<reponame>philsyn/DiffWave-unconditional<filename>distributed_train.py
# *****************************************************************************
# Adapted from https://github.com/NVIDIA/waveglow/blob/master/distributed.py
# *****************************************************************************

# *****************************************************************************
#  Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.
#
#  Redistribution and use in source and binary forms, with or without
#  modification, are permitted provided that the following conditions are met:
#      * Redistributions of source code must retain the above copyright
#        notice, this list of conditions and the following disclaimer.
#      * Redistributions in binary form must reproduce the above copyright
#        notice, this list of conditions and the following disclaimer in the
#        documentation and/or other materials provided with the distribution.
#      * Neither the name of the NVIDIA CORPORATION nor the
#        names of its contributors may be used to endorse or promote products
#        derived from this software without specific prior written permission.
#
#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
#  ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
#  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
#  DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
#  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
#  (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
#  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
#  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
#  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
#  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# *****************************************************************************\

import os
import sys
import time
import subprocess
import argparse
import warnings
warnings.filterwarnings("ignore")

import torch

from distributed_util import *


def main(config, stdout_dir, args_str):
    args_list = ['train.py']
    args_list += args_str.split(' ') if len(args_str) > 0 else []

    args_list.append('--config={}'.format(config))

    num_gpus = torch.cuda.device_count()
    args_list.append('--num_gpus={}'.format(num_gpus))
    args_list.append("--group_name=group_{}".format(time.strftime("%Y_%m_%d-%H%M%S")))

    if not os.path.isdir(stdout_dir):
        os.makedirs(stdout_dir)
        os.chmod(stdout_dir, 0o775)

    workers = []

    for i in range(num_gpus):
        args_list[-2] = '--rank={}'.format(i)
        stdout = None if i == 0 else open(
            os.path.join(stdout_dir, "GPU_{}.log".format(i)), "w")
        print(args_list)
        p = subprocess.Popen([str(sys.executable)]+args_list, stdout=stdout)
        workers.append(p)

    for p in workers:
        p.wait()


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('-c', '--config', type=str,
                        help='JSON file for configuration')
    parser.add_argument('-s', '--stdout_dir', type=str, default="exp/",
                        help='directory to save stoud logs')
    parser.add_argument('-a', '--args_str', type=str, default='',
                        help='double quoted string with space separated key value pairs')

    args = parser.parse_args()
    main(args.config, args.stdout_dir, args.args_str)

# *****************************************************************************
# Adapted from https://github.com/NVIDIA/waveglow/blob/master/distributed.py
# *****************************************************************************

# *****************************************************************************
#  Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.
#
#  Redistribution and use in source and binary forms, with or without
#  modification, are permitted provided that the following conditions are met:
#      * Redistributions of source code must retain the above copyright
#        notice, this list of conditions and the following disclaimer.
#      * Redistributions in binary form must reproduce the above copyright
#        notice, this list of conditions and the following disclaimer in the
#        documentation and/or other materials provided with the distribution.
#      * Neither the name of the NVIDIA CORPORATION nor the
#        names of its contributors may be used to endorse or promote products
#        derived from this software without specific prior written permission.
#
#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
#  ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
#  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
#  DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
#  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
#  (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
#  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
#  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
#  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
#  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# *****************************************************************************\

import os
import sys
import time
import subprocess
import argparse
import warnings
warnings.filterwarnings("ignore")

import torch

from distributed_util import *


def main(config, stdout_dir, args_str):
    args_list = ['train.py']
    args_list += args_str.split(' ') if len(args_str) > 0 else []

    args_list.append('--config={}'.format(config))

    num_gpus = torch.cuda.device_count()
    args_list.append('--num_gpus={}'.format(num_gpus))
    args_list.append("--group_name=group_{}".format(time.strftime("%Y_%m_%d-%H%M%S")))

    if not os.path.isdir(stdout_dir):
        os.makedirs(stdout_dir)
        os.chmod(stdout_dir, 0o775)

    workers = []

    for i in range(num_gpus):
        args_list[-2] = '--rank={}'.format(i)
        stdout = None if i == 0 else open(
            os.path.join(stdout_dir, "GPU_{}.log".format(i)), "w")
        print(args_list)
        p = subprocess.Popen([str(sys.executable)]+args_list, stdout=stdout)
        workers.append(p)

    for p in workers:
        p.wait()


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('-c', '--config', type=str,
                        help='JSON file for configuration')
    parser.add_argument('-s', '--stdout_dir', type=str, default="exp/",
                        help='directory to save stoud logs')
    parser.add_argument('-a', '--args_str', type=str, default='',
                        help='double quoted string with space separated key value pairs')

    args = parser.parse_args()
    main(args.config, args.stdout_dir, args.args_str)
# ***************************************************************************** # Adapted from https://github.com/NVIDIA/waveglow/blob/master/distributed.py # ***************************************************************************** # ***************************************************************************** #  Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved. # #  Redistribution and use in source and binary forms, with or without #  modification, are permitted provided that the following conditions are met: #      * Redistributions of source code must retain the above copyright #        notice, this list of conditions and the following disclaimer. #      * Redistributions in binary form must reproduce the above copyright #        notice, this list of conditions and the following disclaimer in the #        documentation and/or other materials provided with the distribution. #      * Neither the name of the NVIDIA CORPORATION nor the #        names of its contributors may be used to endorse or promote products #        derived from this software without specific prior written permission. # #  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND #  ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED #  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE #  DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY #  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES #  (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; #  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND #  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT #  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS #  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # *****************************************************************************\