(
    op: "PlannedOperator",
    num_samples: Optional[int] = None,
    num_grids: Optional[float] = None,
    pgo: Optional[PGO] = None,
    data_schema: Dict[str, Any] = {},
)
return grids
Top level function: given a lale operator, returns a list of parameter grids
    suitable for passing to GridSearchCV.
    Note that you will need to wrap the lale operator for sklearn compatibility to call GridSearchCV
    directly.  The lale GridSearchCV wrapper takes care of that for you
Top level function: given a lale operator, returns a list of parameter grids
    suitable for passing to GridSearchCV.
    Note that you will need to wrap the lale operator for sklearn compatibility to call GridSearchCV
    directly.  The lale GridSearchCV wrapper takes care of that for you
Top level function : given a lale operator returns a list of parameter grids suitable for passing to GridSearchCV . Note that you will need to wrap the lale operator for sklearn compatibility to call GridSearchCV directly . The lale GridSearchCV wrapper takes care of that for you
def get_grid_search_parameter_grids(
    op: "PlannedOperator",
    num_samples: Optional[int] = None,
    num_grids: Optional[float] = None,
    pgo: Optional[PGO] = None,
    data_schema: Dict[str, Any] = {},
) -> List[Dict[str, List[Any]]]:
    """Top level function: given a lale operator, returns a list of parameter grids
    suitable for passing to GridSearchCV.
    Note that you will need to wrap the lale operator for sklearn compatibility to call GridSearchCV
    directly.  The lale GridSearchCV wrapper takes care of that for you
    """
    hp_grids = get_search_space_grids(
        op, num_grids=num_grids, pgo=pgo, data_schema=data_schema
    )
    grids = SearchSpaceGridstoGSGrids(hp_grids, num_samples=num_samples)
    if should_print_search_space("true", "all", "backend", "gridsearchcv"):
        name = op.name()
        if not name:
            name = "an operator"
        print(f"GridSearchCV grids for {name}:\n{gridsearchcv_grids_to_string(grids)}")

    return grids
def get_grid_search_parameter_grids ( op : "PlannedOperator" , num_samples : Optional [ int ] = None , num_grids : Optional [ float ] = None , pgo : Optional [ PGO ] = None , data_schema : Dict [ str , Any ] = { } , ) -> List [ Dict [ str , List [ Any ] ] ] : hp_grids = get_search_space_grids ( op , num_grids = num_grids , pgo = pgo , data_schema = data_schema ) grids = SearchSpaceGridstoGSGrids ( hp_grids , num_samples = num_samples ) if should_print_search_space ( "true" , "all" , "backend" , "gridsearchcv" ) : name = op . name ( ) if not name : name = "an operator" print ( f"GridSearchCV grids for {name}:\n{gridsearchcv_grids_to_string(grids)}" ) return grids