def METHOD_NAME(self, epoch: int):
    """
    This method is called in every "step" of the search.
    Args:
        epoch: epoch number
    """
    # For reference, this is the code inside new_epoch in RandomSearch:
    # model = torch.nn.Module()
    # model.arch = self.search_space.clone()
    # model.arch.sample_random_architecture(dataset_api=self.dataset_api)
    # model.accuracy = model.arch.query(
    #     self.performance_metric,
    #     self.dataset,
    #     epoch=self.fidelity,
    #     dataset_api=self.dataset_api,
    # )
    # self.sampled_archs.append(model)
    # self._update_history(model)
    # All it does 
    ###########################################################
    ##################### START TODO ##########################
    # Write your logic here
    # Also feel free to write new methods in this class
    ##################### END TODO  ##########################
    ##########################################################
    self.sampled_archs.append(model) # This line is required. Add your chosen model to sampled_archs here.