class_docstr: Implements an API to store large tensors outside the main ModelProto,
  it avoids copying large initializers when defining the model and these initializers
  are never serialized through protobuf.
  No tensor is stored on disk until the user explicitly saves the model.
class_docstr_tok: ["Implements","an","API","to","store","large","tensors","outside","the","main","ModelProto",",","it","avoids","copying","large","initializers","when","defining","the","model","and","these","initializers","are","never","serialized","through","protobuf",".","No","tensor","is","stored","on","disk","until","the","user","explicitly","saves","the","model","."]
code: def check_model(self):
      if self.model_proto is not None:
          onnx.checker.check_model(self.model_proto)
  
imports: from __future__ import annotations
  import os
  import sys
  from typing import Any, Iterable
  import numpy
  import onnx
  import onnx.external_data_helper
  import onnx.helper
label_desc: Use image node_id 2 for calling the ModelContainer obj's underlying member method code with example usage: obj.check_model() without return types