OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Gabriele Galiero Casay 6888ffa328
Revise Reference Implementation of Range op (#3409)
* Range: Align operator with spec and add unit tests

* Range: Remove output shape from range ref impl signature

* Range: Exclude backend unit tests for CPU and GPU due to unsupported dynamic ops

* Range: Add single layer test class for Range-4

* Range: Add unit test for shape inference

* Range: Add unit tests for i32 and f32

* Range: Refactor Range v0 backend test and added test for f32 type

* Range: Add floating point tolerance in unit tests to avoid failures due to precision

* Range: Add subgraph tests for Range add element-wise

* Range: Refactor Range class for single layer tests and add range add element-wise test with truncated inputs
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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.