# Generate decompositions
ST=0.0
LP=1.0
BEAM=5
SEED=0
# Point to model directory (change the final directory number/string/id below to match the directory string from the previous Unsupervised Seq2Seq training command)
MODEL_DIR=dumped/umt.dev1.pseudo_decomp.replace_entity_by_type/20639223
MODEL_NO="$(echo $MODEL_DIR | rev | cut -d/ -f1 | rev)"
for SPLIT in valid train; do
    # Note: Decrease batch size below if GPU goes out of memory
    cat data/umt/all/processed/$SPLIT.mh | python translate.py --exp_name translate --src_lang mh --tgt_lang sh --model_path $MODEL_DIR/best-valid_mh-sh-mh_mt_effective_goods_back_bleu.pth --output_path $MODEL_DIR/$SPLIT.pred.bleu.sh --batch_size 48 --beam_size $BEAM --length_penalty $LP --sample_temperature $ST
done