29a8be523d
* [cldnn] Add initial fused conv eltw POC - Add cldnn unit test - Add fused dependency list to the fused_primitive_desc - fuse_nodes update for saving fusing history and depenecies - Modify Jitter to create jit constants using fused dependencies - Add cldnn unit-test cases for multiple serial and parallel eltwise fuse pattern - Modify Jitter and add default values in sum input Signed-off-by: Ahn, Paul Y <paul.y.ahn@intel.com> Co-authored-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com> * [cldnn] Update fused_conv_eltwise cldnn unit test - Add execute and compare function - Add cldnn unit-test case for multiple parallel eltwise and additional eltwise - Add cldnn unit-test case for combination of multiple parallel eltw - Add cldnn unit-test cases for serial and diverged quantize and eltwise Signed-off-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com> * [cldnn] Modify checking fusibility of eltwise fusing - Add new checking fusibility rule in prepare_primitive_fusing - Move cldnn eltwise fusing test to fusing_gpu_test.cpp - Modify method to get input var name in jitter Signed-off-by: Ahn, Paul Y <paul.y.ahn@intel.com> * [cldnn] Fix fusing item type and activation fusibility checking condition - Extract input_data_supports_fusings from fuse_activaion_f - Fix checking supported mode bug Co-authored-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com> |
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OpenVINO™ Toolkit
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
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ 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.