OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Roman Vyunov (Intel) 7796b0f277
[IE][VPU]: Customer model compilation error - fix(#1901)
Fix of 36693 issue. 

* Problem: One of the concat inputs is a constant. Adjust_data_layout pass tries to duplicate all inputs that do not meet the strides requirements, and then copy from the original input to the duplicate with strides. But duplicateData with an argument in the form of a constant also creates a constant, and then, when Copy, an error appears, the presence of a constant output, which cannot be.
* Solution: In addConvertedData create an intermediate date with the same description as the constant, and then copy the constant data into it with the required strides.

Co-authored-by: DariaMityagina <daria.mityagina@intel.com>
2020-09-01 13:03:31 +03:00
.ci/openvino-onnx Removed NGRAPH_IE_ENABLE flag because it is always ON if unit tests are enabled (#2003) 2020-09-01 06:03:59 +03:00
.github Update issue templates 2020-08-12 13:17:34 +03:00
cmake Simplified plugin interfaces (#1745) 2020-08-14 12:11:54 +03:00
docs Intepolate-4 nGraph operation (#1412) 2020-09-01 06:57:34 +03:00
inference-engine [IE][VPU]: Customer model compilation error - fix(#1901) 2020-09-01 13:03:31 +03:00
model-optimizer [MO] Fix when Crop asks for MXNet specific cmdarg enable_ssd_gluoncv (#1978) 2020-08-31 18:06:13 +03:00
ngraph [CPU] CTCLoss operation implementation. (#1482) 2020-09-01 12:52:31 +03:00
openvino Add static library with nGraph reference implementations (#1810) 2020-08-17 19:43:11 +03:00
scripts Fix the case when run stage of verification scripts failed on Windows 10 due to different build directory for executables (#1478) 2020-08-27 23:58:16 +03:00
tests [Stress] Define --timeout in run_memcheck.py used in gtest-parallel (#1576) 2020-08-05 12:33:01 +03:00
tools Adds first inference time measurements in benchmark_app (#1487) 2020-07-27 16:45:07 +03:00
.gitattributes Doc Migration (master) (#1377) 2020-07-20 17:36:08 +03:00
.gitignore publish master branch snapshot, revision 8d31237e2c3f673cbb0f0ba110fc10f5cce1d2bb 2020-05-22 02:23:12 +03:00
.gitmodules add submodules for mkl-dnn, gflags and gtest 2020-05-21 23:00:55 +03:00
azure-pipelines.yml Azure CI: Enable all MklDnnFunctionalTests (#1881) 2020-08-20 20:53:01 +03:00
build-instruction.md Add python executable for RPI compilation Docker (#1530) 2020-08-10 23:10:46 +03:00
CMakeLists.txt Removed NGRAPH_IE_ENABLE flag because it is always ON if unit tests are enabled (#2003) 2020-09-01 06:03:59 +03:00
CODEOWNERS CODEOWNERS: Add .ci & docs 2020-07-17 15:07:58 +03:00
CONTRIBUTING_DOCS.md docs contribution guides (#1535) 2020-08-07 15:33:11 +03:00
CONTRIBUTING.md Create CONTRIBUTING.md 2020-05-19 19:04:27 +03:00
get-started-linux.md Separate MO configuration for TensorFlow 2 model conversion (#1685) 2020-08-11 18:02:05 +03:00
install_dependencies.sh [Docs] Fixes in readme files: (#750) 2020-06-03 20:14:35 +03:00
Jenkinsfile [Jenkinsfile] Add failFast parameter (#721) 2020-06-02 20:22:25 +03:00
LICENSE Publishing R3 2018-10-16 13:45:03 +03:00
README.md docs contribution guides (#1535) 2020-08-07 15:33:11 +03:00

OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository

Stable release Apache License Version 2.0

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 two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU 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.

Documentation

How to Contribute

See CONTRIBUTING for contribution to the code. See CONTRIBUTING_DOCS for contribution to the documentation. Thank you!

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