code: def image_input_shape(img_rows=28, img_cols=28):
      if tf.keras.backend.image_data_format() == "channels_first":
          return 1, img_rows, img_cols
      else:
          return img_rows, img_cols, 1
  
file_path: model-optimization/tensorflow_model_optimization/python/core/keras/testing/test_utils_mnist.py
imports: import numpy
  import tensorflow
  from tensorflow import keras
label_desc: Use image node_id 4 for calling a global function with example usage: image_input_shape(img_rows, img_cols) and returns: int,  img_rows,  img_cols, img_rows,  img_cols,  int