Coral模型返回损坏的数据，直到python释放结果

Question

我们正在使用coral stick和我们创建的自定义网络（基于vgg作为主干）。 我们使用的edge tpu版本是2.11

网络返回2个输出：形状1*12*12*65和1*12*12*256。 我们用python这样称呼网络：

def _run_net(self, crop : np.ndarray):

    orig_w = crop.shape[1]
    orig_h = crop.shape[0]

    if orig_w != WIDTH or orig_h != HEIGHT:
        crop = cv2.resize(crop, (WIDTH, HEIGHT))
    image = crop.reshape(1, HEIGHT, WIDTH, 1)


    all_data = self.engine.RunInference(image.flatten())[1]
    tensor_sizes = self.engine.get_all_output_tensors_sizes()
    num_points = int(math.sqrt(tensor_sizes[0] / 65))
    raw_points = all_data[:tensor_sizes[0]]
    raw_points = raw_points.reshape((1, num_points, num_points, 65))
    raw_descriptors = all_data[tensor_sizes[0]:]
    raw_descriptors = raw_descriptors.reshape((1, num_points, num_points, 256))
    #Imprtant Note! the copy of raw points and desc here is a must, because as long as memory is held the net always return
    #the same results!!! this seems to be a bug in coral

    return (raw_points, raw_descriptors, orig_w, orig_h) #does not work

    #return (np.copy(raw_points), np.copy(raw_descriptors), orig_w, orig_h) #works ok!

在python调用原始的\u点和原始的\u描述符之前 对同一个网络（甚至引擎的新实例）的每次调用 将产生相同的输出。你知道吗