code: def init_submodule(self, module: Module, target: str) -> Module:
      # Replicate each module for each node type or edge type.
      has_node_level_target = bool(
          self.find_by_target(
              f"{target}.{key2str(self.metadata[0][0])}"
          )
      )
      has_edge_level_target = bool(
          self.find_by_target(
              f"{target}.{key2str(self.metadata[1][0])}"
          )
      )
  
      if not has_node_level_target and not has_edge_level_target:
          return module
  
      module_dict = torch.nn.ModuleDict()
      for key in self.metadata[int(has_edge_level_target)]:
          module_dict[key2str(key)] = copy.deepcopy(module)
          if len(self.metadata[int(has_edge_level_target)]) <= 1:
              continue
          if hasattr(module, "reset_parameters"):
              module_dict[key2str(key)].reset_parameters()
          elif (
              sum(
                  [
                      is_uninitialized_parameter(p) or p.numel()
                      for p in module.parameters()
                  ]
              )
              > 0
          ):
              warnings.warn(
                  f"'{target}' will be duplicated, but its parameters "
                  f"cannot be reset. To suppress this warning, add a "
                  f"'reset_parameters()' method to '{target}'"
              )
  
      return module_dict
  
imports: import copy
  import warnings
  from collections import defaultdict, deque
  from typing import Any, Dict, Optional, Tuple, Union
  import torch
  from torch.nn import Module
  from torch_geometric.nn.dense.linear import is_uninitialized_parameter
  from torch_geometric.nn.fx import Transformer, get_submodule
  from torch_geometric.typing import EdgeType, Metadata, NodeType
  from torch_geometric.utils.hetero import check_add_self_loops, get_unused_node_types
label_desc: Use image node_id 11 for calling the ToHeteroTransformer obj's underlying member method code with example usage: obj.init_submodule(module, target) and returns: module_dict, module