df_batches.py

def batches(X, y, batch_size, randomise):
    rows = X.shape[0]
    i = np.arange(rows)
    if randomise:
        np.random.shuffle(i)
    splits = rows / batch_size
    for x_batch, y_batch in zip(np.array_split(X[i, ], splits),
                                np.array_split(y[i], splits)):
        yield x_batch, y_batch