This repository includes machine learning kernels for Vector Engine and its wrapper for TensorFlow for SX-Aurora.
Prerequisites
- ncc/nc++
- llvm-ve
- vednn
build
build veorun_tf for TensorFlow-VE
% ./scripts/build-release-veorun_tf.sh build
build with prebuilt vednn in extra/vednn directory
% mkdir build
% (cd build && cmake3 -DUSE_PREBUILT_VEDNN=ON .. && make)
build vednn and vetfkernel
% git clone <vednn> libs/vednn
% mkdir build
% (cd build && cmake3 .. && make)
test
% (cd build && ctest3)
% ./build/bench/bench --validation-only
% python test/python/avgpoolgrad.py
or
% ./test.sh [BUILD_DIR]
Then, run perf test
% python perf.py [-e <BUILD_DIR>/bench/bench] -d perfdb/10BE test
See here for details.
profiler
- cmake with -DUSE_PROFILE=ON
- run with VML_PROFILE=conv2d,conv2d_backprop_input
VML API Document
The document is generated into doc/api
directory.
% doxygen
See in your browser. If you need http server, try
% python3 -m http.server