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# Copyright 2020 Tomoki Hayashi | |
# MIT License (https://opensource.org/licenses/MIT) | |
. ./cmd.sh || exit 1; | |
. ./path.sh || exit 1; | |
# basic settings | |
stage=0 # stage to start | |
stop_stage=100 # stage to stop | |
verbose=1 # verbosity level (lower is less info) | |
n_gpus=1 # number of gpus in training | |
n_jobs=4 # number of parallel jobs in feature extraction | |
# NOTE(kan-bayashi): renamed to conf to avoid conflict in parse_options.sh | |
conf=conf/parallel_wavegan.v1.yaml | |
# directory path setting | |
db_root=/path/to/database # direcotry including spk name directory (MODIFY BY YOURSELF) | |
# e.g. | |
# /path/to/database | |
# βββ spk_1 | |
# β βββ utt1.wav | |
# βββ spk_2 | |
# β βββ utt1.wav | |
# β ... | |
# βββ spk_N | |
# βββ utt1.wav | |
# ... | |
dumpdir=dump # directory to dump features | |
# subset setting | |
spks="all" # speaker name to be used (e.g. "spk1 spk2") | |
# it must be matched the name under the ${db_root} | |
# if set to "all", all of the speakers in ${db_root} will be used | |
shuffle=false # whether to shuffle the data to create subset | |
num_dev=10 # the number of development data for each speaker | |
num_eval=10 # the number of evaluation data for each speaker | |
# (if set to 0, the same dev set is used as eval set) | |
# training related setting | |
tag="" # tag for directory to save model | |
resume="" # checkpoint path to resume training | |
# (e.g. <path>/<to>/checkpoint-10000steps.pkl) | |
pretrain="" # checkpoint path to load pretrained parameters | |
# (e.g. ../../jsut/<path>/<to>/checkpoint-400000steps.pkl) | |
# decoding related setting | |
checkpoint="" # checkpoint path to be used for decoding | |
# if not provided, the latest one will be used | |
# (e.g. <path>/<to>/checkpoint-400000steps.pkl) | |
# shellcheck disable=SC1091 | |
. utils/parse_options.sh || exit 1; | |
train_set="train_nodev_$(echo "${spks}" | tr " " "_")" # name of training data directory | |
dev_set="dev_$(echo "${spks}" | tr " " "_")" # name of development data directory | |
eval_set="eval_$(echo "${spks}" | tr " " "_")" # name of evaluation data directory | |
set -euo pipefail | |
if [ "${stage}" -le 0 ] && [ "${stop_stage}" -ge 0 ]; then | |
echo "Stage 0: Data preparation" | |
train_data_dirs="" | |
dev_data_dirs="" | |
eval_data_dirs="" | |
if [ "${spks}" = "all" ]; then | |
spks=$(find "${db_root}" -maxdepth 1 ! -path "${db_root}" \ | |
-follow -type d -print0 -name "[^.]*" | xargs -0 -I{} basename {}) | |
fi | |
for spk in ${spks}; do | |
local/data_prep.sh \ | |
--fs "$(yq ".sampling_rate" "${conf}")" \ | |
--shuffle "${shuffle}" \ | |
--num_dev "${num_dev}" \ | |
--num_eval "${num_eval}" \ | |
--train_set "train_nodev_${spk}" \ | |
--dev_set "dev_${spk}" \ | |
--eval_set "eval_${spk}" \ | |
"${db_root}" "${spk}" data | |
train_data_dirs+=" data/train_nodev_${spk}" | |
dev_data_dirs+=" data/dev_${spk}" | |
eval_data_dirs+=" data/eval_${spk}" | |
done | |
# shellcheck disable=SC2086 | |
utils/combine_data.sh "data/${train_set}" ${train_data_dirs} | |
# shellcheck disable=SC2086 | |
utils/combine_data.sh "data/${dev_set}" ${dev_data_dirs} | |
# shellcheck disable=SC2086 | |
utils/combine_data.sh "data/${eval_set}" ${eval_data_dirs} | |
fi | |
stats_ext=$(grep -q "hdf5" <(yq ".format" "${conf}") && echo "h5" || echo "npy") | |
if [ "${stage}" -le 1 ] && [ "${stop_stage}" -ge 1 ]; then | |
echo "Stage 1: Feature extraction" | |
# extract raw features | |
pids=() | |
for name in "${train_set}" "${dev_set}" "${eval_set}"; do | |
( | |
[ ! -e "${dumpdir}/${name}/raw" ] && mkdir -p "${dumpdir}/${name}/raw" | |
echo "Feature extraction start. See the progress via ${dumpdir}/${name}/raw/preprocessing.*.log." | |
utils/make_subset_data.sh "data/${name}" "${n_jobs}" "${dumpdir}/${name}/raw" | |
${train_cmd} JOB=1:${n_jobs} "${dumpdir}/${name}/raw/preprocessing.JOB.log" \ | |
parallel-wavegan-preprocess \ | |
--config "${conf}" \ | |
--scp "${dumpdir}/${name}/raw/wav.JOB.scp" \ | |
--dumpdir "${dumpdir}/${name}/raw/dump.JOB" \ | |
--verbose "${verbose}" | |
echo "Successfully finished feature extraction of ${name} set." | |
) & | |
pids+=($!) | |
done | |
i=0; for pid in "${pids[@]}"; do wait "${pid}" || ((++i)); done | |
[ "${i}" -gt 0 ] && echo "$0: ${i} background jobs are failed." && exit 1; | |
echo "Successfully finished feature extraction." | |
# calculate statistics for normalization | |
if [ -z "${pretrain}" ]; then | |
# calculate statistics for normalization | |
echo "Statistics computation start. See the progress via ${dumpdir}/${train_set}/compute_statistics.log." | |
${train_cmd} "${dumpdir}/${train_set}/compute_statistics.log" \ | |
parallel-wavegan-compute-statistics \ | |
--config "${conf}" \ | |
--rootdir "${dumpdir}/${train_set}/raw" \ | |
--dumpdir "${dumpdir}/${train_set}" \ | |
--verbose "${verbose}" | |
echo "Successfully finished calculation of statistics." | |
else | |
echo "Use statistics of pretrained model. Skip statistics computation." | |
cp "$(dirname "${pretrain}")/stats.${stats_ext}" "${dumpdir}/${train_set}" | |
fi | |
# normalize and dump them | |
pids=() | |
for name in "${train_set}" "${dev_set}" "${eval_set}"; do | |
( | |
[ ! -e "${dumpdir}/${name}/norm" ] && mkdir -p "${dumpdir}/${name}/norm" | |
echo "Nomalization start. See the progress via ${dumpdir}/${name}/norm/normalize.*.log." | |
${train_cmd} JOB=1:${n_jobs} "${dumpdir}/${name}/norm/normalize.JOB.log" \ | |
parallel-wavegan-normalize \ | |
--config "${conf}" \ | |
--stats "${dumpdir}/${train_set}/stats.${stats_ext}" \ | |
--rootdir "${dumpdir}/${name}/raw/dump.JOB" \ | |
--dumpdir "${dumpdir}/${name}/norm/dump.JOB" \ | |
--verbose "${verbose}" | |
echo "Successfully finished normalization of ${name} set." | |
) & | |
pids+=($!) | |
done | |
i=0; for pid in "${pids[@]}"; do wait "${pid}" || ((++i)); done | |
[ "${i}" -gt 0 ] && echo "$0: ${i} background jobs are failed." && exit 1; | |
echo "Successfully finished normalization." | |
fi | |
if [ -z "${tag}" ]; then | |
expdir="exp/${train_set}_$(basename "${conf}" .yaml)" | |
if [ -n "${pretrain}" ]; then | |
pretrain_tag=$(basename "$(dirname "${pretrain}")") | |
expdir+="_${pretrain_tag}" | |
fi | |
else | |
expdir="exp/${train_set}_${tag}" | |
fi | |
if [ "${stage}" -le 2 ] && [ "${stop_stage}" -ge 2 ]; then | |
echo "Stage 2: Network training" | |
[ ! -e "${expdir}" ] && mkdir -p "${expdir}" | |
cp "${dumpdir}/${train_set}/stats.${stats_ext}" "${expdir}" | |
if [ "${n_gpus}" -gt 1 ]; then | |
train="python -m parallel_wavegan.distributed.launch --nproc_per_node ${n_gpus} -c parallel-wavegan-train" | |
else | |
train="parallel-wavegan-train" | |
fi | |
echo "Training start. See the progress via ${expdir}/train.log." | |
${cuda_cmd} --gpu "${n_gpus}" "${expdir}/train.log" \ | |
${train} \ | |
--config "${conf}" \ | |
--train-dumpdir "${dumpdir}/${train_set}/norm" \ | |
--dev-dumpdir "${dumpdir}/${dev_set}/norm" \ | |
--outdir "${expdir}" \ | |
--resume "${resume}" \ | |
--pretrain "${pretrain}" \ | |
--verbose "${verbose}" | |
echo "Successfully finished training." | |
fi | |
if [ "${stage}" -le 3 ] && [ "${stop_stage}" -ge 3 ]; then | |
echo "Stage 3: Network decoding" | |
# shellcheck disable=SC2012 | |
[ -z "${checkpoint}" ] && checkpoint="$(ls -dt "${expdir}"/*.pkl | head -1 || true)" | |
outdir="${expdir}/wav/$(basename "${checkpoint}" .pkl)" | |
pids=() | |
for name in "${dev_set}" "${eval_set}"; do | |
( | |
[ ! -e "${outdir}/${name}" ] && mkdir -p "${outdir}/${name}" | |
[ "${n_gpus}" -gt 1 ] && n_gpus=1 | |
echo "Decoding start. See the progress via ${outdir}/${name}/decode.log." | |
${cuda_cmd} --gpu "${n_gpus}" "${outdir}/${name}/decode.log" \ | |
parallel-wavegan-decode \ | |
--dumpdir "${dumpdir}/${name}/norm" \ | |
--checkpoint "${checkpoint}" \ | |
--outdir "${outdir}/${name}" \ | |
--verbose "${verbose}" | |
echo "Successfully finished decoding of ${name} set." | |
) & | |
pids+=($!) | |
done | |
i=0; for pid in "${pids[@]}"; do wait "${pid}" || ((++i)); done | |
[ "${i}" -gt 0 ] && echo "$0: ${i} background jobs are failed." && exit 1; | |
echo "Successfully finished decoding." | |
fi | |
echo "Finished." | |