code: def get_transforms_config(self, node, params):
      _, sublayer_template = self.template
  
      params["n_sublayers"] = node.attributes["n_sublayers"]
      params["n_in_features"] = node.attributes["n_in_features"][0]
      params["n_out_features"] = node.attributes["n_out_features"][-1]
  
      sublayer_configs = []
      for il in range(node.attributes["n_sublayers"] - 1, -1, -1):
          sub_params = {"index": node.index, "il": il}
  
          for p in [
              "n_in_features",
              "n_propagate",
              "n_aggregators",
              "n_out_features",
          ]:
              sub_params[p] = node.attributes[p][il]
  
          for wname, weights in node._sublayer_weights[il].items():
              sub_params[wname] = weights.name
              sub_params[f"{wname}_t"] = weights.type.name
              sub_params[f"{wname}_size"] = weights.data_length
  
          if il != node.attributes["n_sublayers"] - 1:
              sub_params["next"] = il + 1
          else:
              sub_params["next"] = 0
  
          sublayer_configs.append(
              sublayer_template.format(**sub_params)
          )
  
      params["sublayer_configs"] = "\n".join(sublayer_configs)
  
imports: import numpy
  from hls4ml.backends.fpga.fpga_types import APTypeConverter
  from hls4ml.backends.template import FunctionCallTemplate, LayerConfigTemplate
  from hls4ml.model.layers import GarNet, GarNetStack
  from hls4ml.model.types import FixedPrecisionType
label_desc: Use image node_id 2 for calling the GarNetStackConfigTemplate obj's underlying member method code with example usage: obj.get_transforms_config(node, params) without return types