sample.py 文件源码

def encoder(args, model):
    latent_dim = args.latent_dim
    data, charset = load_dataset(args.data, split = False)

    if os.path.isfile(args.model):
        model.load(charset, args.model, latent_rep_size = latent_dim)
    else:
        raise ValueError("Model file %s doesn't exist" % args.model)

    x_latent = model.encoder.predict(data)
    if args.save_h5:
        h5f = h5py.File(args.save_h5, 'w')
        h5f.create_dataset('charset', data = charset)
        h5f.create_dataset('latent_vectors', data = x_latent)
        h5f.close()
    else:
        np.savetxt(sys.stdout, x_latent, delimiter = '\t')