code: def test_getitem_from_tuple_handler():
      model = GetItemFromTupleModel()
      tracer = ColoTracer()
      # graph():
      #     %input_1 : torch.Tensor [#users=1] = placeholder[target=input]
      #     %split : [#users=1] = call_function[target=torch.functional.split](args = (%conv2d, 2), kwargs = {dim: 0})
      #     %getitem : [#users=1] = call_function[target=operator.getitem](args = (%split, 1), kwargs = {})
      #     return getitem
      meta_args = {
          "input": torch.rand(4, 4, 64, 64).to("meta"),
      }
      graph = tracer.trace(model, meta_args=meta_args)
      gm = ColoGraphModule(model, graph)
      shape_prop_pass(gm, *meta_args.values())
      physical_mesh_id = torch.arange(0, 4)
  
      mesh_shape = (2, 2)
      device_mesh = DeviceMesh(physical_mesh_id, mesh_shape)
      input_node = list(graph.nodes)[0]
      split_node = list(graph.nodes)[1]
      getitem_node = list(graph.nodes)[2]
      input_strategies_vector = StrategiesVector(input_node)
      getitem_strategies_vector = StrategiesVector(getitem_node)
      split_strategies_vector = StrategiesVector(split_node)
  
      # build handler
      input_handler = PlaceholderHandler(
          node=input_node,
          device_mesh=device_mesh,
          strategies_vector=input_strategies_vector,
          placeholder_option="replicated",
      )
      input_handler.register_strategy(compute_resharding_cost=False)
      setattr(input_node, "strategies_vector", input_strategies_vector)
      split_handler = DefaultReshapeHandler(
          node=split_node,
          device_mesh=device_mesh,
          strategies_vector=split_strategies_vector,
      )
      split_handler.register_strategy(compute_resharding_cost=False)
      setattr(split_node, "strategies_vector", split_strategies_vector)
      getitem_handler = GetItemHandler(
          node=getitem_node,
          device_mesh=device_mesh,
          strategies_vector=getitem_strategies_vector,
      )
      getitem_handler.register_strategy(compute_resharding_cost=False)
      setattr(
          getitem_node, "strategies_vector", getitem_strategies_vector
      )
  
      # check operation data mapping
      mapping = getitem_handler.get_operation_data_mapping()
  
      for name, op_data in mapping.items():
          op_data: OperationData
          # make sure they have valid values
          assert op_data.data is not None
  
      assert mapping["input"].name == "split"
      assert mapping["input"].type == OperationDataType.ARG
      assert mapping["input"].logical_shape == (
          torch.Size([2, 4, 64, 64]),
          torch.Size([2, 4, 64, 64]),
      )
  
      assert mapping["index"].name == "index"
      assert isinstance(mapping["index"].data, int)
      assert mapping["index"].type == OperationDataType.ARG
  
      assert mapping["output"].name == "getitem"
      assert mapping["output"].data.is_meta
      assert mapping["output"].data.shape == torch.Size([2, 4, 64, 64])
      assert mapping["output"].type == OperationDataType.OUTPUT
  
      # getitem is a following strategy handler, so the number of strategies is equal to the predecessor node.
      assert len(getitem_strategies_vector) == len(
          split_strategies_vector
      )
  
imports: import pytest
  import torch
  import torch.nn
  from colossalai._analyzer.fx.graph_module import ColoGraphModule
  from colossalai._analyzer.fx.passes.shape_prop import shape_prop_pass
  from colossalai._analyzer.fx.tracer.tracer import ColoTracer
  from colossalai.auto_parallel.tensor_shard.node_handler.default_reshape_handler import DefaultReshapeHandler
  from colossalai.auto_parallel.tensor_shard.node_handler.getitem_handler import GetItemHandler
  from colossalai.auto_parallel.tensor_shard.node_handler.linear_handler import LinearFunctionHandler
  from colossalai.auto_parallel.tensor_shard.node_handler.placeholder_handler import PlaceholderHandler
  from colossalai.auto_parallel.tensor_shard.sharding_strategy import OperationData, OperationDataType, StrategiesVector
  from colossalai.device.device_mesh import DeviceMesh
  from colossalai.initialize import launch
  from colossalai.logging import disable_existing_loggers
  from colossalai.testing import clear_cache_before_run, parameterize, rerun_if_address_is_in_use, spawn
  from colossalai.testing.pytest_wrapper import run_on_environment_flag
  from tests.test_auto_parallel.test_tensor_shard.test_node_handler.utils import numerical_test_for_node_strategy
label_desc: Use image node_id 3 for calling a global function with example usage: test_getitem_from_tuple_handler() without return types