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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
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module load anaconda/4.00py3.5 OR module load anaconda/4.00py2.7 |
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https://github.com/jcjohnson/pytorch-examples/blob/master/tensor/two_layer_net_tensor.py two_layer_net_tensor.py
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#!/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" |
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