Documentation on Tensorboard HParams plugin

I am looking for documentation on Tensorboard HParams plugin, in particular, I want to know about hp.Discrete & hp.RealInterval and if there are also some other functions like these available. I tried to look for documentation on these but could not find anything. I would be thankful if someone can share a link of the documentation.

[thisismygitrepo]

I highly recommend that these details be added to the notebook, cause the it leaves much to be desired.

[wchargin]

This is described in the text and code of section 3:

For simplicity, use a grid search: try all combinations of the discrete parameters and just the lower and upper bounds of the real-valued parameter. For more complex scenarios, it might be more effective to choose each hyperparameter value randomly (this is called a random search).

and

  for dropout_rate in (HP_DROPOUT.domain.min_value, HP_DROPOUT.domain.max_value):
    ...

You can see that we’re explicitly picking the two endpoints of the domain only. You could instead use something like

  for dropout_rate in tf.linspace(
      HP_DROPOUT.domain.min_value,
      HP_DROPOUT.domain.max_value,
      11,
  ):
    ...

for a higher-resolution grid search, or

  for dropout_rate_iteration in range(10):
    dropout_rate = HP_DROPOUT.domain.sample_uniform()
    ...

for a random search.

More generally, the TensorBoard hparams plugin doesn’t tune the model for you. You bring your own tuner, or write a simple one inline, as in the tutorial; the hparams dashboard lets you visualize the results of tuning along with the rest of your metrics.