Closed decarlof closed 5 years ago
Hi,
yes, that is the case. You could also follow the Tensorflow guide and create the operations separately from Tensorflow, but then you have to match all versions of CUDA, CUDNN, GCC, etc. which are used for the Tensorflow package in the pip repositories. Creating Tensorflow from the sources avoids this problem, so we decided to connect directly to the build process of Tensorflow.
Currently, our patch only works to build on Linux systems. A pre-built binary for Ubuntu with Cuda 10 and CUDNN 7.2 is uploaded to the pyronn_layers repository. We plan to support the Windows build in the near future.
thanks a lot, this address my question, will do.
I followed your installation instruction but when running the example:
I looked into installing pyronn_layers from here but this requires to rebuild Tensorflow and then patch the Tensorflow build process such that all C++ and CUDA files in the pyronn_layers folder are compiled and made available under the pyronn_layers namespace at the python level.
Am I on the right path?