examples/model_selection/Trails/internal/ml/model_selection/src/eva_engine/phase1/algo/singa_ms/cnn_ms/autograd/cifar10_multiprocess.py

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from resnet_cifar10 import *
import multiprocessing
import sys

if __name__ == '__main__':

    # Generate a NCCL ID to be used for collective communication
    nccl_id = singa.NcclIdHolder()

    # Configure the number of GPUs to be used
    world_size = int(sys.argv[1])

    # Testing the experimental partial-parameter update asynchronous training
    partial_update = True

    process = []
    for local_rank in range(0, world_size):
        process.append(
            multiprocessing.Process(target=train_cifar10,
                                    args=(True, local_rank, world_size, nccl_id,
                                          partial_update)))

    for p in process:
        p.start()