⚠️ Source code will be continued to be supported and developed in OpenVINO contrib. Thanks for all who used.

Repository with guides to enable some layers from PyTorch in Intel OpenVINO:

CI

• nn.MaxUnpool2d
• torch.fft
• nn.functional.grid_sample
• torchvision.ops.DeformConv2d
• SparseConv from Open3D

To create OpenVINO IR, use extra --extension flag to specify a path to Model Optimizer extensions that perform graph transformations and register custom layers.

mo --input_model model.onnx --extension openvino_pytorch_layers/mo_extensions

You also need to build CPU extensions library which actually has C++ layers implementations:

source /opt/intel/openvino_2022/setupvars.sh
cd user_ie_extensions
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release && make -j$(nproc --all)

Add compiled extensions library to your project:

from openvino.runtime import Core
core = Core()
core.add_extension('user_ie_extensions/build/libuser_cpu_extension.so')
model = ie.read_model('model.xml')
compiled_model = ie.compile_model(model, 'CPU')