code: def apply_input_props_using_example(
      graph: Graph, example_input: List[Any]
  ):
      """
      Applies properties for each tensor in the graph inputs
      using the example supplied.
      """
      graph_inputs = list(graph.inputs())
      if len(graph_inputs) == 0:
          return
  
      # Strip self args off for methods
      in_0 = graph_inputs[0]
      if (
          isinstance(in_0.type(), torch._C.ClassType)
          and in_0.debugName() == "self"
      ):
          graph_inputs = graph_inputs[1:]
  
      if not len(graph_inputs) == len(example_input):
          raise RuntimeError(
              "Number of inputs in graph does not match number of inputs in the example"
          )
  
      for i, (graph_i, example_i) in enumerate(
          zip(graph_inputs, example_input)
      ):
          if example_i is None:
              continue  # Skip the type check
  
          if isinstance(example_i, torch.Tensor) != isinstance(
              graph_i.type(), TensorType
          ):
              raise RuntimeError(
                  f"Input {i} does not match type of example",
                  graph_i,
                  example_i,
              )
  
          if isinstance(example_i, torch.Tensor):
              graph_i.setType(TensorType.create_from_tensor(example_i))
  
imports: from typing import Any, List
  import torch
  from torch import TensorType
  from torch._C import Graph
label_desc: Use image node_id 1 for calling a global function with example usage: apply_input_props_using_example(graph, example_input) without return types