reuse common schemas in lale.lib.sklearn

[hirzel]

Many operators in lale.lib.sklearn have similar schemas for fit, predict, transform, predict_proba, etc. Similarly, there are some hyperparameters that occur in many of the operators in lale.lib.sklearn, such as random_state, n_jobs, etc. We could make our code base smaller and easier to maintain by defining such schemas only once in a file imported by each of the operators, and then plugging them in at the right place.

We already do something like that for lale.lib.aif360:

• schema reuse for fit and predict:

  lale/lale/lib/aif360/disparate_impact_remover.py

  Lines 120 to 122 in 1f03397

  	_input_fit_schema = _categorical_supervised_input_fit_schema
  	_input_transform_schema = _categorical_input_transform_schema
  	_output_transform_schema = _numeric_output_transform_schema

• schema reuse for common hyperparameters:

  lale/lale/lib/aif360/disparate_impact_remover.py

  Line 131 in 1f03397

  *_categorical_fairness_properties.keys(),

  and

  lale/lale/lib/aif360/disparate_impact_remover.py

  Line 138 in 1f03397

  **_categorical_fairness_properties,

[hirzel]

Started a file for this, only used by one operator so far: https://github.com/IBM/lale/blob/master/lale/lib/sklearn/_common_schemas.py

[shinnar]

tol is a good candidate for a shared parameter

[hirzel]

Did this for lale.lib.imblearn: https://github.com/IBM/lale/blob/master/lale/lib/imblearn/_common_schemas.py

[shinnar]

Did this for lale.lib.autoai_libs: https://github.com/IBM/lale/blob/master/lale/lib/autoai_libs/_common_schemas.py