Remove unused convolution ref impl argument. * Fix style. * Revert "Remove unused convolution ref impl argument." This reverts commit739065d0d0. * WA for arm-plugin: additional include with ConvolutionBackpropData. * Style format in Convolution SLT CPU instantiation. * Add 1D Convolution SLT CPU tests. * Add Convolution Serialization SLT. * Update source banners with 2021 date. * Specification review. * Readability improvement in padding detection. * Refactoring regarding Tensor usage. * Iteration over tensor slices made more readable. * Code refactored to use only one convolution implementation. 3D convolution is used to compute also in 1D & 2D case (parameters, inputs and filters shapes are adjusted accordingly). * Removed Tensor abstraction. * Name unnamed namespace as convolution_details. * Refactoring: replaced std::next + negative index with std::prev. * Specification refactoring. * Revert "Name unnamed namespace as convolution_details." This reverts commitcea526ec49. * Added new convolution() overload. * Fix legacy convolution() overload (needed for kmb-plugin). * Reduced number of template type arguments in convolution ref impl. * Added 'output' section in Convolution spec. * Remove floating round type configuration.
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*.
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:
- Docs: https://docs.openvinotoolkit.org/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Additional OpenVINO modules: https://github.com/openvinotoolkit/openvino_contrib
- HomePage
- OpenVINO™ Release Notes
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.