code: def build_linear_keras_functional_model(input_shape, weights):
      inputs = tf.keras.Input(shape=input_shape, name="feature")
      layer = tf.keras.layers.Dense(
          1,
          use_bias=False,
          kernel_initializer=tf.keras.initializers.Constant(weights),
      )
      outputs = layer(inputs)
      return tf.keras.Model(inputs=inputs, outputs=outputs)
  
file_path: neural-structured-learning/neural_structured_learning/keras/adversarial_regularization_multi_device_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import neural_structured_learning.configs
  from neural_structured_learning.keras import adversarial_regularization
  import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: build_linear_keras_functional_model(input_shape, weights) and returns: tf