utils.py 文件源码

def load_cifar10(path, num_training=1000, num_test=1000):
    Xs, ys = [], []
    for batch in range(1, 6):
        f = open(os.path.join(path, "data_batch_{0}".format(batch)), 'rb')
        data = cPickle.load(f, encoding='iso-8859-1')
        f.close()
        X = data["data"].reshape(10000, 3, 32, 32).astype("float64")
        y = np.array(data["labels"])
        Xs.append(X)
        ys.append(y)
    f = open(os.path.join(CIFAR10_PATH, "test_batch"), 'rb')
    data = cPickle.load(f, encoding='iso-8859-1')
    f.close()
    X_train, y_train = np.concatenate(Xs), np.concatenate(ys)
    X_test = data["data"].reshape(10000, 3, 32, 32).astype("float")
    y_test = np.array(data["labels"])
    X_train, y_train = X_train[range(
        num_training)], y_train[range(num_training)]
    X_test, y_test = X_test[range(num_test)], y_test[range(num_test)]
    mean = np.mean(X_train, axis=0)
    std = np.std(X_train)
    X_train /= 255.0
    X_test /= 255.0
    return (X_train, y_train), (X_test, y_test)