text: import os
  
  import numpy as np
  import tensorflow as tf
  from tensorflow.python.framework import graph_io
  from tensorflow.python.framework import graph_util
  
  model_name = "2inputs"
  output_file = os.path.join(
      os.path.dirname(os.path.realpath(__file__)),
      "..",
      "models",
      "{}.pb".format(model_name),
  )
  input_data_file = os.path.join(
      os.path.dirname(os.path.realpath(__file__)),
      "..",
      "models",
      "{}_input_example.npy".format(model_name),
  )
  
  input_size = 16
  output_size = 2
  input_shape = [1, input_size]
  x1 = tf.placeholder(tf.float32, shape=input_shape)
  x2 = tf.placeholder(tf.float32, shape=input_shape)
  
  x = x1 + x2
  w1 = tf.get_variable(
      "w1", [input_size, output_size], initializer=tf.random_normal_initializer()
  )
  b1 = tf.get_variable("b1", [output_size], initializer=tf.random_normal_initializer())
  x = tf.matmul(x, w1) + b1
  y = tf.sigmoid(x)
  
  pred_node_names = ["output"]
  pred = [tf.identity(y, name=pred_node_names[0])]
  
  sess = tf.Session()
  sess.run(tf.global_variables_initializer())
  
  constant_graph = graph_util.convert_variables_to_constants(
      sess, sess.graph.as_graph_def(), pred_node_names
  )
  
  frozen = graph_util.remove_training_nodes(constant_graph)
  
  graph_io.write_graph(frozen, ".", output_file, as_text=False)
  print("saved the frozen graph (ready for inference) at: ", output_file)
  
  data = np.random.standard_normal(input_shape)
  np.save(input_data_file, data)
  