# train model
CUDA_VISIBLE_DEVICES=0 \
python -u synthesis.py \
--max_len=400 \ --use_gpu=0 \
--output='./synthesis' \ --config='configs/ljspeech.yaml' \ --checkpoint_transformer='./checkpoint/transformer/step-120000' \
--vocoder='wavenet' \ --config_vocoder='../wavenet/config.yaml' \ --checkpoint_vocoder='../wavenet/step-2450000' \ #--vocoder='waveflow' \ #--config_vocoder='../waveflow/checkpoint/waveflow_res64_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \ #--checkpoint_vocoder='../waveflow/checkpoint/waveflow_res64_ljspeech_ckpt_1.0/step-3020000' \ #--vocoder='cbhg' \ #--config_vocoder='configs/ljspeech.yaml' \ #--checkpoint_vocoder='checkpoint/cbhg/step-100000' \
if [ $? -ne 0 ]; then echo "Failed in training!" exit 1 fi
exit 0
