add molnet script

#!/usr/bin/env bash

envname=`cat /dev/urandom | tr -dc 'a-zA-Z0-9' | fold -w 16 | head -n 1`

sed -i -- 's/tensorflow$/tensorflow-gpu/g' scripts/install_deepchem_conda.sh

bash scripts/install_deepchem_conda.sh $envname

source activate $envname

python setup.py install

rm examples/results.csv || true

export DEEPCHEM_DATA_DIR='/tmp/molnet_'$envname

mkdir $DEEPCHEM_DATA_DIR

cd examples

python benchmark.py -d tox21 -m weave -m graphconv -m tf_robust -m tf -m irv -m xgb -m logreg -m textcnn -s random --seed 123

python benchmark.py -d clintox -m weave -m graphconv -m tf -m tf_robust -m irv -m xgb -m logreg -m textcnn -s random --seed 123

python benchmark.py -d sider -m weave -m graphconv -m tf -m tf_robust -m irv -m xgb -m logreg -m textcnn -s random --seed 123

python benchmark.py -d bbbp -m weave -m graphconv -m tf -m irv -m xgb -m logreg -m textcnn -s scaffold --seed 123

python benchmark.py -d hiv -m weave -m graphconv -m tf -m irv -m logreg -m xgb -m textcnn -s scaffold --seed 123

python benchmark.py -d muv -m weave -m graphconv -m tf -m tf_robust -m irv -m logreg -m xgb -s random --seed 123

python benchmark.py -d bace -m weave -m graphconv -m tf -m irv -m logreg -m xgb -m textcnn -s scaffold --seed 123

python benchmark.py -d delaney -m weave_regression -m graphconvreg -m tf_regression -m xgb_regression -m textcnn_regression -m krr -m dag_regression -m mpnn -s random --seed 123

python benchmark.py -d sampl -m weave_regression -m graphconvreg -m tf_regression -m xgb_regression -m textcnn_regression -m krr -m dag_regression -m mpnn -s random --seed 123

python benchmark.py -d lipo -m weave_regression -m graphconvreg -m tf_regression -m xgb_regression -m textcnn_regression -m krr -m dag_regression -m mpnn -s random --seed 123

python benchmark.py -d qm7 -m dtnn -m graphconvreg -m tf_regression_ft -m krr_ft -s stratified --seed 123

python benchmark.py -d qm7b -m dtnn -m tf_regression_ft -m krr_ft -s random --seed 123

python benchmark.py -d qm8 -m dtnn -m mpnn -m graphconvreg -m tf_regression -m tf_regression_ft -s random --seed 123

python benchmark.py -d qm9 -m dtnn -m graphconvreg -m tf_regression -m tf_regression_ft -s random --seed 123

cd ..

nosetests -v devtools/jenkins/compare_results.py --with-xunit || true

export retval2=$?

source deactivate

conda remove --name $envname --all