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50 lines
1.6 KiB
50 lines
1.6 KiB
train_output_path=$1
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stage=0
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stop_stage=0
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# e2e, synthesize from text
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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python3 ${BIN_DIR}/../ort_predict_e2e.py \
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--inference_dir=${train_output_path}/inference_onnx \
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--am=fastspeech2_canton \
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--voc=pwgan_aishell3 \
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--spk_id=10 \
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--output_dir=${train_output_path}/onnx_infer_out_e2e \
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--text=${BIN_DIR}/../../assets/sentences_canton.txt \
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--phones_dict=dump/phone_id_map.txt \
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--speaker_dict=dump/speaker_id_map.txt \
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--lang=canton \
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--device=cpu \
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--cpu_threads=2
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fi
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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python3 ${BIN_DIR}/../ort_predict_e2e.py \
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--inference_dir=${train_output_path}/inference_onnx \
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--am=fastspeech2_canton \
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--voc=mb_melgan_csmsc \
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--spk_id=10 \
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--output_dir=${train_output_path}/onnx_infer_out_e2e \
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--text=${BIN_DIR}/../../assets/sentences_canton.txt \
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--phones_dict=dump/phone_id_map.txt \
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--speaker_dict=dump/speaker_id_map.txt \
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--lang=canton \
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--device=cpu \
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--cpu_threads=2
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fi
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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python3 ${BIN_DIR}/../ort_predict_e2e.py \
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--inference_dir=${train_output_path}/inference_onnx \
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--am=fastspeech2_canton \
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--voc=hifigan_csmsc \
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--output_dir=${train_output_path}/onnx_infer_out_e2e \
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--text=${BIN_DIR}/../../assets/sentences_canton.txt \
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--phones_dict=dump/phone_id_map.txt \
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--speaker_dict=dump/speaker_id_map.txt \
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--lang=canton \
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--device=cpu \
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--cpu_threads=2
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fi
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