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PaddleSpeech/examples/opencpop/svs1/local/synthesize_e2e.sh

54 lines
1.9 KiB

#!/bin/bash
config_path=$1
train_output_path=$2
ckpt_name=$3
stage=0
stop_stage=0
# pwgan
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../synthesize_e2e.py \
--am=diffsinger_opencpop \
--am_config=${config_path} \
--am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--am_stat=dump/train/speech_stats.npy \
--voc=pwgan_opencpop \
--voc_config=pwgan_opencpop_ckpt_1.4.0/default.yaml \
--voc_ckpt=pwgan_opencpop_ckpt_1.4.0/snapshot_iter_100000.pdz \
--voc_stat=pwgan_opencpop_ckpt_1.4.0/feats_stats.npy \
--lang=sing \
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--text=${BIN_DIR}/../../assets/sentences_sing.txt \
--output_dir=${train_output_path}/test_e2e \
--phones_dict=dump/phone_id_map.txt \
--speech_stretchs=dump/train/speech_stretchs.npy \
--pinyin_phone=local/pinyin_to_phone.txt
fi
# for more GAN Vocoders
# hifigan
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
echo "in hifigan syn_e2e"
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../synthesize_e2e.py \
--am=diffsinger_opencpop \
--am_config=${config_path} \
--am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
--am_stat=dump/train/speech_stats.npy \
--voc=hifigan_opencpop \
--voc_config=hifigan_opencpop_ckpt_1.4.0/default.yaml \
--voc_ckpt=hifigan_opencpop_ckpt_1.4.0/snapshot_iter_625000.pdz \
--voc_stat=hifigan_opencpop_ckpt_1.4.0/feats_stats.npy \
--lang=sing \
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--text=${BIN_DIR}/../../assets/sentences_sing.txt \
--output_dir=${train_output_path}/test_e2e \
--phones_dict=dump/phone_id_map.txt \
--speech_stretchs=dump/train/speech_stretchs.npy \
--pinyin_phone=local/pinyin_to_phone.txt
fi