code: def on_predict(self, data):
      try:
          if self._dataframeColumns is not None:
              data = pd.DataFrame(data, columns=self._dataframeColumns)
              data = data.astype(dict(self._dfdtypes))
          if self._is_classifier:
              prediction = convert_to_list(
                  self._model.predict_proba(data), EXP_VIZ_ERR_MSG
              )
          else:
              prediction = convert_to_list(
                  self._model.predict(data), EXP_VIZ_ERR_MSG
              )
          return {WidgetRequestResponseConstants.DATA: prediction}
      except Exception:
          return {
              WidgetRequestResponseConstants.ERROR: "Model threw exception"
              " while predicting...",
              WidgetRequestResponseConstants.DATA: [],
          }
  
file_path: responsible-ai-toolbox/raiwidgets/raiwidgets/explanation_dashboard_input.py
imports: import warnings
  import numpy
  import pandas
  from raiutils.data_processing import convert_to_list, serialize_json_safe
  from raiutils.models import is_classifier
  from .constants import ErrorMessages
  from .error_handling import _format_exception
  from .explanation_constants import ExplanationDashboardInterface, WidgetRequestResponseConstants
label_desc: Use image node_id 2 for calling the ExplanationDashboardInput obj's underlying member method code with example usage: obj.on_predict(data) and returns: dict, dict