Fixes for broken tests

                    + ["y_means", "y_stds"])

    pred_y_df = pd.DataFrame(columns=column_names)

    #batch_size = self.model_params["batch_size"]

    #for (X_batch, y_batch, w_batch, ids_batch) in dataset.iterbatches(batch_size):

    for (X_batch, y_batch, w_batch, ids_batch) in dataset.itershards():

    batch_size = self.model_params["batch_size"]

    for (X_batch, y_batch, w_batch, ids_batch) in dataset.iterbatches(batch_size):

      # HACK(JG): This was a hack to perform n-fold averaging of y_pred on

      # a given X_batch.  If fit_transformers exist, we will apply them to

MUV_task_types = {task: "Classification" for task in MUV_tasks}

params_dict = { 

    "batch_size": [32],

    "batch_size": [None],

    "data_shape": [train_dataset.get_data_shape()],

}