#
# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import argparse

def parse_waveglow_args(parent, add_help=False):
    """
    Parse commandline arguments.
    """
    parser = argparse.ArgumentParser(parents=[parent], add_help=add_help)

    # misc parameters
    parser.add_argument('--n-mel-channels', default=80, type=int,
                        help='Number of bins in mel-spectrograms')

    # glow parameters
    parser.add_argument('--flows', default=12, type=int,
                        help='Number of steps of flow')
    parser.add_argument('--groups', default=8, type=int,
                        help='Number of samples in a group processed by the steps of flow')
    parser.add_argument('--early-every', default=4, type=int,
                        help='Determines how often (i.e., after how many coupling layers) \
                        a number of channels (defined by --early-size parameter) are output\
                        to the loss function')
    parser.add_argument('--early-size', default=2, type=int,
                        help='Number of channels output to the loss function')
    parser.add_argument('--sigma', default=1.0, type=float,
                        help='Standard deviation used for sampling from Gaussian')
    parser.add_argument('--segment-length', default=4000, type=int,
                        help='Segment length (audio samples) processed per iteration')

    # wavenet parameters
    wavenet = parser.add_argument_group('WaveNet parameters')
    wavenet.add_argument('--wn-kernel-size', default=3, type=int,
                        help='Kernel size for dialted convolution in the affine coupling layer (WN)')
    wavenet.add_argument('--wn-channels', default=512, type=int,
                        help='Number of channels in WN')
    wavenet.add_argument('--wn-layers', default=8, type=int,
                        help='Number of layers in WN')

    return parser
