我想应用多处理模块来加快numpy数组元素的更新。

这是一个在制品代码...

counter = Value(c_int)  # defaults to 0
# counter_lock = Lock()
def increment():
    with counter.get_lock():
        counter.value += 1
    print(f'\r{counter.value}/{total} has been completed.',end='')

total = len(data_paths)

# Assign number to the data
data_w_num=list(enumerate(data_paths))

def prepare_data(data_w_num):
    i,imgs = data_w_num

    try:
        with data.get_lock():
            data[i] = np.array([preprocess(read_img(imgs[m]),input_shape[1:]) for m in ['t1','t2','t1ce','flair']],dtype=np.float32)
        with data.get_lock():
            labels[i] = preprocess_label(read_img(imgs['seg']),input_shape[1:])[None,...] 

        # Print the progress bar
        increment()

    except Exception as e:
        print(f'Something went wrong with {imgs["t1"]},skipping...\n Exception:\n{str(e)}')
        return


with Pool(cpu_count()) as p:
    print('total: ' + f'{total}')
    r = p.map_async(prepare_data,data_w_num)
    print("Processing...")
    r.wait()
    print('\nAll processes were done.')

data_paths变量如下：

但是它不起作用。 错误消息是“只能将size-1数组转换为Python标量。” 而且我不确定如何应用多重处理。

如果您能帮助我解决这个问题，将非常高兴。