code: def test_mapping_syntax():
      model = InferenceModel()
  
      mapping_layer = MappingLayer(model)
  
      mapping_layer.set_dependency("model.val.item.d_1", torch.ones(1))
      mapping_layer.set_dependency(
          "model.val.item.d_2", torch.ones(1) * 2
      )
  
      assert isinstance(mapping_layer.multi_depend, torch.Tensor)
  
      for i in range(16):
          mapping_layer.set_dependency(
              f"model.list_vals.{i}.d", torch.ones(1) * i
          )
          if i != 16 - 1:
              assert mapping_layer.is_populated == False
  
      assert isinstance(mapping_layer.list_depend, InferenceParameter)
      assert mapping_layer.is_populated == True
  
imports: import pytest
  import torch
  from deepspeed.inference.v2.allocator import on_device
  from deepspeed.inference.v2.inference_parameter import InferenceParameter
  from deepspeed.inference.v2.model_implementations.parameter_base import ParameterBase, ParamList
  from deepspeed.inference.v2.model_implementations.layer_container_base import LayerContainer
label_desc: Use image node_id 1 for calling a global function with example usage: test_mapping_syntax() without return types