ERROR:interpret.utils.all:Could not unify data of type: <class 'dask.array.core.Array'>

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-53-b5e1d33190e1> in <module>
      1 model = create_model()
      2 
----> 3 fold_models, train_preds, valid_preds = model_cv(model)

<ipython-input-48-178d0374bff6> in model_cv(model)
     17 
---> 18             fold_model = sklearn.clone(model).fit(x_train_fold, y_train_fold)
     19 

/opt/anaconda/envs/ebm/lib/python3.8/site-packages/interpret/glassbox/ebm/ebm.py in fit(self, X, y)
    744         # TODO: PK don't overwrite self.feature_names here (scikit-learn rules), and it's also confusing to
    745         #       user to have their fields overwritten.  Use feature_names_out_ or something similar
--> 746         X, y, self.feature_names, _ = unify_data(
    747             X, y, self.feature_names, self.feature_types, missing_data_allowed=False
    748         )

/opt/anaconda/envs/ebm/lib/python3.8/site-packages/interpret/utils/all.py in unify_data(data, labels, feature_names, feature_types, missing_data_allowed)
    325         msg = "Could not unify data of type: {0}".format(type(data))
    326         log.error(msg)
--> 327         raise ValueError(msg)
    328 
    329     new_labels = unify_vector(labels)

ValueError: Could not unify data of type: <class 'dask.array.core.Array'>