code: def group_node_placeholder(
      input_dict: Dict[NodeType, Tensor], type2id: Dict[NodeType, int]
  ) -> Tensor:
      inputs = [input_dict[key] for key in type2id.keys()]
      return (
          inputs[0] if len(inputs) == 1 else torch.cat(inputs, dim=-2)
      )
  
imports: import copy
  import warnings
  from typing import Any, Dict, List, Optional, Union
  import torch
  from torch import Tensor
  from torch.nn import Module, Parameter
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.nn.dense import Linear
  from torch_geometric.nn.fx import Transformer
  from torch_geometric.typing import EdgeType, Metadata, NodeType, SparseTensor
  from torch_geometric.utils.hetero import get_unused_node_types
label_desc: Use image node_id 5 for calling a global function with example usage: group_node_placeholder(input_dict, type2id) and returns: unknown