3a36d90c11
* Moving PWL to ngraph * improving the running time of php_search; refactoring the pwl operation * fixed erros & refactored code * moved PWL op to GNA * Update src/plugins/intel_gna/ops/pwl.hpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * Update src/plugins/intel_gna/ops/reference/pwl.hpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * Update src/plugins/intel_gna/ops/pwl.cpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * Update src/plugins/intel_gna/transformations/transpose_to_pwl.hpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * Update src/plugins/intel_gna/transformations/transpose_to_pwl.cpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * fixed compilation error * Update inference-engine/tests/unit/gna/ngraph/transformations/gna_pwl.cpp Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> * added some tests; changed algorithm of checking accuracy of pwl; refactoring * added first and last segments; added fq and fixed errors * fixed after review & rewrote some tests on ngraph * removed debug logs & fixed code style check error * s/ngraph_helper/ngraph_util * removed TRANSFORMATIONS_API in PWLApproximation class declaration * removed OPENVINO_API in Pwl class declaration * replaced the deprecated version of evaluate() with a new one * fixed some problems after reviewing * fixed a problem when a value of function of left point of segment is less than minimum of function * corrected a value of the right point of last segments * [GNA] Moved pwl func tests * Deleted deprecated test * s/OPENVINO_RTTI/OPENVINO_OP * Deleted conflicted test file * fixed after review Co-authored-by: Dmitrii Khurtin <dmitrii.khurtin@intel.com> Co-authored-by: Elizaveta Lobanova <elizaveta.lobanova@intel.com> |
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OpenVINO™ Toolkit
This toolkit allows developers to deploy pre-trained deep learning models through a high-level OpenVINO™ Runtime C++ and Python APIs integrated with application logic.
This open source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, 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 TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi.
Repository components
License
OpenVINO™ 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.openvino.ai/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ toolkit modules: https://github.com/openvinotoolkit/openvino_contrib
- Intel® Distribution of OpenVINO™ toolkit Product Page
- Intel® Distribution of OpenVINO™ toolkit 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.