Closed snowzach closed 4 years ago
I figured out what the issue is, I think that it uses cpu=armeabi
but in the tensorflow lite build stuff there is armeabi-v7a
and armv7a
but not targer for armeabi
that includes the neon libraries. I think the easy fix is to change the cross compile stuff to use cpu-armeabi
but I'm not sure what else that breaks.
In next branch have patch for fixes neon issues.
cd tensorflow-on-arm/build_tensorflow/
docker build -t tf-arm-buster -f Dockerfile .
docker run --name tf-arm-buster -it -v /tmp/tensorflow_pkg/:/tmp/tensorflow_pkg/ tf-arm-buster /bin/bash
git checkout next
edit your config file and replace //tensorflow/tools/pip_package:build_pip_package
with //tensorflow/lite:libtensorflowlite.so
and build.
I'm testing edit the rpi.conf file, after build, libtensorflowlite.so
can be found in bazel-bin/tensorflow/lite/libtensorflowlite.so
Yep, that worked! Thanks!
Any other suggestions on how I can use this to build tensorflow lite without having to edit the config files?
This repo works awesome to compile tensorflow but I am also trying to use it to compile tensorflow lite.
Essentially I just edit the config file and replace
//tensorflow/tools/pip_package:build_pip_package
with//tensorflow/lite:libtensorflowlite.so
It actually seems like it compiles fine but it doesn't link properly and errors with a bunch of
undefined reference to
tflite::tensor_utils::NeonYaddaYadda` errors.I found another post related to this https://github.com/tensorflow/tensorflow/issues/25120
I wasn't sure what to edit or if there was another flag I could pass to make it link properly.
Just curious if you or anyone else might have some ideas? I really don't get bazel totally.