Question

我试图了解Tensorflow，并且我看到了一个官方的例子，即Cifar-10模型。

在cifar10.py中，在inference（）中，您可以看到以下几行：

with tf.variable_scope('softmax_linear') as scope:
    weights = _variable_with_weight_decay('weights', [192, NUM_CLASSES],
                                      stddev=1/192.0, wd=0.0)
    biases = _variable_on_cpu('biases', [NUM_CLASSES],
                          tf.constant_initializer(0.0))
    softmax_linear = tf.add(tf.matmul(local4, weights), biases, name=scope.name)
    _activation_summary(softmax_linear)

scope.name应该是softmax_linear，它应该是节点的名称。我使用以下行保存了图形原型（它与教程不同）：

with tf.Graph().as_default():
    global_step = tf.Variable(0, trainable=False)

    # Get images and labels
    images, labels = cifar10.distorted_inputs()


    # Build a Graph that computes the logits predictions from the
    # inference model.
    logits = cifar10.inference(images)

    # Calculate loss.
    loss = cifar10.loss(logits, labels)

    # Build a Graph that trains the model with one batch of examples and
    # updates the model parameters.
    train_op = cifar10.train(loss, global_step)

    # Create a saver.
    saver = tf.train.Saver(tf.global_variables())

    # Build the summary operation based on the TF collection of Summaries.
    summary_op = tf.summary.merge_all()

    # Build an initialization operation to run below.
    init = tf.global_variables_initializer()

    # Start running operations on the Graph.
    sess = tf.Session(config=tf.ConfigProto(
        log_device_placement=FLAGS.log_device_placement))
    sess.run(init)

    # save the graph
    tf.train.write_graph(sess.graph_def, FLAGS.train_dir, 'model.pbtxt')  

    ....

但我无法在model.pbtxt中看到名为softmax_linear的节点。我究竟做错了什么？我只想输出节点的名称来导出图形。

Answer 1

运营商名称不会是"softmax_linear"。 tf.name_scope()前缀名称的运算符名称，以/分隔。每个运营商都有自己的名称。例如，如果你写

with tf.name_scope("foo"):
   a = tf.constant(1, name="bar")

然后常量将具有名称"foo/bar"。

希望有所帮助！

Tensorflow：Cifar-10模型中的输出节点名称是什么？

1 个答案: