Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Server terminated abruptly (error code: 14, error message: '', log file: '/home/ramesh/.cache/bazel/_bazel_dlr/d2c1d92543abd40408507a006043a91a/server/jvm.out') #3647

Closed
rameshjes opened this issue Mar 19, 2018 · 10 comments
Assignees
Labels
models:research models that come under research directory type:support

Comments

@rameshjes
Copy link


System information

  • What is the top-level directory of the model you are using: syntaxnet
  • Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Running TensorFlow script
  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Virtual machine Linux Ubuntu 16.04
  • TensorFlow installed from (source or binary): source
  • TensorFlow version (use command below): ('v1.6.0-0-gd2e24b6039', '1.6.0')
  • Bazel version (if compiling from source): 0.5.4
  • CUDA/cuDNN version: Running on CPU
  • GPU model and memory:
  • Exact command to reproduce: bazel test ...
  • Virtual Machine RAM: 4 GB

Describe the problem

I am trying to setup Google syntaxnet by following manual installation steps from this link: https://github.com/tensorflow/models/tree/master/research/syntaxnet
I have installed all the required dependencies, after that I follow these commands

git clone --recursive https://github.com/tensorflow/models.git
  cd models/research/syntaxnet/tensorflow
  ./configure
  cd ..
  bazel test ...

When I execute bazel test..., terminal shows:

INFO: Loading package: @org_tensorflow//third_party/fft2d

Server terminated abruptly (error code: 14, error message: '', log file: '/home/dlr/.cache/bazel/_bazel_dlr/d2c1d92543abd40408507a006043a91a/server/jvm.out')

TensorFlow configuration

(tensor) dlr@ubuntu:~/github/models/research/syntaxnet/tensorflow$ ./configure 
You have bazel 0.5.4 installed.
Please specify the location of python. [Default is /home/dlr/anaconda2/bin/python]: 
Found possible Python library paths:
/home/dlr/anaconda2/lib/python2.7/site-packages
Please input the desired Python library path to use.  Default is /home/dlr/anaconda2/lib/python2.7/site-packages
Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]: Y
jemalloc as malloc support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]: N
No Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [y/N]: N
No Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]: N
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with GDR support? [y/N]: N
No GDR support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]: N
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL support? [y/N]: N
No OpenCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: N
No CUDA support will be enabled for TensorFlow.

Do you wish to build TensorFlow with MPI support? [y/N]: N
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]: 
Add "--config=mkl" to your bazel command to build with MKL support.
Please note that MKL on MacOS or windows is still not supported.
If you would like to use a local MKL instead of downloading, please set the environment variable "TF_MKL_ROOT" every time before build.
Configuration finished


@sujaybabruwad
Copy link

any update on overcoming this error ? @rameshjesswani

@rameshjes rameshjes changed the title Server terminated abruptly (error code: 14, error message: '', log file: '/home/dlr/.cache/bazel/_bazel_dlr/d2c1d92543abd40408507a006043a91a/server/jvm.out') Server terminated abruptly (error code: 14, error message: '', log file: '/home/ramesh/.cache/bazel/_bazel_dlr/d2c1d92543abd40408507a006043a91a/server/jvm.out') Jul 31, 2018
@rameshjes
Copy link
Author

@sujaybabruwad no, I was unable to figure out this problem.

@padoremu
Copy link

I am getting the same error message when running bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package, this time at [9,978 / 13,688]. So far it has been therefore impossible for me to build tensorflow with bazel. I would like to install tf-nightly with pip instead, but it seems to be frozen at tf-nightly-1.15.0.dev20190730, which I don't fully understand with regard to "nightly". Is there any information on this or is there anything else I can do to install an actual nightly version via pip?

@byronyi
Copy link

byronyi commented Apr 7, 2020

@rameshjesswani You run out of memory when building TF from source. Use bazel build -j 4/8/16 //... (pick one from 4/8/16) to manually limit the number of concurrent build jobs and reduce the memory consumption.

@eduamf
Copy link

eduamf commented Jul 8, 2020

I have 22GB of RAM and same error. How to configure the memory consumption?

@ravikyram ravikyram added models:research models that come under research directory type:support labels Jul 10, 2020
@ravikyram ravikyram self-assigned this Jul 10, 2020
@ravikyram
Copy link

@rameshjesswani

Is this still an issue?
Please, close this thread if your issue was resolved.Thanks!

@aryan-f
Copy link

aryan-f commented Jul 24, 2020

This issue is still very much in place. I'm unable to build v2.3 on 16GB of ram. Progressed as far as [24,171 / 27,443] before being terminated.

@josemarfdc
Copy link

I have 32GB of RAM and this is issue is affecting me as well

@aliz64
Copy link

aliz64 commented Aug 12, 2020

same issue. 32gb ram, 12 core CPU, cuda gpu....

NVM. It was because my CPU is 12-core (24 thread) that 32gb was not enough. So just use -j 12 or something and it will work.

@cellcoresystems
Copy link

more RAM or less simultaneous jobs.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
models:research models that come under research directory type:support
Projects
None yet
Development

No branches or pull requests

10 participants