code: def test_double_mapping_syntax():
      model = InferenceModel()
  
      mapping_layer = DoubleMappingLayer(model)
      mapping_layer.set_dependency("model.val.item.d_1", torch.ones(1))
  
      # The single parameter setting should immediately make the parameter finalized
      # and the whole layer initialized.
      assert isinstance(mapping_layer.multi_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 3 for calling a global function with example usage: test_double_mapping_syntax() without return types