metacluster.py 文件源码

def subset_iterator(X, m, repeats=1):
    '''
    Iterates over array X in chunks of m, repeat number of times.
    Each time the order of the repeat is randomly generated.
    '''

    N, dim = X.shape
    progress = tqdm(total=repeats * int(N / m))

    for i in range(repeats):

        indices = np.random.permutation(N)

        for idx in np.array_split(indices, N // m):
            yield X[idx][:]
            progress.update()

    progress.close()