Introduction

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit.

Usage

module load anaconda/4.00py3.5
OR
module load anaconda/4.00py2.7

Installation

module load anaconda/4.00py3.5
conda install tensorflow
python
Python 3.5.4 |Anaconda custom (64-bit)| (default, Aug 14 2017, 13:26:58)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>>

Anaconda with Python 2.7

module load anaconda/4.00py2.7
[root@gowonda2 ~]# conda install tensorflow
Fetching package metadata .........
Solving package specifications: .

Package plan for installation in environment /sw/anaconda/py27-ver400:

The following NEW packages will be INSTALLED:

    backports:              1.0-py27_0
    backports.weakref:      1.0rc1-py27_0
    bleach:                 1.5.0-py27_0
    html5lib:               0.9999999-py27_0
    libprotobuf:            3.4.0-0
    markdown:               2.6.9-py27_0
    mock:                   2.0.0-py27_0
    pbr:                    1.10.0-py27_0
    protobuf:               3.4.0-py27_0
    tensorflow:             1.3.0-0
    tensorflow-base:        1.3.0-py27_0
    tensorflow-tensorboard: 0.1.5-py27_0

The following packages will be UPDATED:

    conda:                  4.3.16-py27_0    --> 4.3.30-py27h6ae6dc7_0
    funcsigs:               0.4-py27_0       --> 1.0.2-py27_0
    werkzeug:               0.11.4-py27_0    --> 0.12.2-py27_0

Proceed ([y]/n)?

Sample pbs script that will work with n060

https://github.com/jcjohnson/pytorch-examples/blob/master/tensor/two_layer_net_tensor.py two_layer_net_tensor.py

 
#!/bin/sh
#PBS -m abe
#PBS -M youremail@griffith.edu.au
#PBS -N myTestRun
#PBS -q dljun
#PBS -l walltime=01:00:00
#PBS -l select=1:ncpus=1:ngpus=1:mem=16g,walltime=1:00:00
source $HOME/.bashrc
cd $PBS_O_WORKDIR
module load cuda/10.0
module load anaconda/5.3.1py3
#source activate tensorflow_gpuenv
source activate tensorflow-gpu
#module list
###source of the sample: https://github.com/jcjohnson/pytorch-examples/blob/master/tensor/two_layer_net_tensor.py
python sample/two_layer_net_tensor.py > output_${PBS_JOBID}.log
echo "Done with job"

Reference

https://github.com/tensorflow/tensorflow