def _get_summary_data(self) -> list[tuple[str, list[str]]]:
        """Makes a summary listing with:

        Layer Name, Layer Type, Number of Parameters, Input Sizes, Output Sizes, Model Size

        """
        arrays = [
            (" ", list(map(str, range(len(self._layer_summary))))),
            ("Name", self.layer_names),
            ("Type", self.layer_types),
            ("Params", list(map(get_human_readable_count, self.param_nums))),
            ("Params per Device", list(map(get_human_readable_count, self.parameters_per_layer))),
            ("Mode", ["train" if mode else "eval" for mode in self.training_modes]),
        ]
        if self._model.example_input_array is not None:
            arrays.append(("In sizes", [str(x) for x in self.in_sizes]))
            arrays.append(("Out sizes", [str(x) for x in self.out_sizes]))

        total_leftover_params = self.total_parameters - self.total_layer_params
        if total_leftover_params > 0:
            self._add_leftover_params_to_summary(arrays, total_leftover_params)

        return arrays
Makes a summary listing with:

        Layer Name, Layer Type, Number of Parameters, Input Sizes, Output Sizes, Model Size

        
src/lightning/pytorch/utilities/model_summary/model_summary_deepspeed.py