#!/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 ${BIN_DIR}/../synthesize.py \ --am=speedyspeech_csmsc \ --am_config=${config_path} \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/feats_stats.npy \ --voc=pwgan_csmsc \ --voc_config=pwg_baker_ckpt_0.4/pwg_default.yaml \ --voc_ckpt=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ --voc_stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --phones_dict=dump/phone_id_map.txt \ --tones_dict=dump/tone_id_map.txt fi # for more GAN Vocoders # multi band melgan if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then FLAGS_allocator_strategy=naive_best_fit \ FLAGS_fraction_of_gpu_memory_to_use=0.01 \ python3 ${BIN_DIR}/../synthesize.py \ --am=speedyspeech_csmsc \ --am_config=${config_path} \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/feats_stats.npy \ --voc=mb_melgan_csmsc \ --voc_config=mb_melgan_csmsc_ckpt_0.1.1/default.yaml \ --voc_ckpt=mb_melgan_csmsc_ckpt_0.1.1/snapshot_iter_1000000.pdz\ --voc_stat=mb_melgan_csmsc_ckpt_0.1.1/feats_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --phones_dict=dump/phone_id_map.txt \ --tones_dict=dump/tone_id_map.txt fi # style melgan if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then FLAGS_allocator_strategy=naive_best_fit \ FLAGS_fraction_of_gpu_memory_to_use=0.01 \ python3 ${BIN_DIR}/../synthesize.py \ --am=speedyspeech_csmsc \ --am_config=${config_path} \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/feats_stats.npy \ --voc=style_melgan_csmsc \ --voc_config=style_melgan_csmsc_ckpt_0.1.1/default.yaml \ --voc_ckpt=style_melgan_csmsc_ckpt_0.1.1/snapshot_iter_1500000.pdz \ --voc_stat=style_melgan_csmsc_ckpt_0.1.1/feats_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --phones_dict=dump/phone_id_map.txt \ --tones_dict=dump/tone_id_map.txt fi # hifigan if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then echo "in hifigan syn" FLAGS_allocator_strategy=naive_best_fit \ FLAGS_fraction_of_gpu_memory_to_use=0.01 \ python3 ${BIN_DIR}/../synthesize.py \ --am=speedyspeech_csmsc \ --am_config=${config_path} \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/feats_stats.npy \ --voc=hifigan_csmsc \ --voc_config=hifigan_csmsc_ckpt_0.1.1/default.yaml \ --voc_ckpt=hifigan_csmsc_ckpt_0.1.1/snapshot_iter_2500000.pdz \ --voc_stat=hifigan_csmsc_ckpt_0.1.1/feats_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --phones_dict=dump/phone_id_map.txt \ --tones_dict=dump/tone_id_map.txt fi # wavernn if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then echo "in wavernn syn" FLAGS_allocator_strategy=naive_best_fit \ FLAGS_fraction_of_gpu_memory_to_use=0.01 \ python3 ${BIN_DIR}/../synthesize.py \ --am=speedyspeech_csmsc \ --am_config=${config_path} \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/feats_stats.npy \ --voc=wavernn_csmsc \ --voc_config=wavernn_csmsc_ckpt_0.2.0/default.yaml \ --voc_ckpt=wavernn_csmsc_ckpt_0.2.0/snapshot_iter_400000.pdz \ --voc_stat=wavernn_csmsc_ckpt_0.2.0/feats_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --tones_dict=dump/tone_id_map.txt \ --phones_dict=dump/phone_id_map.txt fi