Exemplo n.º 1
0
def experiment(variant):
    beta = variant["beta"]
    representation_size = variant["representation_size"]
    m = ConvVAE(representation_size, beta=beta)
    for epoch in range(10):
        m.train_epoch(epoch)
        m.test_epoch(epoch)
        m.dump_samples(epoch)
Exemplo n.º 2
0
def experiment(variant):
    c = joblib.load(
        "/Users/ashvin/data/s3doodad/ashvin/vae/point2d-conv/run0/id0/params.pkl"
    )
    import pdb
    pdb.set_trace()

    beta = variant["beta"]
    representation_size = variant["representation_size"]
    m = ConvVAE(representation_size, beta=beta)
    for epoch in range(10):
        m.train_epoch(epoch)
        m.test_epoch(epoch)
        m.dump_samples(epoch)
Exemplo n.º 3
0
def experiment(variant):
    if variant["use_gpu"]:
        gpu_id = variant["gpu_id"]
        ptu.set_gpu_mode(True)
        ptu.set_device(gpu_id)

    beta = variant["beta"]
    representation_size = variant["representation_size"]
    train_data, test_data = get_data(10000)
    m = ConvVAE(train_data,
                test_data,
                representation_size,
                beta=beta,
                use_cuda=True,
                input_channels=3)
    for epoch in range(50):
        m.train_epoch(epoch)
        m.test_epoch(epoch)
        m.dump_samples(epoch)