You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
69 lines
2.7 KiB
69 lines
2.7 KiB
#!/bin/bash
|
|
|
|
set -e
|
|
source path.sh
|
|
|
|
gpus=0,1
|
|
stage=0
|
|
stop_stage=100
|
|
|
|
conf_path=conf/default.yaml
|
|
train_output_path=exp/default
|
|
ckpt_name=snapshot_iter_201.pdz
|
|
|
|
# with the following command, you can choose the stage range you want to run
|
|
# such as `./run.sh --stage 0 --stop-stage 0`
|
|
# this can not be mixed use with `$1`, `$2` ...
|
|
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
|
|
|
|
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
|
# prepare data
|
|
./local/preprocess.sh ${conf_path} || exit -1
|
|
fi
|
|
|
|
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
|
|
# train model, all `ckpt` under `train_output_path/checkpoints/` dir
|
|
CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${train_output_path} || exit -1
|
|
fi
|
|
|
|
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
|
|
# synthesize, vocoder is pwgan by default
|
|
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
|
|
fi
|
|
|
|
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
|
|
# synthesize_e2e, vocoder is pwgan by default
|
|
CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
|
|
fi
|
|
|
|
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
|
|
# inference with static model, vocoder is pwgan by default
|
|
CUDA_VISIBLE_DEVICES=${gpus} ./local/inference.sh ${train_output_path} || exit -1
|
|
fi
|
|
|
|
# paddle2onnx, please make sure the static models are in ${train_output_path}/inference first
|
|
# we have only tested the following models so far
|
|
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
|
|
# install paddle2onnx
|
|
pip install paddle2onnx --upgrade
|
|
./local/paddle2onnx.sh ${train_output_path} inference inference_onnx fastspeech2_ljspeech
|
|
# considering the balance between speed and quality, we recommend that you use hifigan as vocoder
|
|
./local/paddle2onnx.sh ${train_output_path} inference inference_onnx pwgan_ljspeech
|
|
# ./local/paddle2onnx.sh ${train_output_path} inference inference_onnx hifigan_ljspeech
|
|
fi
|
|
|
|
# inference with onnxruntime, use fastspeech2 + pwgan by default
|
|
if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
|
|
./local/ort_predict.sh ${train_output_path}
|
|
fi
|
|
|
|
# must run after stage 3 (which stage generated static models)
|
|
if [ ${stage} -le 7 ] && [ ${stop_stage} -ge 7 ]; then
|
|
./local/export2lite.sh ${train_output_path} inference pdlite fastspeech2_ljspeech x86
|
|
./local/export2lite.sh ${train_output_path} inference pdlite pwgan_ljspeech x86
|
|
# ./local/export2lite.sh ${train_output_path} inference pdlite hifigan_ljspeech x86
|
|
fi
|
|
|
|
if [ ${stage} -le 8 ] && [ ${stop_stage} -ge 8 ]; then
|
|
CUDA_VISIBLE_DEVICES=${gpus} ./local/lite_predict.sh ${train_output_path} || exit -1
|
|
fi |