code: def suggest_next_locations(self, context = None, pending_X = None, ignored_X = None):
          
          self.model_parameters_iterations = None
          self.num_acquisitions = 0
          self.context = context
          self._update_model(self.normalization_type)
  
          suggested_locations = self._compute_next_evaluations(pending_zipped_X = pending_X, ignored_zipped_X = ignored_X)
  
          return suggested_locations
docs: Run a single optimization step and return the next locations to evaluate the objective.
          Number of suggested locations equals to batch_size.
  
          :param context: fixes specified variables to a particular context (values) for the optimization run (default, None).
          :param pending_X: matrix of input configurations that are in a pending state (i.e., do not have an evaluation yet) (default, None).
          :param ignored_X: matrix of input configurations that the user black-lists, i.e., those configurations will not be suggested again (default, None).