无法在 tensorboard 中使用 summary.merge 进行单独的训练和评估摘要

Question

我正在尝试使用 tensorboard 来观察卷积神经网络的学习。我很好地使用 tf.summary.merge_all 函数来创建合并摘要。但是，我想跟踪训练和测试数据的准确性和损失。这个post有用：Logging training and validation loss in tensorboard.

为了让事情更容易处理，我想将我的摘要合并成两个合并的摘要，一个用于训练，一个用于验证。（我最终会添加更多的东西，比如图像权重等）我试着按照来自 tensorboard tf.summary.merge 的描述。我无法让它工作，我找不到任何工作示例来帮助我理解我哪里出错了。

with tf.name_scope('accuracy'):
    correct_prediction = tf.equal(tf.argmax(y_logits, 1), tf.argmax(y, 1))
    accuracy = tf.reduce_mean(tf.cast(correct_prediction, 'float'))
    tf.summary.scalar('accuracy', accuracy)
    tf.summary.scalar('train_accuracy', accuracy)

with tf.name_scope('Cost'):
    cross_entropy = tf.reduce_mean(
        tf.nn.softmax_cross_entropy_with_logits(logits=y_logits, labels=y))
    opt = tf.train.AdamOptimizer()
    optimizer = opt.minimize(cross_entropy)
    grads = opt.compute_gradients(cross_entropy, [b_fc_loc2])
    tf.summary.scalar('cost', cross_entropy)
    tf.summary.scalar('train_cost', cross_entropy)


with tf.Session() as sess:
    writer = tf.summary.FileWriter('./logs/mnistlogs/1f', sess.graph)
    sess.run(tf.global_variables_initializer())
    merged = tf.summary.merge([cost, accuracy])

这会导致以下错误：

InvalidArgumentError (see above for traceback): Could not parse one of the summary inputs [[Node: Merge/MergeSummary = MergeSummary[N=2, _device="/job:localhost/replica:0/task:0/cpu:0"](Merge/MergeSummary/inputs_0, Merge/MergeSummary/inputs_1)]]

我想知道为什么这不起作用，以及如何找到解决方案，感谢任何有效的示例。

Answer 1

我明白了。我需要在合并之前给出摘要名称。下面的代码解决了这个问题：

with tf.name_scope('Cost'):
    cross_entropy = tf.reduce_mean(
            tf.nn.softmax_cross_entropy_with_logits(logits=y_logits, labels=y))
    opt = tf.train.AdamOptimizer(learning_rate=0.000003)
    optimizer = opt.minimize(cross_entropy)
    grads = opt.compute_gradients(cross_entropy, [b_fc_loc2])
    cost_sum = tf.summary.scalar('val_cost', cross_entropy)
    training_cost_sum = tf.summary.scalar('train_cost', cross_entropy)


with tf.name_scope('accuracy'):
    correct_prediction = tf.equal(tf.argmax(y_logits, 1), tf.argmax(y, 1))
    accuracy = tf.reduce_mean(tf.cast(correct_prediction, 'float'))
    train_accuracy = accuracy
    accuracy_sum = tf.summary.scalar('val_accuracy', accuracy)
    training_accuracy_sum = tf.summary.scalar('train_accuracy', accuracy)


with tf.Session() as sess:
    writer = tf.summary.FileWriter('./logs/{}/{}'.format(session_name, run_num), sess.graph)
    sess.run(tf.global_variables_initializer())
    train_merged = tf.summary.merge([training_accuracy_sum, training_cost_sum])

无法在 tensorboard 中使用 summary.merge 进行单独的训练和评估摘要

Unable to use summary.merge in tensorboard for separate training and evaluation summaries

python

tensorflow

tensorboard