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.
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docstr: Save the large model.
  The function returns a ModelProto,
  the current one if the model did not need any modification,
  a modified copy of it if it required changes such as giving file names
  to every external tensor.
  
  Arguments:
      file_path: model file
      all_tensors_to_one_file: saves all large tensors in one file or
          one file per lerge tensor
  
  Returns:
      the saved ModelProto
docstr_tok: ["Save","the","large","model",".","The","function","returns","a","ModelProto",",","the","current","one","if","the","model","did","not","need","any","modification",",","a","modified","copy","of","it","if","it","required","changes","such","as","giving","file","names","to","every","external","tensor",".","Arguments",":","file_path",":","model","file","all_tensors_to_one_file",":","saves","all","large","tensors","in","one","file","or","one","file","per","lerge","tensor","Returns",":","the","saved","ModelProto"]
code: def save(
      self,
      file_path: str,
      all_tensors_to_one_file: bool = False,
  ) -> onnx.ModelProto:
      """Save the large model.
      The function returns a ModelProto,
      the current one if the model did not need any modification,
      a modified copy of it if it required changes such as giving file names
      to every external tensor.
  
      Arguments:
          file_path: model file
          all_tensors_to_one_file: saves all large tensors in one file or
              one file per lerge tensor
  
      Returns:
          the saved ModelProto
      """
      return self._save_external(
          file_path, all_tensors_to_one_file=all_tensors_to_one_file
      )
  
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 11 for calling the ModelContainer obj's underlying member method code with example usage: obj.save(file_path, all_tensors_to_one_file) and returns: self