code: def _get_onnx_outputs_info(
      model,
  ):  # type: (...) -> Dict[Text, EdgeInfo]
      """
      Takes in an onnx model and returns a dictionary
      of onnx output names mapped to a tuple that is (output_name, type, shape)
      """
      if isinstance(model, _string_types):
          onnx_model = onnx.load(model)
      elif isinstance(model, onnx.ModelProto):
          onnx_model = model
  
      graph = onnx_model.graph
      onnx_output_dict = {}
      for o in graph.output:
          out = _input_from_onnx_input(o)
          onnx_output_dict[out[0]] = out
      return onnx_output_dict
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from typing import Any, Text, Dict, Tuple
  from onnx import ModelProto
  from onnx.backend.base import Backend
  from six import string_types
  from ._backend_rep import CoreMLRep
  from ._converter import convert
  import onnx
  from ._graph import _input_from_onnx_input, EdgeInfo
label_desc: Use image node_id 1 for calling a global function with example usage: _get_onnx_outputs_info(model) and returns: onnx_output_dict