Reputation: 807
I'm currently experiencing problems with compiling TensorFlow. It looks like there are problems downloading certain packages, as mentioned here, however the last mention of the bug was in September. What is wrong? I simply cloned the latest r1.5 branch, ran ./configure
and tried to compile. I'm using cuda 9.1 with cudnn 7.
bazel build --config=opt --config=cuda --config=mkl //tensorflow/tools/pip_package:build_pip_package
........
ERROR: /home/mv310/projects/tensorflow/tensorflow/tools/pip_package/BUILD:28:1: no such package 'third_party/eigen3': error globbing [**/*]: /home/mv310/projects/tensorflow/third_party/eigen3/mkl_include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include (Too many levels of symbolic links) and referenced by '//tensorflow/tools/pip_package:included_headers_gather'
ERROR: Analysis of target '//tensorflow/tools/pip_package:build_pip_package' failed; build aborted: no such package 'third_party/eigen3': error globbing [**/*]: /home/mv310/projects/tensorflow/third_party/eigen3/mkl_include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include/include (Too many levels of symbolic links)
INFO: Elapsed time: 10.798s
FAILED: Build did NOT complete successfully (37 packages loaded)
currently loading: tensorflow/core ... (11 packages)
Upvotes: 0
Views: 805
Reputation: 861
I was working in the models project. My issue was a leftover directory from a previous install. Deleting the directory and doing a fresh clone helped.
rm -r -f models/research/syntaxnet/tensorflow
git pull --recurse
cd tensorflow
./configure
In the tensorflow directory, I think you can also stash your changes and do a hard reset too.
git stash
git reset --hard HEAD
Finally, if all else fails, clean your bazel cache
rm -r -f ~/.cache/bazel/*
Upvotes: 0