with tf.name_scope(name):
conv2d = tf.layers.conv2d(inputs,
output_channel,
kernel_size,
padding = padding,
activation = None,
name = ‘conv2d’)

老师我想问一下，为什么上一段代码在 with tf.name_scope(name): 定义完名字后，conv2d中的 name=name + ‘/conv2d’ 改成 name=‘conv2d’ 会报错，而下一段代码with tf.name_scope(name):定义完名字后的各个变量的名字可以直接写成像 ‘mean’ ‘min’ ‘max’ ‘histogram’ 的形式

with tf.name_scope(name):
mean = tf.reduce_mean(var)
with tf.name_scope(‘stddev’):
stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean)))
tf.summary.scalar(‘mean’, mean)
tf.summary.scalar(‘stddev’, stddev)
tf.summary.scalar(‘min’, tf.reduce_min(var))
tf.summary.scalar(‘max’, tf.reduce_max(var))
tf.summary.histogram(‘histogram’, var)