From 3b718aefb49f0e463e9e3b77213433606b6e6a08 Mon Sep 17 00:00:00 2001
From: kan-bayashi <hayashi.tomoki@g.sp.m.is.nagoya-u.ac.jp>
Date: Mon, 11 May 2020 16:44:58 +0900
Subject: [PATCH 1/5] added template for single speaker recipe

---
 egs/template_single_spk/voc1/cmd.sh           |  91 +++++++++
 .../voc1/conf/parallel_wavegan.v1.yaml        | 121 ++++++++++++
 egs/template_single_spk/voc1/conf/slurm.conf  |  12 ++
 .../voc1/local/data_prep.sh                   |  87 ++++++++
 egs/template_single_spk/voc1/path.sh          |  33 ++++
 egs/template_single_spk/voc1/run.sh           | 187 ++++++++++++++++++
 egs/template_single_spk/voc1/utils            |   1 +
 7 files changed, 532 insertions(+)
 create mode 100644 egs/template_single_spk/voc1/cmd.sh
 create mode 100644 egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
 create mode 100644 egs/template_single_spk/voc1/conf/slurm.conf
 create mode 100755 egs/template_single_spk/voc1/local/data_prep.sh
 create mode 100644 egs/template_single_spk/voc1/path.sh
 create mode 100755 egs/template_single_spk/voc1/run.sh
 create mode 120000 egs/template_single_spk/voc1/utils

diff --git a/egs/template_single_spk/voc1/cmd.sh b/egs/template_single_spk/voc1/cmd.sh
new file mode 100644
index 00000000..19f34210
--- /dev/null
+++ b/egs/template_single_spk/voc1/cmd.sh
@@ -0,0 +1,91 @@
+# ====== About run.pl, queue.pl, slurm.pl, and ssh.pl ======
+# Usage: <cmd>.pl [options] JOB=1:<nj> <log> <command...>
+# e.g.
+#   run.pl --mem 4G JOB=1:10 echo.JOB.log echo JOB
+#
+# Options:
+#   --time <time>: Limit the maximum time to execute.
+#   --mem <mem>: Limit the maximum memory usage.
+#   -–max-jobs-run <njob>: Limit the number parallel jobs. This is ignored for non-array jobs.
+#   --num-threads <ngpu>: Specify the number of CPU core.
+#   --gpu <ngpu>: Specify the number of GPU devices.
+#   --config: Change the configuration file from default.
+#
+# "JOB=1:10" is used for "array jobs" and it can control the number of parallel jobs.
+# The left string of "=", i.e. "JOB", is replaced by <N>(Nth job) in the command and the log file name,
+# e.g. "echo JOB" is changed to "echo 3" for the 3rd job and "echo 8" for 8th job respectively.
+# Note that the number must start with a positive number, so you can't use "JOB=0:10" for example.
+#
+# run.pl, queue.pl, slurm.pl, and ssh.pl have unified interface, not depending on its backend.
+# These options are mapping to specific options for each backend and
+# it is configured by "conf/queue.conf" and "conf/slurm.conf" by default.
+# If jobs failed, your configuration might be wrong for your environment.
+#
+#
+# The official documentaion for run.pl, queue.pl, slurm.pl, and ssh.pl:
+#   "Parallelization in Kaldi": http://kaldi-asr.org/doc/queue.html
+# =========================================================~
+
+
+# Select the backend used by run.sh from "local", "stdout", "sge", "slurm", or "ssh"
+cmd_backend="local"
+
+# Local machine, without any Job scheduling system
+if [ "${cmd_backend}" = local ]; then
+
+    # The other usage
+    export train_cmd="utils/run.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="utils/run.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="utils/run.pl"
+
+# Local machine, without any Job scheduling system
+elif [ "${cmd_backend}" = stdout ]; then
+
+    # The other usage
+    export train_cmd="utils/stdout.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="utils/stdout.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="utils/stdout.pl"
+
+# "qsub" (SGE, Torque, PBS, etc.)
+elif [ "${cmd_backend}" = sge ]; then
+    # The default setting is written in conf/queue.conf.
+    # You must change "-q g.q" for the "queue" for your environment.
+    # To know the "queue" names, type "qhost -q"
+    # Note that to use "--gpu *", you have to setup "complex_value" for the system scheduler.
+
+    export train_cmd="utils/queue.pl"
+    export cuda_cmd="utils/queue.pl"
+    export decode_cmd="utils/queue.pl"
+
+# "sbatch" (Slurm)
+elif [ "${cmd_backend}" = slurm ]; then
+    # The default setting is written in conf/slurm.conf.
+    # You must change "-p cpu" and "-p gpu" for the "partion" for your environment.
+    # To know the "partion" names, type "sinfo".
+    # You can use "--gpu * " by defualt for slurm and it is interpreted as "--gres gpu:*"
+    # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}".
+
+    export train_cmd="utils/slurm.pl"
+    export cuda_cmd="utils/slurm.pl"
+    export decode_cmd="utils/slurm.pl"
+
+elif [ "${cmd_backend}" = ssh ]; then
+    # You have to create ".queue/machines" to specify the host to execute jobs.
+    # e.g. .queue/machines
+    #   host1
+    #   host2
+    #   host3
+    # Assuming you can login them without any password, i.e. You have to set ssh keys.
+
+    export train_cmd="utils/ssh.pl"
+    export cuda_cmd="utils/ssh.pl"
+    export decode_cmd="utils/ssh.pl"
+
+else
+    echo "$0: Error: Unknown cmd_backend=${cmd_backend}" 1>&2
+    return 1
+fi
diff --git a/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml b/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
new file mode 100644
index 00000000..e69c11e0
--- /dev/null
+++ b/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
@@ -0,0 +1,121 @@
+# This is the hyperparameter configuration file for Parallel WaveGAN.
+# This configuration requires 12 GB GPU memory and takes ~3 days on TITAN V.
+# You need to change the setting depneding on your dataset.
+
+###########################################################
+#                FEATURE EXTRACTION SETTING               #
+###########################################################
+sampling_rate: 22050     # Sampling rate.
+fft_size: 1024           # FFT size.
+hop_size: 256            # Hop size.
+win_length: null         # Window length.
+                         # If set to null, it will be the same as fft_size.
+window: "hann"           # Window function.
+num_mels: 80             # Number of mel basis.
+fmin: 80                 # Minimum freq in mel basis calculation.
+fmax: 7600               # Maximum frequency in mel basis calculation.
+global_gain_scale: 1.0   # Will be multiplied to all of waveform.
+trim_silence: true       # Whether to trim the start and end of silence.
+trim_threshold_in_db: 60 # Need to tune carefully if the recording is not good.
+trim_frame_size: 2048    # Frame size in trimming.
+trim_hop_size: 512       # Hop size in trimming.
+format: "hdf5"           # Feature file format. "npy" or "hdf5" is supported.
+
+###########################################################
+#         GENERATOR NETWORK ARCHITECTURE SETTING          #
+###########################################################
+generator_params:
+    in_channels: 1        # Number of input channels.
+    out_channels: 1       # Number of output channels.
+    kernel_size: 3        # Kernel size of dilated convolution.
+    layers: 30            # Number of residual block layers.
+    stacks: 3             # Number of stacks i.e., dilation cycles.
+    residual_channels: 64 # Number of channels in residual conv.
+    gate_channels: 128    # Number of channels in gated conv.
+    skip_channels: 64     # Number of channels in skip conv.
+    aux_channels: 80      # Number of channels for auxiliary feature conv.
+                          # Must be the same as num_mels.
+    aux_context_window: 2 # Context window size for auxiliary feature.
+                          # If set to 2, previous 2 and future 2 frames will be considered.
+    dropout: 0.0          # Dropout rate. 0.0 means no dropout applied.
+    use_weight_norm: true # Whether to use weight norm.
+                          # If set to true, it will be applied to all of the conv layers.
+    upsample_net: "ConvInUpsampleNetwork" # Upsampling network architecture.
+    upsample_params:                      # Upsampling network parameters.
+        upsample_scales: [4, 4, 4, 4]     # Upsampling scales. Prodcut of these must be the same as hop size.
+
+###########################################################
+#       DISCRIMINATOR NETWORK ARCHITECTURE SETTING        #
+###########################################################
+discriminator_params:
+    in_channels: 1        # Number of input channels.
+    out_channels: 1       # Number of output channels.
+    kernel_size: 3        # Number of output channels.
+    layers: 10            # Number of conv layers.
+    conv_channels: 64     # Number of chnn layers.
+    bias: true            # Whether to use bias parameter in conv.
+    use_weight_norm: true # Whether to use weight norm.
+                          # If set to true, it will be applied to all of the conv layers.
+    nonlinear_activation: "LeakyReLU" # Nonlinear function after each conv.
+    nonlinear_activation_params:      # Nonlinear function parameters
+        negative_slope: 0.2           # Alpha in LeakyReLU.
+
+###########################################################
+#                   STFT LOSS SETTING                     #
+###########################################################
+stft_loss_params:
+    fft_sizes: [1024, 2048, 512]  # List of FFT size for STFT-based loss.
+    hop_sizes: [120, 240, 50]     # List of hop size for STFT-based loss
+    win_lengths: [600, 1200, 240] # List of window length for STFT-based loss.
+    window: "hann_window"         # Window function for STFT-based loss
+
+###########################################################
+#               ADVERSARIAL LOSS SETTING                  #
+###########################################################
+lambda_adv: 4.0  # Loss balancing coefficient.
+
+###########################################################
+#                  DATA LOADER SETTING                    #
+###########################################################
+batch_size: 6              # Batch size.
+batch_max_steps: 25600     # Length of each audio in batch. Make sure dividable by hop_size.
+pin_memory: true           # Whether to pin memory in Pytorch DataLoader.
+num_workers: 2             # Number of workers in Pytorch DataLoader.
+remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps.
+allow_cache: true          # Whether to allow cache in dataset. If true, it requires cpu memory.
+
+###########################################################
+#             OPTIMIZER & SCHEDULER SETTING               #
+###########################################################
+generator_optimizer_params:
+    lr: 0.0001             # Generator's learning rate.
+    eps: 1.0e-6            # Generator's epsilon.
+    weight_decay: 0.0      # Generator's weight decay coefficient.
+generator_scheduler_params:
+    step_size: 200000      # Generator's scheduler step size.
+    gamma: 0.5             # Generator's scheduler gamma.
+                           # At each step size, lr will be multiplied by this parameter.
+generator_grad_norm: 10    # Generator's gradient norm.
+discriminator_optimizer_params:
+    lr: 0.00005            # Discriminator's learning rate.
+    eps: 1.0e-6            # Discriminator's epsilon.
+    weight_decay: 0.0      # Discriminator's weight decay coefficient.
+discriminator_scheduler_params:
+    step_size: 200000      # Discriminator's scheduler step size.
+    gamma: 0.5             # Discriminator's scheduler gamma.
+                           # At each step size, lr will be multiplied by this parameter.
+discriminator_grad_norm: 1 # Discriminator's gradient norm.
+
+###########################################################
+#                    INTERVAL SETTING                     #
+###########################################################
+discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator.
+train_max_steps: 400000                 # Number of training steps.
+save_interval_steps: 5000               # Interval steps to save checkpoint.
+eval_interval_steps: 1000               # Interval steps to evaluate the network.
+log_interval_steps: 100                 # Interval steps to record the training log.
+
+###########################################################
+#                     OTHER SETTING                       #
+###########################################################
+num_save_intermediate_results: 4  # Number of results to be saved as intermediate results.
diff --git a/egs/template_single_spk/voc1/conf/slurm.conf b/egs/template_single_spk/voc1/conf/slurm.conf
new file mode 100644
index 00000000..cefd21f0
--- /dev/null
+++ b/egs/template_single_spk/voc1/conf/slurm.conf
@@ -0,0 +1,12 @@
+# Default configuration
+command sbatch --export=PATH  --ntasks-per-node=1
+option time=* --time $0
+option mem=* --mem-per-cpu $0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* --cpus-per-task $0 --ntasks-per-node=1
+option num_threads=1 --cpus-per-task 1  --ntasks-per-node=1 # Do not add anything to qsub_opts
+default gpu=0
+option gpu=0 -p cpu
+option gpu=* -p gpu --gres=gpu:$0
+# note: the --max-jobs-run option is supported as a special case
+# by slurm.pl and you don't have to handle it in the config file.
diff --git a/egs/template_single_spk/voc1/local/data_prep.sh b/egs/template_single_spk/voc1/local/data_prep.sh
new file mode 100755
index 00000000..b2044d8f
--- /dev/null
+++ b/egs/template_single_spk/voc1/local/data_prep.sh
@@ -0,0 +1,87 @@
+#!/bin/bash
+
+# Copyright 2020 Tomoki Hayashi
+#  MIT License (https://opensource.org/licenses/MIT)
+
+# shellcheck disable=SC1091
+. ./path.sh || exit 1;
+
+fs=22050
+num_dev=100
+num_eval=100
+train_set="train_nodev"
+dev_set="dev"
+eval_set="eval"
+shuffle=false
+
+# shellcheck disable=SC1091
+. utils/parse_options.sh || exit 1;
+
+db_root=$1
+data_dir=$2
+
+# check arguments
+if [ $# != 2 ]; then
+    echo "Usage: $0 [Options] <db_root> <data_dir>"
+    echo ""
+    echo "Options:"
+    echo "    --num_dev: number of development uttreances (default=250)."
+    echo "    --num_eval: number of evaluation uttreances (default=250)."
+    echo "    --train_set: name of train set (default=train_nodev)."
+    echo "    --dev_set: name of dev set (default=dev)."
+    echo "    --eval_set: name of eval set (default=eval)."
+    echo "    --shuffle: whether to perform shuffle in making dev / eval set (default=false)."
+    exit 1
+fi
+
+set -euo pipefail
+
+[ ! -e "${data_dir}/all" ] && mkdir -p "${data_dir}/all"
+
+# set filenames
+scp="${data_dir}/all/wav.scp"
+
+# check file existence
+[ -e "${scp}" ] && rm "${scp}"
+
+# make all scp
+find "${db_root}" -follow -name "*.wav" | sort | while read -r filename; do
+    id=$(basename "${filename}" | sed -e "s/\.[^\.]*$//g")
+    echo "${id} cat ${filename} | sox -t wav - -c 1 -b 16 -t wav - rate ${fs} |" >> "${scp}"
+done
+
+# split
+num_all=$(wc -l < "${scp}")
+num_deveval=$((num_dev + num_eval))
+num_train=$((num_all - num_deveval))
+if [ ${num_eval} -ne 0 ]; then
+    utils/split_data.sh \
+        --num_first "${num_train}" \
+        --num_second "${num_deveval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/all" \
+        "${data_dir}/${train_set}" \
+        "${data_dir}/deveval"
+    utils/split_data.sh \
+        --num_first "${num_dev}" \
+        --num_second "${num_eval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/deveval" \
+        "${data_dir}/${dev_set}" \
+        "${data_dir}/${eval_set}"
+else
+    utils/split_data.sh \
+        --num_first "${num_train}" \
+        --num_second "${num_deveval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/all" \
+        "${data_dir}/${train_set}" \
+        "${data_dir}/${dev_set}"
+    cp -r "${data_dir}/${dev_set}" "${data_dir}/${eval_set}"
+fi
+
+# remove tmp directories
+rm -rf "${data_dir}/all"
+rm -rf "${data_dir}/deveval"
+
+echo "Successfully prepared data."
diff --git a/egs/template_single_spk/voc1/path.sh b/egs/template_single_spk/voc1/path.sh
new file mode 100644
index 00000000..b0ca27c6
--- /dev/null
+++ b/egs/template_single_spk/voc1/path.sh
@@ -0,0 +1,33 @@
+# cuda related
+export CUDA_HOME=/usr/local/cuda-10.0
+export LD_LIBRARY_PATH="${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}"
+
+# path related
+export PRJ_ROOT="${PWD}/../../.."
+if [ -e "${PRJ_ROOT}/tools/venv/bin/activate" ]; then
+    # shellcheck disable=SC1090
+    . "${PRJ_ROOT}/tools/venv/bin/activate"
+fi
+
+# python related
+export OMP_NUM_THREADS=1
+export PYTHONIOENCODING=UTF-8
+export MPL_BACKEND=Agg
+
+# check installation
+if ! command -v parallel-wavegan-train > /dev/null; then
+    echo "Error: It seems setup is not finished." >&2
+    echo "Error: Please setup your environment by following README.md" >&2
+    return 1
+fi
+if ! command -v jq > /dev/null; then
+    echo "Error: It seems jq is not installed." >&2
+    echo "Error: Please install via \`sudo apt-get install jq\`." >&2
+    echo "Error: If you do not have sudo, please download from https://stedolan.github.io/jq/download/." >&2
+    return 1
+fi
+if ! command -v yq > /dev/null; then
+    echo "Error: It seems yq is not installed." >&2
+    echo "Error: Please install via \`pip install yq\`." >&2
+    return 1
+fi
diff --git a/egs/template_single_spk/voc1/run.sh b/egs/template_single_spk/voc1/run.sh
new file mode 100755
index 00000000..44e0c12c
--- /dev/null
+++ b/egs/template_single_spk/voc1/run.sh
@@ -0,0 +1,187 @@
+#!/bin/bash
+
+# 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=16      # 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 wavfiles (MODIFY BY YOURSELF)
+                          # each wav filename in the directory should be unique
+                          # e.g.
+                          # /path/to/database
+                          # ├── utt_1.wav
+                          # ├── utt_2.wav
+                          # │   ...
+                          # └── utt_N.wav
+dumpdir=dump # directory to dump features
+
+# subset setting
+shuffle=false # whether to shuffle the data to create subset
+num_dev=100   # the number of development data
+num_eval=100  # the number of evaluation data
+              # (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" # name of training data directory
+dev_set="dev"           # name of development data direcotry
+eval_set="eval"         # name of evaluation data direcotry
+
+set -euo pipefail
+
+if [ "${stage}" -le 0 ] && [ "${stop_stage}" -ge 0 ]; then
+    echo "Stage 0: Data preparation"
+    local/data_prep.sh \
+        --fs "$(yq ".sampling_rate" "${conf}")" \
+        --num_dev "${num_dev}" \
+        --num_eval "${num_eval}" \
+        --train_set "${train_set}" \
+        --dev_set "${dev_set}" \
+        --eval_set "${eval_set}" \
+        --shuffle "${shuffle}" \
+        "${db_root}" data
+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}" \
+            --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."
diff --git a/egs/template_single_spk/voc1/utils b/egs/template_single_spk/voc1/utils
new file mode 120000
index 00000000..973afe67
--- /dev/null
+++ b/egs/template_single_spk/voc1/utils
@@ -0,0 +1 @@
+../../../utils
\ No newline at end of file

From 26516fe2d5964f84f2b1cf7a4c18919a2af53204 Mon Sep 17 00:00:00 2001
From: kan-bayashi <hayashi.tomoki@g.sp.m.is.nagoya-u.ac.jp>
Date: Mon, 11 May 2020 16:45:10 +0900
Subject: [PATCH 2/5] added template for multi speaker recipe

---
 egs/template_multi_spk/voc1/cmd.sh            |  91 ++++++++
 .../voc1/conf/parallel_wavegan.v1.yaml        | 121 +++++++++++
 egs/template_multi_spk/voc1/conf/slurm.conf   |  12 +
 .../voc1/local/data_prep.sh                   |  93 ++++++++
 egs/template_multi_spk/voc1/path.sh           |  33 +++
 egs/template_multi_spk/voc1/run.sh            | 205 ++++++++++++++++++
 egs/template_multi_spk/voc1/utils             |   1 +
 7 files changed, 556 insertions(+)
 create mode 100644 egs/template_multi_spk/voc1/cmd.sh
 create mode 100644 egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
 create mode 100644 egs/template_multi_spk/voc1/conf/slurm.conf
 create mode 100755 egs/template_multi_spk/voc1/local/data_prep.sh
 create mode 100644 egs/template_multi_spk/voc1/path.sh
 create mode 100755 egs/template_multi_spk/voc1/run.sh
 create mode 120000 egs/template_multi_spk/voc1/utils

diff --git a/egs/template_multi_spk/voc1/cmd.sh b/egs/template_multi_spk/voc1/cmd.sh
new file mode 100644
index 00000000..19f34210
--- /dev/null
+++ b/egs/template_multi_spk/voc1/cmd.sh
@@ -0,0 +1,91 @@
+# ====== About run.pl, queue.pl, slurm.pl, and ssh.pl ======
+# Usage: <cmd>.pl [options] JOB=1:<nj> <log> <command...>
+# e.g.
+#   run.pl --mem 4G JOB=1:10 echo.JOB.log echo JOB
+#
+# Options:
+#   --time <time>: Limit the maximum time to execute.
+#   --mem <mem>: Limit the maximum memory usage.
+#   -–max-jobs-run <njob>: Limit the number parallel jobs. This is ignored for non-array jobs.
+#   --num-threads <ngpu>: Specify the number of CPU core.
+#   --gpu <ngpu>: Specify the number of GPU devices.
+#   --config: Change the configuration file from default.
+#
+# "JOB=1:10" is used for "array jobs" and it can control the number of parallel jobs.
+# The left string of "=", i.e. "JOB", is replaced by <N>(Nth job) in the command and the log file name,
+# e.g. "echo JOB" is changed to "echo 3" for the 3rd job and "echo 8" for 8th job respectively.
+# Note that the number must start with a positive number, so you can't use "JOB=0:10" for example.
+#
+# run.pl, queue.pl, slurm.pl, and ssh.pl have unified interface, not depending on its backend.
+# These options are mapping to specific options for each backend and
+# it is configured by "conf/queue.conf" and "conf/slurm.conf" by default.
+# If jobs failed, your configuration might be wrong for your environment.
+#
+#
+# The official documentaion for run.pl, queue.pl, slurm.pl, and ssh.pl:
+#   "Parallelization in Kaldi": http://kaldi-asr.org/doc/queue.html
+# =========================================================~
+
+
+# Select the backend used by run.sh from "local", "stdout", "sge", "slurm", or "ssh"
+cmd_backend="local"
+
+# Local machine, without any Job scheduling system
+if [ "${cmd_backend}" = local ]; then
+
+    # The other usage
+    export train_cmd="utils/run.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="utils/run.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="utils/run.pl"
+
+# Local machine, without any Job scheduling system
+elif [ "${cmd_backend}" = stdout ]; then
+
+    # The other usage
+    export train_cmd="utils/stdout.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="utils/stdout.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="utils/stdout.pl"
+
+# "qsub" (SGE, Torque, PBS, etc.)
+elif [ "${cmd_backend}" = sge ]; then
+    # The default setting is written in conf/queue.conf.
+    # You must change "-q g.q" for the "queue" for your environment.
+    # To know the "queue" names, type "qhost -q"
+    # Note that to use "--gpu *", you have to setup "complex_value" for the system scheduler.
+
+    export train_cmd="utils/queue.pl"
+    export cuda_cmd="utils/queue.pl"
+    export decode_cmd="utils/queue.pl"
+
+# "sbatch" (Slurm)
+elif [ "${cmd_backend}" = slurm ]; then
+    # The default setting is written in conf/slurm.conf.
+    # You must change "-p cpu" and "-p gpu" for the "partion" for your environment.
+    # To know the "partion" names, type "sinfo".
+    # You can use "--gpu * " by defualt for slurm and it is interpreted as "--gres gpu:*"
+    # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}".
+
+    export train_cmd="utils/slurm.pl"
+    export cuda_cmd="utils/slurm.pl"
+    export decode_cmd="utils/slurm.pl"
+
+elif [ "${cmd_backend}" = ssh ]; then
+    # You have to create ".queue/machines" to specify the host to execute jobs.
+    # e.g. .queue/machines
+    #   host1
+    #   host2
+    #   host3
+    # Assuming you can login them without any password, i.e. You have to set ssh keys.
+
+    export train_cmd="utils/ssh.pl"
+    export cuda_cmd="utils/ssh.pl"
+    export decode_cmd="utils/ssh.pl"
+
+else
+    echo "$0: Error: Unknown cmd_backend=${cmd_backend}" 1>&2
+    return 1
+fi
diff --git a/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml b/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
new file mode 100644
index 00000000..e69c11e0
--- /dev/null
+++ b/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
@@ -0,0 +1,121 @@
+# This is the hyperparameter configuration file for Parallel WaveGAN.
+# This configuration requires 12 GB GPU memory and takes ~3 days on TITAN V.
+# You need to change the setting depneding on your dataset.
+
+###########################################################
+#                FEATURE EXTRACTION SETTING               #
+###########################################################
+sampling_rate: 22050     # Sampling rate.
+fft_size: 1024           # FFT size.
+hop_size: 256            # Hop size.
+win_length: null         # Window length.
+                         # If set to null, it will be the same as fft_size.
+window: "hann"           # Window function.
+num_mels: 80             # Number of mel basis.
+fmin: 80                 # Minimum freq in mel basis calculation.
+fmax: 7600               # Maximum frequency in mel basis calculation.
+global_gain_scale: 1.0   # Will be multiplied to all of waveform.
+trim_silence: true       # Whether to trim the start and end of silence.
+trim_threshold_in_db: 60 # Need to tune carefully if the recording is not good.
+trim_frame_size: 2048    # Frame size in trimming.
+trim_hop_size: 512       # Hop size in trimming.
+format: "hdf5"           # Feature file format. "npy" or "hdf5" is supported.
+
+###########################################################
+#         GENERATOR NETWORK ARCHITECTURE SETTING          #
+###########################################################
+generator_params:
+    in_channels: 1        # Number of input channels.
+    out_channels: 1       # Number of output channels.
+    kernel_size: 3        # Kernel size of dilated convolution.
+    layers: 30            # Number of residual block layers.
+    stacks: 3             # Number of stacks i.e., dilation cycles.
+    residual_channels: 64 # Number of channels in residual conv.
+    gate_channels: 128    # Number of channels in gated conv.
+    skip_channels: 64     # Number of channels in skip conv.
+    aux_channels: 80      # Number of channels for auxiliary feature conv.
+                          # Must be the same as num_mels.
+    aux_context_window: 2 # Context window size for auxiliary feature.
+                          # If set to 2, previous 2 and future 2 frames will be considered.
+    dropout: 0.0          # Dropout rate. 0.0 means no dropout applied.
+    use_weight_norm: true # Whether to use weight norm.
+                          # If set to true, it will be applied to all of the conv layers.
+    upsample_net: "ConvInUpsampleNetwork" # Upsampling network architecture.
+    upsample_params:                      # Upsampling network parameters.
+        upsample_scales: [4, 4, 4, 4]     # Upsampling scales. Prodcut of these must be the same as hop size.
+
+###########################################################
+#       DISCRIMINATOR NETWORK ARCHITECTURE SETTING        #
+###########################################################
+discriminator_params:
+    in_channels: 1        # Number of input channels.
+    out_channels: 1       # Number of output channels.
+    kernel_size: 3        # Number of output channels.
+    layers: 10            # Number of conv layers.
+    conv_channels: 64     # Number of chnn layers.
+    bias: true            # Whether to use bias parameter in conv.
+    use_weight_norm: true # Whether to use weight norm.
+                          # If set to true, it will be applied to all of the conv layers.
+    nonlinear_activation: "LeakyReLU" # Nonlinear function after each conv.
+    nonlinear_activation_params:      # Nonlinear function parameters
+        negative_slope: 0.2           # Alpha in LeakyReLU.
+
+###########################################################
+#                   STFT LOSS SETTING                     #
+###########################################################
+stft_loss_params:
+    fft_sizes: [1024, 2048, 512]  # List of FFT size for STFT-based loss.
+    hop_sizes: [120, 240, 50]     # List of hop size for STFT-based loss
+    win_lengths: [600, 1200, 240] # List of window length for STFT-based loss.
+    window: "hann_window"         # Window function for STFT-based loss
+
+###########################################################
+#               ADVERSARIAL LOSS SETTING                  #
+###########################################################
+lambda_adv: 4.0  # Loss balancing coefficient.
+
+###########################################################
+#                  DATA LOADER SETTING                    #
+###########################################################
+batch_size: 6              # Batch size.
+batch_max_steps: 25600     # Length of each audio in batch. Make sure dividable by hop_size.
+pin_memory: true           # Whether to pin memory in Pytorch DataLoader.
+num_workers: 2             # Number of workers in Pytorch DataLoader.
+remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps.
+allow_cache: true          # Whether to allow cache in dataset. If true, it requires cpu memory.
+
+###########################################################
+#             OPTIMIZER & SCHEDULER SETTING               #
+###########################################################
+generator_optimizer_params:
+    lr: 0.0001             # Generator's learning rate.
+    eps: 1.0e-6            # Generator's epsilon.
+    weight_decay: 0.0      # Generator's weight decay coefficient.
+generator_scheduler_params:
+    step_size: 200000      # Generator's scheduler step size.
+    gamma: 0.5             # Generator's scheduler gamma.
+                           # At each step size, lr will be multiplied by this parameter.
+generator_grad_norm: 10    # Generator's gradient norm.
+discriminator_optimizer_params:
+    lr: 0.00005            # Discriminator's learning rate.
+    eps: 1.0e-6            # Discriminator's epsilon.
+    weight_decay: 0.0      # Discriminator's weight decay coefficient.
+discriminator_scheduler_params:
+    step_size: 200000      # Discriminator's scheduler step size.
+    gamma: 0.5             # Discriminator's scheduler gamma.
+                           # At each step size, lr will be multiplied by this parameter.
+discriminator_grad_norm: 1 # Discriminator's gradient norm.
+
+###########################################################
+#                    INTERVAL SETTING                     #
+###########################################################
+discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator.
+train_max_steps: 400000                 # Number of training steps.
+save_interval_steps: 5000               # Interval steps to save checkpoint.
+eval_interval_steps: 1000               # Interval steps to evaluate the network.
+log_interval_steps: 100                 # Interval steps to record the training log.
+
+###########################################################
+#                     OTHER SETTING                       #
+###########################################################
+num_save_intermediate_results: 4  # Number of results to be saved as intermediate results.
diff --git a/egs/template_multi_spk/voc1/conf/slurm.conf b/egs/template_multi_spk/voc1/conf/slurm.conf
new file mode 100644
index 00000000..cefd21f0
--- /dev/null
+++ b/egs/template_multi_spk/voc1/conf/slurm.conf
@@ -0,0 +1,12 @@
+# Default configuration
+command sbatch --export=PATH  --ntasks-per-node=1
+option time=* --time $0
+option mem=* --mem-per-cpu $0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* --cpus-per-task $0 --ntasks-per-node=1
+option num_threads=1 --cpus-per-task 1  --ntasks-per-node=1 # Do not add anything to qsub_opts
+default gpu=0
+option gpu=0 -p cpu
+option gpu=* -p gpu --gres=gpu:$0
+# note: the --max-jobs-run option is supported as a special case
+# by slurm.pl and you don't have to handle it in the config file.
diff --git a/egs/template_multi_spk/voc1/local/data_prep.sh b/egs/template_multi_spk/voc1/local/data_prep.sh
new file mode 100755
index 00000000..6c3df19a
--- /dev/null
+++ b/egs/template_multi_spk/voc1/local/data_prep.sh
@@ -0,0 +1,93 @@
+#!/bin/bash
+
+# Copyright 2020 Tomoki Hayashi
+#  MIT License (https://opensource.org/licenses/MIT)
+
+# shellcheck disable=SC1091
+. ./path.sh || exit 1;
+
+fs=22050
+num_dev=5
+num_eval=5
+train_set="train_nodev"
+dev_set="dev"
+eval_set="eval"
+shuffle=false
+
+# shellcheck disable=SC1091
+. utils/parse_options.sh || exit 1;
+
+db_root=$1
+spk=$2
+data_dir=$3
+
+# check arguments
+if [ $# != 3 ]; then
+    echo "Usage: $0 [Options] <db_root> <spk> <data_dir>"
+    echo ""
+    echo "Options:"
+    echo "    --fs: target sampling rate (default=22050)."
+    echo "    --num_dev: number of development uttreances (default=10)."
+    echo "    --num_eval: number of evaluation uttreances (default=10)."
+    echo "    --train_set: name of train set (default=train_nodev)."
+    echo "    --dev_set: name of dev set (default=dev)."
+    echo "    --eval_set: name of eval set (default=eval)."
+    echo "    --shuffle: whether to perform shuffule to make dev & eval set (default=true)."
+    exit 1
+fi
+
+set -euo pipefail
+
+# check spk existence
+[ ! -e "${db_root}/${spk}" ] && \
+    echo "${spk} does not exist." >&2 && exit 1;
+
+[ ! -e "${data_dir}/all_${spk}" ] && mkdir -p "${data_dir}/all_${spk}"
+
+# set filenames
+scp="${data_dir}/all_${spk}/wav.scp"
+
+# check file existence
+[ -e "${scp}" ] && rm "${scp}"
+
+# make all scp
+find "${db_root}/${spk}" -follow -name "*.wav" | sort | while read -r filename; do
+    id=${spk}_$(basename "${filename}" | sed -e "s/\.[^\.]*$//g")
+    echo "${id} cat ${filename} | sox -t wav - -c 1 -b 16 -t wav - rate ${fs} |" >> "${scp}"
+done
+
+# split
+num_all=$(wc -l < "${scp}")
+num_deveval=$((num_dev + num_eval))
+num_train=$((num_all - num_deveval))
+if [ ${num_eval} -ne 0 ]; then
+    utils/split_data.sh \
+        --num_first "${num_train}" \
+        --num_second "${num_deveval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/all_${spk}" \
+        "${data_dir}/${train_set}" \
+        "${data_dir}/deveval_${spk}"
+    utils/split_data.sh \
+        --num_first "${num_dev}" \
+        --num_second "${num_eval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/deveval_${spk}" \
+        "${data_dir}/${dev_set}" \
+        "${data_dir}/${eval_set}"
+else
+    utils/split_data.sh \
+        --num_first "${num_train}" \
+        --num_second "${num_deveval}" \
+        --shuffle "${shuffle}" \
+        "${data_dir}/all_${spk}" \
+        "${data_dir}/${train_set}" \
+        "${data_dir}/${dev_set}"
+    cp -r "${data_dir}/${dev_set}" "${data_dir}/${eval_set}"
+fi
+
+# remove tmp directories
+rm -rf "${data_dir}/all_${spk}"
+rm -rf "${data_dir}/deveval_${spk}"
+
+echo "Successfully prepared data."
diff --git a/egs/template_multi_spk/voc1/path.sh b/egs/template_multi_spk/voc1/path.sh
new file mode 100644
index 00000000..b0ca27c6
--- /dev/null
+++ b/egs/template_multi_spk/voc1/path.sh
@@ -0,0 +1,33 @@
+# cuda related
+export CUDA_HOME=/usr/local/cuda-10.0
+export LD_LIBRARY_PATH="${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}"
+
+# path related
+export PRJ_ROOT="${PWD}/../../.."
+if [ -e "${PRJ_ROOT}/tools/venv/bin/activate" ]; then
+    # shellcheck disable=SC1090
+    . "${PRJ_ROOT}/tools/venv/bin/activate"
+fi
+
+# python related
+export OMP_NUM_THREADS=1
+export PYTHONIOENCODING=UTF-8
+export MPL_BACKEND=Agg
+
+# check installation
+if ! command -v parallel-wavegan-train > /dev/null; then
+    echo "Error: It seems setup is not finished." >&2
+    echo "Error: Please setup your environment by following README.md" >&2
+    return 1
+fi
+if ! command -v jq > /dev/null; then
+    echo "Error: It seems jq is not installed." >&2
+    echo "Error: Please install via \`sudo apt-get install jq\`." >&2
+    echo "Error: If you do not have sudo, please download from https://stedolan.github.io/jq/download/." >&2
+    return 1
+fi
+if ! command -v yq > /dev/null; then
+    echo "Error: It seems yq is not installed." >&2
+    echo "Error: Please install via \`pip install yq\`." >&2
+    return 1
+fi
diff --git a/egs/template_multi_spk/voc1/run.sh b/egs/template_multi_spk/voc1/run.sh
new file mode 100755
index 00000000..2615db3b
--- /dev/null
+++ b/egs/template_multi_spk/voc1/run.sh
@@ -0,0 +1,205 @@
+#!/bin/bash
+
+# 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=16      # 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
+                          # ├── spk_1
+                          # │   ├── utt1.wav
+                          # ├── spk_2
+                          # │   ├── utt1.wav
+                          # │   ...
+                          # └── spk_N
+                          #     ├── 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
+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}" \
+            --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."
diff --git a/egs/template_multi_spk/voc1/utils b/egs/template_multi_spk/voc1/utils
new file mode 120000
index 00000000..973afe67
--- /dev/null
+++ b/egs/template_multi_spk/voc1/utils
@@ -0,0 +1 @@
+../../../utils
\ No newline at end of file

From 15cd9323f57b3e0c2ef42d935e24e6c0b62583ff Mon Sep 17 00:00:00 2001
From: kan-bayashi <hayashi.tomoki@g.sp.m.is.nagoya-u.ac.jp>
Date: Mon, 11 May 2020 17:12:32 +0900
Subject: [PATCH 3/5] added README

---
 egs/README.md | 108 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 egs/README.md

diff --git a/egs/README.md b/egs/README.md
new file mode 100644
index 00000000..a20f13c6
--- /dev/null
+++ b/egs/README.md
@@ -0,0 +1,108 @@
+# Kaldi-sytle all-in-one recipes
+
+This repository provides [Kaldi](https://github.com/kaldi-asr/kaldi)-style recipes, as the same as [ESPnet](https://github.com/espnet/espnet).  
+Currently, the following recipes are supported.
+
+- [LJSpeech](https://keithito.com/LJ-Speech-Dataset/): English female speaker
+- [JSUT](https://sites.google.com/site/shinnosuketakamichi/publication/jsut): Japanese female speaker
+- [CSMSC](https://www.data-baker.com/open_source.html): Mandarin female speaker
+- [CMU Arctic](http://www.festvox.org/cmu_arctic/): English speakers
+- [JNAS](http://research.nii.ac.jp/src/en/JNAS.html): Japanese multi-speaker
+- [VCTK](https://homepages.inf.ed.ac.uk/jyamagis/page3/page58/page58.html): English multi-speaker
+- [LibriTTS](https://arxiv.org/abs/1904.02882): English multi-speaker
+
+
+## How to run the recipe
+
+```bash
+# Let us move on the recipe directory
+$ cd egs/ljspeech/voc1
+
+# Run the recipe from scratch
+$ ./run.sh
+
+# You can change config via command line
+$ ./run.sh --conf <your_customized_yaml_config>
+
+# You can select the stage to start and stop
+$ ./run.sh --stage 2 --stop_stage 2
+
+# If you want to specify the gpu
+$ CUDA_VISIBLE_DEVICES=1 ./run.sh --stage 2
+
+# If you want to resume training from 10000 steps checkpoint
+$ ./run.sh --stage 2 --resume <path>/<to>/checkpoint-10000steps.pkl
+```
+
+You can check the command line options in `run.sh`.
+
+The integration with job schedulers such as [slurm](https://slurm.schedmd.com/documentation.html) can be done via `cmd.sh` and  `conf/slurm.conf`.  
+If you want to use it, please check [this page](https://kaldi-asr.org/doc/queue.html).
+
+All of the hyperparameters is written in a single yaml format configuration file.  
+Please check [this example](https://github.com/kan-bayashi/ParallelWaveGAN/blob/master/egs/ljspeech/voc1/conf/parallel_wavegan.v1.yaml) in ljspeech recipe.
+
+## How to make the recipe for your own dateset
+
+1. Setup your dataset to be the following structure.
+
+    ```bash
+    # For single-speaker case
+    $ tree /path/to/databse
+    /path/to/database
+    ├── utt_1.wav
+    ├── utt_2.wav
+    │   ...
+    └── utt_N.wav
+    # The directory can be nested, but each filename must be unique
+
+    # For multi-speaker case
+    $ tree /path/to/databse
+    /path/to/database
+    ├── spk_1
+    │   ├── utt1.wav
+    ├── spk_2
+    │   ├── utt1.wav
+    │   ...
+    └── spk_N
+        ├── utt1.wav
+        ...
+    # The directory under each speaker can be nested, but each filename in each speaker directory must be unique
+    ```
+
+2. Copy the template directory.
+
+    ```bash
+    cd egs
+
+    # For single speaker case
+    cp -r template_single_spk <your_dataset_name>
+
+    # For multi speaker case
+    cp -r template_multi_spk <your_dataset_name>
+
+    # Move on your recipe
+    cd egs/<your_dataset_name>/voc1
+    ```
+
+3. Modify the options in `run.sh`.
+
+    > What you need to change at least in `run.sh` is `db_root` option.
+
+4. Modify the hyperpameters in `conf/parallel_wavegan.v1.yaml`.
+
+    > What you need to change at least is `sampling_rate`
+
+5. (Optional) Change command backend in `cmd.sh`.
+
+    > If you are not familiar with kaldi and run in your local env, you do not need to change.
+
+6. Run your recipe.
+
+    ```bash
+    # Run all stages from the first stage
+    ./run.sh
+
+    # Specify CUDA device
+    CUDA_VISIBLE_DEVICES=0 ./run.sh
+    ```

From dc07821e1b02912ac6e6122ef2986596027bf5c3 Mon Sep 17 00:00:00 2001
From: kan-bayashi <hayashi.tomoki@g.sp.m.is.nagoya-u.ac.jp>
Date: Mon, 11 May 2020 17:20:17 +0900
Subject: [PATCH 4/5] updated README

---
 egs/README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/egs/README.md b/egs/README.md
index a20f13c6..7cb23e61 100644
--- a/egs/README.md
+++ b/egs/README.md
@@ -106,3 +106,5 @@ Please check [this example](https://github.com/kan-bayashi/ParallelWaveGAN/blob/
     # Specify CUDA device
     CUDA_VISIBLE_DEVICES=0 ./run.sh
     ```
+
+If you want to try the other advanced model, please check the config files in `egs/ljspeech/voc1/conf`.

From bcfb898e6554f7d0c99565ce2bd155a2562901c0 Mon Sep 17 00:00:00 2001
From: kan-bayashi <hayashi.tomoki@g.sp.m.is.nagoya-u.ac.jp>
Date: Mon, 11 May 2020 17:22:18 +0900
Subject: [PATCH 5/5] disable trimming as default

---
 egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml  | 2 +-
 egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml b/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
index e69c11e0..920cb7be 100644
--- a/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
+++ b/egs/template_multi_spk/voc1/conf/parallel_wavegan.v1.yaml
@@ -15,7 +15,7 @@ num_mels: 80             # Number of mel basis.
 fmin: 80                 # Minimum freq in mel basis calculation.
 fmax: 7600               # Maximum frequency in mel basis calculation.
 global_gain_scale: 1.0   # Will be multiplied to all of waveform.
-trim_silence: true       # Whether to trim the start and end of silence.
+trim_silence: false      # Whether to trim the start and end of silence.
 trim_threshold_in_db: 60 # Need to tune carefully if the recording is not good.
 trim_frame_size: 2048    # Frame size in trimming.
 trim_hop_size: 512       # Hop size in trimming.
diff --git a/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml b/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
index e69c11e0..29ff94d0 100644
--- a/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
+++ b/egs/template_single_spk/voc1/conf/parallel_wavegan.v1.yaml
@@ -15,7 +15,7 @@ num_mels: 80             # Number of mel basis.
 fmin: 80                 # Minimum freq in mel basis calculation.
 fmax: 7600               # Maximum frequency in mel basis calculation.
 global_gain_scale: 1.0   # Will be multiplied to all of waveform.
-trim_silence: true       # Whether to trim the start and end of silence.
+trim_silence: false       # Whether to trim the start and end of silence.
 trim_threshold_in_db: 60 # Need to tune carefully if the recording is not good.
 trim_frame_size: 2048    # Frame size in trimming.
 trim_hop_size: 512       # Hop size in trimming.