utils.py 文件源码

def prepare_mixture_gm_data(arguments):
    dataset = []

    arguments.L2 = 2
    arguments.L1 = 2
    arguments.K = 200
    sig0 = 5
    sig = 0.1

    num_means = arguments.num_means
    means = 5*torch.randn(num_means, arguments.L2) 
    arguments.means = means.numpy()

    N = 2000

    mixinds = torch.multinomial(torch.ones(num_means), N, replacement=True) 
    obsnoise = torch.randn(N, arguments.L2) 

    data = means[mixinds] + obsnoise
    inp = torch.randn(N, arguments.L1) 

    dataset1 = TensorDataset(inp, data, [1]*N)
    datasetmix = dataset1 

    kwargs = {'num_workers': 1, 'pin_memory': True} if arguments.cuda else {}
    loader1 = data_utils.DataLoader(dataset1, batch_size=arguments.batch_size, shuffle=False, **kwargs)
    loader_mix = data_utils.DataLoader(datasetmix, batch_size=arguments.batch_size, shuffle=False, **kwargs)

    return loader1, loader_mix