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PaddleSpeech/examples/mustc/st1/run.sh

41 lines
1.1 KiB

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#!/bin/bash
set -e
. ./path.sh || exit 1;
. ./cmd.sh || exit 1;
gpus=0,1,2,3
stage=0
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stop_stage=3
conf_path=conf/transformer_es.yaml
ips= #xx.xx.xx.xx,xx.xx.xx.xx
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decode_conf_path=conf/tuning/decode.yaml
must_c_path=
lang=es
avg_num=5
ckpt_path= # (finetune from FAT-ST or ASR pretrained model)
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
avg_ckpt=avg_${avg_num}
ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}')
echo "checkpoint name ${ckpt}"
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
# prepare data
bash ./local/data.sh --tgt_lang ${lang} --must_c ${must_c_path} || exit -1
fi
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
# train model, all `ckpt` under `exp` dir
CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${ckpt} "${ckpt_path}" ${ips}
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fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
# avg n best model
avg.sh best exp/${ckpt}/checkpoints ${avg_num}
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
# test ckpt avg_n
CUDA_VISIBLE_DEVICES=0 ./local/test.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} ${lang} || exit -1
fi