code: def check_getitem_from_tensor_handler(
      rank, getitem_index, world_size, port
  ):
      disable_existing_loggers()
      launch(
          config={},
          rank=rank,
          world_size=world_size,
          host="localhost",
          port=port,
          backend="nccl",
      )
  
      model = GetItemFromTensorModel(getitem_index=getitem_index)
  
      input = torch.rand(8, 16, 64, 32).to("cuda")
      other = torch.rand(64, 32).to("cuda")
      # index of linear node in computation graph
      node_index = 2
      # total number of linear strategies
      strategy_number = 23
  
      physical_mesh_id = torch.arange(0, 4)
      mesh_shape = (2, 2)
      device_mesh = DeviceMesh(
          physical_mesh_id, mesh_shape, init_process_group=True
      )
  
      numerical_test_for_node_strategy(
          model=model,
          device_mesh=device_mesh,
          node_index=node_index,
          strategy_number=strategy_number,
          input_args=[input, other],
          meta_arg_names=["input", "other"],
          node_type="following",
      )
  
      tracer = ColoTracer(bias_addition_split=True)
      meta_args = {
          "input": torch.rand(8, 16, 64, 32).to("meta"),
          "other": torch.rand(64, 32).to("meta"),
      }
      graph = tracer.trace(model, meta_args=meta_args)
  
      gm = ColoGraphModule(model, graph)
      shape_prop_pass(gm, *list(meta_args.values()))
      linear_mod_node = list(graph.nodes)[2]
      getitem_mod_node = list(graph.nodes)[3]
      getitem_strategies_vector = StrategiesVector(getitem_mod_node)
      linear_strategies_vector = StrategiesVector(linear_mod_node)
  
      # build handler
      linear_handler = LinearFunctionHandler(
          node=linear_mod_node,
          device_mesh=device_mesh,
          strategies_vector=linear_strategies_vector,
      )
      linear_handler.register_strategy(compute_resharding_cost=False)
      setattr(
          linear_mod_node, "strategies_vector", linear_strategies_vector
      )
      getitem_handler = GetItemHandler(
          node=getitem_mod_node,
          device_mesh=device_mesh,
          strategies_vector=getitem_strategies_vector,
      )
  
      getitem_handler.register_strategy(compute_resharding_cost=False)
      # 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
  
      # getitem is a following strategy handler, so the number of strategies is equal to the predecessor node.
      assert len(getitem_strategies_vector) == len(
          linear_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 1 for calling a global function with example usage: check_getitem_from_tensor_handler(rank, getitem_index, world_size, port) without return types