OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Eugeny Volosenkov 6f512142b6
Re-implement onnx old-style extractors with extractor extensions (#3459)
* add class ConcatFrontExtractor for onnx

* add class ConcatFrontExtractor for onnx

* Delete concat from mo/front/onnx/extractor.py

* Add identity, reshape extractors classes for onnx

* import FrontExtractorOp

* Added BatchNormalizationExtractor

* Added extra line

* Fix import modules

* fix caffe bn.py and bn_test.py

* Fix BatchNormInference

* Modify convert_batch_norm

* Modify convert_batch_norm

* Modify bn_test.py

* Fix old comments BN->batchNormInference
2020-12-10 09:24:24 +03:00
.ci Template device testing (#3521) 2020-12-09 17:13:32 +03:00
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inference-engine Template device testing (#3521) 2020-12-09 17:13:32 +03:00
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model-optimizer Re-implement onnx old-style extractors with extractor extensions (#3459) 2020-12-10 09:24:24 +03:00
ngraph [ONNX] Set defaults in LSTMSequence even if dimensions are dynamic (#3491) 2020-12-08 14:53:24 +01:00
openvino CPU plugin selective build (#3360) 2020-12-07 17:49:08 +03:00
scripts setupvars should export TBB_DIR (44241) (#3434) 2020-12-02 14:18:59 +03:00
tests Build time_tests with OpenVINO install (#3484) 2020-12-07 12:56:37 +03:00
tools benchmark_tool: replace logger.warn with logger.warning (#3291) 2020-11-24 06:19:29 +03:00
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install_build_dependencies.sh [install_dependencies.sh] install latest cmake if current version is lower 3.13 (#2695) 2020-10-16 21:03:46 +03:00
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OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository

Stable release Apache License Version 2.0 Azure DevOps builds (branch)

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.

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* Other names and brands may be claimed as the property of others.