9

I'm trying to install tensorflow 0.11.0 by running 

./configure

I'm getting an error saying :

ERROR: /home/abc/.cache/bazel/_bazel_abc/235fe154e0/server (Directory not empty).

I'm not sure if they are related, but before the error message, I also get a warning saying:

WARNING: Output base '/home/abc/.cache/bazel/_bazel_abc/235fe154e0' is on NFS.     
This may lead to surprising failures and undetermined behavior.

I have no clue what the error message means, but if I try running ./configure right after this error message, I get another message saying:

/home/rkohli1/.cache/bazel/_bazel_rkohli1/235fe154e0a4c7e0c0527cd185fe6b6b/server/
.nfs00000000820050bd00000e9e (Device or resource busy).

At this point, I just tried deleting the entire .cache folder (I had to first kill a process which was preventing me from deleting it). I tried running configure with the --expunge_async flag as well but it doesn't help. It takes me back to the first error message.

Not sure if it's relevant, but I'm trying to install tensorflow with GPU support and use cuda 8.0 and cudNN 5

kerouac
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    This is a bug in Bazel (visibly it has hard time using a .cache on NFS), can you report it to https://github.com/bazelbuild/bazel/issues? – Damien Martin-Guillerez Oct 20 '16 at 08:05
  • Okay, I've raised the issue in bazel : https://github.com/bazelbuild/bazel/issues/1970 I'm hoping someone can suggest a workaround though it there is one, or I would actually have to resort to using another deep learning library in order to be able to use a GPU. Thanks! – kerouac Oct 20 '16 at 19:41
  • You get `Device or resource busy` because bazel seems to continue running. Do `ps aux | grep bazel` and you will see. – Mitar Jan 24 '17 at 04:54

2 Answers2

18

I am not sure if it is correct. After I changed 

bazel clean --expunge

to

bazel clean --expunge_async

in the tensorflow/configure file, the build is successful.

Environments:

  • bazel 0.3.1
  • cuDNN 5
  • Cuda 8.0
user200340
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0

Faced same issue with Bazel 0.4.5 however could resolve by changing bazel clean --expunge to bazel clean --expunge_async in tensorflow/configure file.

Nayana
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