code: def _make_model(
      self,
      nodes: list[NodeProto],
      inputs: list[ValueInfoProto],
      outputs: list[ValueInfoProto],
      initializer: list[TensorProto],
      value_info: list[ValueInfoProto],
      local_functions: list[FunctionProto],
  ) -> ModelProto:
      name = "Extracted from {" + self.graph.name + "}"
      graph = onnx.helper.make_graph(
          nodes,
          name,
          inputs,
          outputs,
          initializer=initializer,
          value_info=value_info,
      )
  
      meta = {
          "ir_version": self.model.ir_version,
          "opset_imports": self.model.opset_import,
          "producer_name": "onnx.utils.extract_model",
          "functions": local_functions,
      }
      return onnx.helper.make_model(graph, **meta)
  
file_path: onnx/onnx/utils.py
imports: from __future__ import annotations
  import os
  import onnx.checker
  import onnx.helper
  import onnx.shape_inference
  from onnx import FunctionProto, ModelProto, NodeProto, TensorProto, ValueInfoProto
label_desc: Use image node_id 10 for calling the Extractor obj's underlying member method code with example usage: obj._make_model(nodes, inputs, outputs, initializer, value_info, local_functions) and returns: onnx