Python错误：‘int’对象没有属性值

Question

def get_model(point_cloud, is_training, bn_decay=None):
    """ Classification PointNet, input is BxNx3, output Bx40 """
    batch_size = point_cloud.get_shape()[0].value
    num_point = point_cloud.get_shape()[1].value
    end_points = {}**
    
    with tf.variable_scope('transform_net1') as sc:
        transform = input_transform_net(point_cloud, is_training, bn_decay, K=3)
    point_cloud_transformed = tf.matmul(point_cloud, transform)
    print(point_cloud_transformed)
    input_image = tf.expand_dims(point_cloud_transformed, -1)
    print(input_image)

    net = conv2d(input_image, 64, [1,3],
                         padding='VALID', stride=[1,1],
                         bn=True, is_training=is_training,
                         scope='conv1', bn_decay=bn_decay)
    net = conv2d(net, 64, [1,1],
                         padding='VALID', stride=[1,1],
                         bn=True, is_training=is_training,
                         scope='conv2', bn_decay=bn_decay)

    with tf.variable_scope('transform_net2') as sc:
        transform = feature_transform_net(net, is_training, bn_decay, K=64)
    end_points['transform'] = transform
    net_transformed = tf.matmul(tf.squeeze(net, axis=[2]), transform)
    net_transformed = tf.expand_dims(net_transformed, [2])

    net = conv2d(net_transformed, 64, [1,1],
                         padding='VALID', stride=[1,1],
                         bn=True, is_training=is_training,
                         scope='conv3', bn_decay=bn_decay)
    net = conv2d(net, 128, [1,1],
                         padding='VALID', stride=[1,1],
                         bn=True, is_training=is_training,
                         scope='conv4', bn_decay=bn_decay)
    net = conv2d(net, 1024, [1,1],
                         padding='VALID', stride=[1,1],
                         bn=True, is_training=is_training,
                         scope='conv5', bn_decay=bn_decay)
    # Symmetric function: max pooling
    net = max_pool2d(net, [num_point,1],
                             padding='VALID', scope='maxpool')
                             
    net = tf.reshape(net, [batch_size, -1])
    net = fully_connected(net, 512, bn=True, is_training=is_training,
                                  scope='fc1', bn_decay=bn_decay)
    net = dropout(net, keep_prob=0.7, is_training=is_training,
                          scope='dp1')
    net = fully_connected(net, 256, bn=True, is_training=is_training,
                                  scope='fc2', bn_decay=bn_decay)
    net = dropout(net, keep_prob=0.7, is_training=is_training,
                          scope='dp2')
    net = fully_connected(net, 40, activation_fn=None, scope='fc3')

    return net, end_points

Answer 1

我的问题是，我正在执行一个允许提取点云显着性的代码，它显示以下错误:错误：‘int’对象没有函数的属性'value‘：def get_model(point_cloud，is_training，bn_decay=None)：“”分类PointNet，输入是BxNx3，输出Bx40“batch_size = point_cloud.get_shape().value num_point = point_cloud.get_shape()1.value end_points = {}”