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73 lines
2.7 KiB
73 lines
2.7 KiB
#!/bin/bash
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set -e
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source path.sh
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gpus=0,1,2,3
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stage=0
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stop_stage=100
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conf_path=conf/default.yaml
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train_output_path=exp/default
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ckpt_name=snapshot_iter_153.pdz
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add_blank=true
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# with the following command, you can choose the stage range you want to run
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# such as `./run.sh --stage 0 --stop-stage 0`
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# this can not be mixed use with `$1`, `$2` ...
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source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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# prepare data
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./local/preprocess.sh ${conf_path} ${add_blank}|| exit -1
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fi
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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# train model, all `ckpt` under `train_output_path/checkpoints/` dir
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CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${train_output_path} || exit -1
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fi
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1
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fi
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if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
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# synthesize_e2e, vocoder is pwgan
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CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} ${add_blank}|| exit -1
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fi
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if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
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CUDA_VISIBLE_DEVICES=${gpus} ./local/inference.sh ${train_output_path} ${add_blank}|| exit -1
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fi
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# # not ready yet for operator missing in Paddle2ONNX
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# # paddle2onnx, please make sure the static models are in ${train_output_path}/inference first
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# # we have only tested the following models so far
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# if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
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# # install paddle2onnx
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# version=$(echo `pip list |grep "paddle2onnx"` |awk -F" " '{print $2}')
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# if [[ -z "$version" || ${version} != '1.0.0' ]]; then
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# pip install paddle2onnx==1.0.0
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# fi
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# ./local/paddle2onnx.sh ${train_output_path} inference inference_onnx vits_csmsc
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# fi
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# # inference with onnxruntime
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# if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
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# ./local/ort_predict.sh ${train_output_path}
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# fi
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# # not ready yet for operator missing in Paddle-Lite
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# # must run after stage 3 (which stage generated static models)
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# if [ ${stage} -le 7 ] && [ ${stop_stage} -ge 7 ]; then
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# # NOTE by yuantian 2022.11.21: please compile develop version of Paddle-Lite to export and run TTS models,
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# # cause TTS models are supported by https://github.com/PaddlePaddle/Paddle-Lite/pull/9587
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# # and https://github.com/PaddlePaddle/Paddle-Lite/pull/9706
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# ./local/export2lite.sh ${train_output_path} inference pdlite vits_csmsc x86
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# fi
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# if [ ${stage} -le 8 ] && [ ${stop_stage} -ge 8 ]; then
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# CUDA_VISIBLE_DEVICES=${gpus} ./local/lite_predict.sh ${train_output_path} || exit -1
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# fi
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