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

Created on 19 Mar 2018 · 10Comments · Source: tensorflow/models

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

research support

Source

rameshjes

Most helpful comment

@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.

byronyi on 8 Apr 2020

👍3

All 10 comments

any update on overcoming this error ? @rameshjesswani

sujaybabruwad on 31 Jul 2018

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

rameshjes on 31 Jul 2018

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?