2-train_dcgan.py 文件源码

def gen_samples(n, nbatch=128):
    samples = []
    labels = []
    n_gen = 0
    for i in range(n/nbatch):
        ymb = floatX(OneHot(np_rng.randint(0, 10, nbatch), ny))
        zmb = floatX(np_rng.uniform(-1., 1., size=(nbatch, nz)))
        xmb = _gen(zmb, ymb)
        samples.append(xmb)
        labels.append(np.argmax(ymb, axis=1))
        n_gen += len(xmb)
    n_left = n-n_gen
    ymb = floatX(OneHot(np_rng.randint(0, 10, n_left), ny))
    zmb = floatX(np_rng.uniform(-1., 1., size=(n_left, nz)))
    xmb = _gen(zmb, ymb)
    samples.append(xmb)
    labels.append(np.argmax(ymb, axis=1))
    return np.concatenate(samples, axis=0), np.concatenate(labels, axis=0)