Keras:将Tensorboard与train_on_batch()结合使用 [英] Keras: use Tensorboard with train_on_batch()

问题描述

对于keras函数fit()和fit_generator()，可以通过将keras.callbacks.TensorBoard对象传递给函数来实现张量板可视化.对于train_on_batch()函数，显然没有可用的回调.在这种情况下，keras中还有其他选项可用来创建Tensorboard吗?

For the keras functions fit() and fit_generator() there is the possibility of tensorboard visualization by passing a keras.callbacks.TensorBoard object to the functions. For the train_on_batch() function there obviously are no callback available. Are there other options in keras to create a Tensorboard in this case?

推荐答案

我认为当前唯一的选择是使用tensorflow代码.在此stackoverflow答案中，我找到了一种手动创建张量板日志的方法.因此，带有keras train_on_batch()的代码示例可能如下所示:

I think that currently the only option is to use tensorflow code. In this stackoverflow answer I found a way to create a tensorboard log manually. Thus a code sample with the keras train_on_batch() could look like this:

# before training init writer (for tensorboard log) / model
writer = tf.summary.FileWriter(...)
model = ...

# train model
loss = model.train_on_batch(...)
summary = tf.Summary(value=[tf.Summary.Value(tag="loss", 
                                             simple_value=value), ])
writer.add_summary(summary)

注意:对于Tensorboard中的此示例，您必须选择水平轴"RELATIVE"，因为不会传递任何步骤到夏季.

Note: For this example in Tensorboard you have to choose the Horizontal Axis "RELATIVE" as no step is passed to the summery.

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