code: def print_all_node_names(model_file, is_BrainScript=True):
      loaded_model = load_model(model_file)
      if is_BrainScript:
          loaded_model = combine([loaded_model.outputs[0]])
      node_list = graph.depth_first_search(
          loaded_model, lambda x: x.is_output
      )
      print("printing node information in the format")
      print("node name (tensor shape)")
      for node in node_list:
          print(node.name, node.shape)
  
file_path: CNTK/Examples/Image/GettingStarted/07_Deconvolution_Visualizer.py
imports: from __future__ import print_function
  import os, sys
  import numpy
  import argparse
  from cntk import load_model
  from cntk.ops import combine
  from cntk.io import MinibatchSource, CTFDeserializer, StreamDef, StreamDefs
  from PIL import Image
  from cntk.logging import graph
label_desc: Use image node_id 1 for calling a global function with example usage: print_all_node_names(model_file, is_BrainScript) without return types