Reputation: 2854
I am using Estimator to train my net. I want to monitor with Tensorboard. Blogs for Estimator claim things like:
"The training will output information like the global step, loss,
and accuracy over time on the terminal output. Besides this, the
Experiment and Estimator framework will log certain statistics to
be visualized by TensorBoard."
https://medium.com/onfido-tech/higher-level-apis-in-tensorflow-67bfb602e6c0
My process does indeed create and event file, but there is nothing in it.
These tags are in checkpoints/1504359209.469093:
audio -
histograms -
images -
scalars -
tensor -
What controls which scalars etc. Estimator writes, and how often it writes them?
Upvotes: 0
Views: 991
Reputation: 2854
Thank you. That's very helpful.
I have, already got it working using the default scalars, but your suggestions will allow me to add new ones.
In my case, the problem was in the data input. I copied existing code which uses a DataSet. Here is my code
# Build dataset iterator
dataset = tf.contrib.data.Dataset.from_tensor_slices(
# dataset = tf.contrib.data.Dataset.from_tensors(
(fingerprints_placeholder, labels_placeholder))
#dataset = dataset.repeat(None) # Infinite iterations
#dataset = dataset.shuffle(buffer_size=10000)
dataset = dataset.batch(batch_size)
iterator = dataset.make_initializable_iterator()
Notice the commented out lines. For some reason they cause the code to run forever with no output. Removing them allowed everything to work as advertised.
Upvotes: 0
Reputation: 36
Firstly, the documentation is not very clear on this point. To avoid writing a tutorial, here are a few points that you might find helpful, although I should say I am not quite clear on how your code is currently set up.
Upvotes: 1