Describe your feature request

It is already possible to give actors a name: https://docs.ray.io/en/master/actors.html#named-actors and to retrieve the actor handle via ray.get_actor("some_name").
It would however be very handy to have some kind of ray.list_named_actors() API method to get a list/dict of all currently available named actors.
It can be useful for:

• Better debugging

What would you like to be added: As title

Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.

**Without this feature, how does current nni

with the Power Transformer.

Motivation

From following resources, the search space of examples/xgboost_simple.py seems not to be practical.

• https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/
• https://www.youtube.com/watch?v=VC8Jc9_lNoY
• https://www.amazon.co.jp/dp/B07YTDBC3Z/

Description

Improve the search space of examples/xgboost_simple.py.

The AutoML crashes if all models have error. It should be handled more gently.

The example of crash:

AutoML directory: AutoML_88
The task is multiclass_classification with evaluation metric logloss
AutoML will use algorithms: ['MLP']
AutoML steps: ['simple_algorithms', 'default_algorithms', 'not_so_random', 'hill_climbing_1', 'hill_climbing_2']
Skip simple_algorithms because no parame

If enter_data() is called with the same train_path twice in a row and the data itself hasn't changed, a new Dataset does not need to be created.

We should add a column which stores some kind of hash of the actual data. When a Dataset would be created, if the metadata and data hash are exactly the same as an existing Dataset, nothing should be added to the ModelHub database and the existing

Need further investigation.

Related:

• Epistimio/orion#335
• Epistimio/orion#359