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PaddleSpeech/examples/csmsc/tts3/local/ort_predict.sh

53 lines
1.8 KiB

train_output_path=$1
stage=0
stop_stage=0
# e2e, synthesize from text
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
python3 ${BIN_DIR}/../ort_predict_e2e.py \
--inference_dir=${train_output_path}/inference_onnx \
--am=fastspeech2_csmsc \
--voc=pwgan_csmsc \
--output_dir=${train_output_path}/onnx_infer_out_e2e \
--text=${BIN_DIR}/../../assets/csmsc_test.txt \
--phones_dict=dump/phone_id_map.txt \
--device=cpu \
--cpu_threads=2
fi
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
python3 ${BIN_DIR}/../ort_predict_e2e.py \
--inference_dir=${train_output_path}/inference_onnx \
--am=fastspeech2_csmsc \
--voc=mb_melgan_csmsc \
--output_dir=${train_output_path}/onnx_infer_out_e2e \
--text=${BIN_DIR}/../../assets/csmsc_test.txt \
--phones_dict=dump/phone_id_map.txt \
--device=cpu \
--cpu_threads=2
fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
python3 ${BIN_DIR}/../ort_predict_e2e.py \
--inference_dir=${train_output_path}/inference_onnx \
--am=fastspeech2_csmsc \
--voc=hifigan_csmsc \
--output_dir=${train_output_path}/onnx_infer_out_e2e \
--text=${BIN_DIR}/../../assets/csmsc_test.txt \
--phones_dict=dump/phone_id_map.txt \
--device=cpu \
--cpu_threads=2
fi
# synthesize from metadata, take hifigan as an example
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
python3 ${BIN_DIR}/../ort_predict.py \
--inference_dir=${train_output_path}/inference_onnx \
--am=fastspeech2_csmsc \
--voc=hifigan_csmsc \
--test_metadata=dump/test/norm/metadata.jsonl \
--output_dir=${train_output_path}/onnx_infer_out \
--device=cpu \
--cpu_threads=2
fi