real.py 文件源码

def mnist(digit='all', n_samples=0, return_gt=False):
    mnist = sk_datasets.fetch_mldata('MNIST original')
    X = mnist.data
    gt = mnist.target

    if digit == 'all':  # keep all digits
        pass
    else:
        X = X[gt == digit, :]
        gt = gt[gt == digit]

    if n_samples > len(X):
        raise ValueError('Requesting {} samples'
                         'from {} datapoints'.format(n_samples, len(X)))
    if n_samples > 0:
        np.random.seed(0)
        selection = np.random.randint(len(X), size=n_samples)
        X = X[selection, :]
        gt = gt[selection]

        idx = np.argsort(gt)
        X = X[idx, :]
        gt = gt[idx]

    if return_gt:
        return X, gt
    else:
        return X