code: def get_shape(inputs: Any) -> str:
      if not isinstance(inputs, (tuple, list)):
          inputs = (inputs,)
  
      out = []
      for x in inputs:
          if isinstance(x, SparseTensor):
              out.append(str(list(x.sizes())))
          elif hasattr(x, "size"):
              out.append(str(list(x.size())))
      return ", ".join(out)
  
file_path: pytorch_geometric/torch_geometric/nn/summary.py
imports: from collections import defaultdict
  from typing import Any, List, Optional, Union
  import torch
  from torch.jit import ScriptModule
  from torch.nn import Module
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.nn.dense.linear import is_uninitialized_parameter
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: get_shape(inputs) and returns: str