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lfs: 'true' | ||
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- name: Install apt-get dependencies | ||
uses: awalsh128/[email protected].0 | ||
uses: awalsh128/[email protected].1 | ||
with: | ||
packages: graphviz texlive liblua5.2-0 libclang1-9 libclang-cpp9 | ||
version: 3.0 | ||
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@@ -30,7 +30,7 @@ jobs: | |
submodules: 'true' | ||
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- name: Install OpenCL | ||
uses: awalsh128/[email protected].0 | ||
uses: awalsh128/[email protected].1 | ||
if: runner.os == 'Linux' | ||
with: | ||
packages: ocl-icd-opencl-dev opencl-headers | ||
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* Sun Jul 4 12:00:00 2010 OpenVINO Developers <[email protected]> - 2022.3.0-1 | ||
* Sun Dec 25 2022 OpenVINO Developers <[email protected]> - 2022.3.0-1 | ||
- Implemented Debian, RPM packages support | ||
- Support of Ubuntu 22.04 | ||
- Support of python 3.10 | ||
- Introduced OpenVINO Runtime 2.0 C API | ||
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* Thu Jul 28 12:00:00 2022 OpenVINO Developers <[email protected]> - 2022.2.0-1 | ||
* Thu Jul 28 2022 OpenVINO Developers <[email protected]> - 2022.2.0-1 | ||
- Broader model and hardware support - Optimize & deploy with ease across an expanded range of deep learning models including NLP, and access AI acceleration across an expanded range of hardware. | ||
- NEW: Support for Intel 13th Gen Core Processor for desktop (code named Raptor Lake). | ||
- NEW: Preview support for Intel’s discrete graphics cards, Intel® Data Center GPU Flex Series and Intel® Arc™ GPU for DL inferencing workloads in intelligent cloud, edge and media analytics workloads. Hundreds of models enabled. | ||
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- NEW: Introducing new performance hint (”Cumulative throughput”) in AUTO device, enabling multiple accelerators (e.g. multiple GPUs) to be used at once to maximize inferencing performance. | ||
- NEW: Introducing Intel® FPGA AI Suite support which enables real-time, low-latency, and low-power deep learning inference in this easy-to-use package | ||
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* Thu Mar 22 12:00:00 2022 OpenVINO Developers <[email protected]> - 2022.1.0-1 | ||
* Thu Mar 22 2022 OpenVINO Developers <[email protected]> - 2022.1.0-1 | ||
- Implemented OpenVINO 2.0 Runtime API for both C++ and Python | ||
- Introduced IR v11 which is aligned with frameworks model format |
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