Difference between revisions of "Infrastructure/software/tensorflow"
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<pre> | <pre> | ||
| − | module load nlpl- | + | module load nlpl-tensorflow/1.11 |
pip install --upgrade pip | pip install --upgrade pip | ||
| − | pip install --upgrade | + | pip install --upgrade $(pip list | tail -n +3 | awk '{print $1}') |
| − | pip | ||
</pre> | </pre> | ||
<pre> | <pre> | ||
| − | + | qlogin --account=nn9106k --time=6:00:00 --nodes=1 --ntasks-per-node=1 --partition=accel --gres=gpu:1 | |
| − | + | module purge | |
| − | + | module use -a /projects/nlpl/software/modulefiles | |
| + | module load nlpl-tensorflow | ||
</pre> | </pre> | ||
Revision as of 14:56, 19 September 2018
Background
TensorFlow is one of the most widely used Deep Learning frameworks in NLP (in mid-2018, at least), with corporate support from Google.
Installation on Abel
The module nlpl-pytorch provides a PyTorch installation in a Python 3.5 virtual environment.
module purge module load gcc/4.9.2 cuda/8.0 module load python3/3.5.0
cd /projects/nlpl/software mkdir tensorflow virtualenv tensorflow/1.11
First things first: Enable use of our custom (more modern) GNU C Library installation, by wrapping the basic python binary:
mv /projects/nlpl/software/tensorflow/1.11/bin/{,.}python3.5
sed 's@pytorch/0.4.1@tensorflow/1.11@' \
/projects/nlpl/software/pytorch/0.4.1/bin/python3.5 \
> /projects/nlpl/software/tensorflow/1.11/bin/python3.5
chmod 755 /projects/nlpl/software/tensorflow/1.11/bin/python3.5
Next, create a module definition, in this case /projects/nlpl/software/modulefiles/nlpl-tensorflow/1.11.
module load nlpl-tensorflow/1.11
pip install --upgrade pip
pip install --upgrade $(pip list | tail -n +3 | awk '{print $1}')
qlogin --account=nn9106k --time=6:00:00 --nodes=1 --ntasks-per-node=1 --partition=accel --gres=gpu:1 module purge module use -a /projects/nlpl/software/modulefiles module load nlpl-tensorflow
