hyperparameter-optimization

What happened + What you expected to happen

When initializing a Ray Trainer, we provide a logdir argument, and the __init__ method of the Trainer stores it as a logdir class variable.

Then, when creating a Trainable with Trainer.to_tune_trainable(), it in-turn calls _create_tune_trainable(), which does not use self.logdir. So when tune_function is defined inside `_create_tu

Bug with GPU Model

Currently, while using pruning methods like TaylorFOWeight Pruner, If I use a model on GPU for getting the metrics (as calculated for getting masks), it fails on line while creating masks. The reason why it fails i

Motivation

optuna/optuna#3651 has introduced chunking to send too long tag/metric/params to avoid mlflow's API limit. Hopefully, mlflow itself will handle this case by mlflow/mlflow#6052, so Optuna doesn't need the logic introduced by #3651 with the next mlflow version anymore.

Description

Revert all changes introduced by #3651 after the n

The program throws an error at runtime, how can this error be solved?

[ERROR] [2022-06-27 14:13:51,391:asyncio.events] 
Traceback (most recent call last):
  File "/home/xumaoyuan/.virtualenvs/lib/python3.8/site-packages/distributed/utils.py", line 761, in wrapper
    return await func(*args, **kwargs)
  File "/home/xumaoyuan/.virtualenvs/lib/python3.8/site-packages/distributed/clie

Add PECOS model to TabularPredictor.

If you'd like to work on this, please respond to this GitHub issue.

It is recommended to follow the custom model tutorial for implementing the model into AutoGluon.

Use case

Polyaxon tracking can be used to automatically log all information generated by Ludwig.

We should probably think about adding support for Polyaxon's tracking module in Ludwig contrib.

I trained models on Windows, then I tried to use them on Linux, however, I could not load them due to an incorrect path joining. During model loading, I got learner_path in the following format experiments_dir/model_1/100_LightGBM\\learner_fold_0.lightgbm. The last two slashes were incorrectly concatenated with the rest part of the path. In this regard, I would suggest adding something like `l

ray.init(n_cpus=16)
should be
ray.init(num_cpus=16) in the documentation page
https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML#parallel-tuning

Describe the bug
Sometimes we init using a class that is not our parent. We should not do this.

To Reproduce
See: https://app.codacy.com/gh/Neuraxio/Neuraxle/issues?&filters=W3siaWQiOiJMYW5ndWFnZSIsInZhbHVlcyI6W119LHsiaWQiOiJDYXRlZ29yeSIsInZhbHVlcyI6WyJDb2RlU3R5bGUiXX0seyJpZCI6IkxldmVsIiwidmFsdWVzIjpbXX0seyJpZCI6IlBhdHRlcm4iLCJ2YWx1ZXMiOlsiMTcxNCJdfSx7ImlkIjoiQXV0aG9yIiwidmFsdWVzIjpb