Skip to content

Latest commit

 

History

History
44 lines (29 loc) · 1.37 KB

build_from_source.md

File metadata and controls

44 lines (29 loc) · 1.37 KB
Raw

Build RECom from source

We highly recommend building RECom in the docker nvidia/cuda:11.3.1-cudnn8-devel-ubuntu18.04, as the compatibility of RECom has not been checked yet.

You should prepare the following environments before building RECom:

  • Python 3.8
  • TensorFlow 2.6.2
  • Bazel 4.2.1 (bazelisk is recommended)

You should also download the libgmp-dev, which is required by SymEngine:

apt-get install libgmp-dev

After preparing the environments, you should set some environment variables and run the configure.py to generate the .bazelrc:

export TF_NEED_CUDA="1"

# Set these if the below defaults are different on your system
export TF_CUDA_VERSION="11"
export TF_CUDNN_VERSION="8"
export CUDA_TOOLKIT_PATH="/usr/local/cuda"
export CUDNN_INSTALL_PATH="/usr/lib/x86_64-linux-gnu"

python ./configure.py

Then, you can start building the shared library of RECom:

bazel build //tensorflow_addons:librecom.so

Finally, you will find the target librecom.so in bazel-bin/tensorflow_addons.

Usage

You can use tf.load_op_library/TF_LoadLibrary in your Python/C++ inference scripts to load the TensorFlow addon of RECom without modifying any source codes of the models. Then, the models will be optimized automatically (warm-up required).

More details can be found in RECom examples.