42 lines
1.2 KiB
Bash
42 lines
1.2 KiB
Bash
|
#!/usr/bin/env bash
|
||
|
|
|
||
|
|
set -e
|
||
|
|
set -x
|
||
|
|
SRCDIR=`dirname $0`
|
||
|
|
|
||
|
|
# functional tests
|
||
|
|
|
||
|
|
function on_error {
|
||
|
|
rm -fr $workdir
|
||
|
|
}
|
||
|
|
|
||
|
|
mkdir -p $SRCDIR/embeddings
|
||
|
|
|
||
|
|
for v in glove.6B.50d charNgram ; do
|
||
|
|
for f in vectors itos table ; do
|
||
|
|
wget -c "https://parmesan.stanford.edu/glove/${v}.txt.${f}.npy" -O $SRCDIR/embeddings/${v}.txt.${f}.npy
|
||
|
|
done
|
||
|
|
done
|
||
|
|
|
||
|
|
TMPDIR=`pwd`
|
||
|
|
workdir=`mktemp -d $TMPDIR/decaNLP-tests-XXXXXX`
|
||
|
|
trap on_error ERR INT TERM
|
||
|
|
|
||
|
|
i=0
|
||
|
|
for hparams in "" "--use_curriculum"; do
|
||
|
|
|
||
|
|
# train
|
||
|
|
pipenv run python3 -m decanlp train --train_tasks almond --train_iterations 4 --preserve_case --save_every 2 --log_every 2 --val_every 2 --save $workdir/model_$i --data $SRCDIR/dataset/ $hparams --exist_ok --skip_cache --root "" --embeddings $SRCDIR/embeddings --small_glove --no_commit
|
||
|
|
|
||
|
|
# greedy decode
|
||
|
|
pipenv run python3 -m decanlp predict --tasks almond --evaluate test --path $workdir/model_$i --overwrite --eval_dir $workdir/model_$i/eval_results/ --data $SRCDIR/dataset/ --embeddings $SRCDIR/embeddings
|
||
|
|
|
||
|
|
# check if result files exist
|
||
|
|
if test ! -f $workdir/model_$i/eval_results/test/almond.tsv ; then
|
||
|
|
echo "File not found!"
|
||
|
|
exit
|
||
|
|
fi
|
||
|
|
|
||
|
|
i=$((i+1))
|
||
|
|
done
|