How to use the lale.operators function in lale

'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.lale.hyperopt_cv.html',
    'description': 'SMAC, the optimizer used inside auto-weka and auto-sklearn.',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['estimator'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_predict': _input_predict_schema,
        'output_predict': _output_predict_schema}}

lale.docstrings.set_docstrings(SMACImpl, _combined_schemas)

SMAC = lale.operators.make_operator(SMACImpl, _combined_schemas)

'$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Passes the data through unchanged.',
    'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.lale.no_op.html',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema}}

lale.docstrings.set_docstrings(NoOpImpl, _combined_schemas)

NoOp = lale.operators.make_operator(NoOpImpl, _combined_schemas)

.. _Imputer: https://scikit-learn.org/0.20/modules/generated/sklearn.preprocessing.Imputer.html#sklearn-preprocessing-imputer""",
    'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.autoai_libs.num_imputer.html',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema}}

lale.docstrings.set_docstrings(NumImputerImpl, _combined_schemas)

NumImputer = lale.operators.make_operator(NumImputerImpl, _combined_schemas)

""",
    'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.random_forest_regressor.html',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['estimator', 'regressor'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_predict': _input_predict_schema,
        'output_predict': _output_predict_schema}}

lale.docstrings.set_docstrings(RandomForestRegressorImpl, _combined_schemas)

RandomForestRegressor = lale.operators.make_operator(RandomForestRegressorImpl, _combined_schemas)

'$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Combined schema for expected data and hyperparameters.',
    'documentation_url': 'https://scikit-learn.org/0.20/modules/generated/sklearn.preprocessing.RobustScaler#sklearn-preprocessing-robustscaler',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema},
}
lale.docstrings.set_docstrings(RobustScalerImpl, _combined_schemas)
RobustScaler = lale.operators.make_operator(RobustScalerImpl, _combined_schemas)

def _get_state(op: 'lale.operators.Operator') -> str:
    if isinstance(op, lale.operators.TrainedOperator):
        return 'trained'
    if isinstance(op, lale.operators.TrainableOperator):
        return 'trainable'
    if isinstance(op, lale.operators.PlannedOperator) or isinstance(op, lale.operators.OperatorChoice):
        return 'planned'
    if isinstance(op, lale.operators.Operator):
        return 'metamodel'
    raise TypeError(f'Expected lale.operators.Operator, got {type(op)}.')

'$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Combined schema for expected data and hyperparameters.',
    'documentation_url': 'https://scikit-learn.org/0.20/modules/generated/sklearn.kernel_approximation.RBFSampler#sklearn-kernel_approximation-rbfsampler',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema},
}
lale.docstrings.set_docstrings(RBFSamplerImpl, _combined_schemas)
RBFSampler = lale.operators.make_operator(RBFSamplerImpl, _combined_schemas)

'$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Combined schema for expected data and hyperparameters.',
    'documentation_url': 'https://scikit-learn.org/0.20/modules/generated/sklearn.linear_model.Ridge#sklearn-linear_model-ridge',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['estimator'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_predict': _input_predict_schema,
        'output_predict': _output_predict_schema},
}
lale.docstrings.set_docstrings(RidgeImpl, _combined_schemas)
Ridge = lale.operators.make_operator(RidgeImpl, _combined_schemas)

'properties': {
    'hyperparams': _hyperparams_schema,
    'input_fit': _input_fit_schema,
    'input_transform': _input_transform_schema,
    'output_transform': _output_transform_schema,
    'input_predict': _input_predict_schema,
    'output_predict': _output_predict_schema,
    'input_predict_proba': _input_predict_proba_schema,
    'output_predict_proba': _output_predict_proba_schema,
    'input_decision_function': _input_decision_function_schema,
    'output_decision_function': _output_decision_function_schema
}}

lale.docstrings.set_docstrings(RepeatedEditedNearestNeighboursImpl, _combined_schemas)

RepeatedEditedNearestNeighbours = lale.operators.make_operator(RepeatedEditedNearestNeighboursImpl, _combined_schemas)

'$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Combined schema for expected data and hyperparameters.',
    'documentation_url': 'https://scikit-learn.org/0.20/modules/generated/sklearn.decomposition.SparsePCA#sklearn-decomposition-sparsepca',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema},
}
lale.docstrings.set_docstrings(SparsePCAImpl, _combined_schemas)
SparsePCA = lale.operators.make_operator(SparsePCAImpl, _combined_schemas)