def METHOD_NAME():
    """Download and partitions the MNIST dataset."""
    (x_train, y_train), testset = tf.keras.datasets.mnist.load_data()
    partitions = []
    # We keep all partitions equal-sized in this example
    partition_size = math.floor(len(x_train) / NUM_CLIENTS)
    for cid in range(NUM_CLIENTS):
        # Split dataset into non-overlapping NUM_CLIENT partitions
        idx_from, idx_to = int(cid) * partition_size, (int(cid) + 1) * partition_size
        partitions.append((x_train[idx_from:idx_to] / 255.0, y_train[idx_from:idx_to]))
    return partitions, testset