When the ray cluster runs for a long time or execute many tasks, log files can be large, such as monitor.err, full of could not find ip for client xxxx. I find parameters logging_level, logging_format and log_to_driver in ray.init(). Is there a way to restrict the size of log files by default, like using logging.handlers.RotatingFileHandler and set maxBytes?

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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.

See optuna/optuna#1913.

Some type hints are not complying to the latest mypy == 0.790 and should be addressed.

How do i resume training for text classification?

Create gifs with folder structure after AutoML training and add them to the Readme

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