()
return parser.parse_args()
Helper function parsing the command line options
    @retval ArgumentParser
Helper function parsing the command line options
Helper function parsing the command line options
def parse_args():
    """
    Helper function parsing the command line options
    @retval ArgumentParser
    """
    parser = ArgumentParser(description="PyTorch distributed training launch "
                                        "helper utilty that will spawn up "
                                        "multiple distributed processes")

    # Optional arguments for the launch helper
    parser.add_argument("--nnodes", type=int, default=1,
                        help="The number of nodes to use for distributed "
                             "training")
    parser.add_argument("--node_rank", type=int, default=0,
                        help="The rank of the node for multi-node distributed "
                             "training")
    parser.add_argument("--nproc_per_node", type=int, default=1,
                        help="The number of processes to launch on each node, "
                             "for GPU training, this is recommended to be set "
                             "to the number of GPUs in your system so that "
                             "each process can be bound to a single GPU.")
    parser.add_argument("--master_addr", default="127.0.0.1", type=str,
                        help="Master node (rank 0)'s address, should be either "
                             "the IP address or the hostname of node 0, for "
                             "single node multi-proc training, the "
                             "--master_addr can simply be 127.0.0.1")
    parser.add_argument("--master_port", default=29500, type=int,
                        help="Master node (rank 0)'s free port that needs to "
                             "be used for communciation during distributed "
                             "training")

    # positional
    parser.add_argument("training_script", type=str,
                        help="The full path to the single GPU training "
                             "program/script to be launched in parallel, "
                             "followed by all the arguments for the "
                             "training script")

    # rest from the training program
    parser.add_argument('training_script_args', nargs=REMAINDER)
    return parser.parse_args()
def parse_args ( ) : parser = ArgumentParser ( description = "PyTorch distributed training launch " "helper utilty that will spawn up " "multiple distributed processes" ) # Optional arguments for the launch helper parser . add_argument ( "--nnodes" , type = int , default = 1 , help = "The number of nodes to use for distributed " "training" ) parser . add_argument ( "--node_rank" , type = int , default = 0 , help = "The rank of the node for multi-node distributed " "training" ) parser . add_argument ( "--nproc_per_node" , type = int , default = 1 , help = "The number of processes to launch on each node, " "for GPU training, this is recommended to be set " "to the number of GPUs in your system so that " "each process can be bound to a single GPU." ) parser . add_argument ( "--master_addr" , default = "127.0.0.1" , type = str , help = "Master node (rank 0)'s address, should be either " "the IP address or the hostname of node 0, for " "single node multi-proc training, the " "--master_addr can simply be 127.0.0.1" ) parser . add_argument ( "--master_port" , default = 29500 , type = int , help = "Master node (rank 0)'s free port that needs to " "be used for communciation during distributed " "training" ) # positional parser . add_argument ( "training_script" , type = str , help = "The full path to the single GPU training " "program/script to be launched in parallel, " "followed by all the arguments for the " "training script" ) # rest from the training program parser . add_argument ( 'training_script_args' , nargs = REMAINDER ) return parser . parse_args ( )