code: def make_two_layer_functional_model(
      layer_generator: type_aliases.LayerGenerator,
      input_dims: Sequence[int],
      output_dims: Sequence[int],
  ) -> tf.keras.Model:
      """Creates a 2-layer sequential model."""
      inputs = tf.keras.Input(shape=input_dims)
      layer1 = layer_generator(input_dims, output_dims)
      temp1 = layer1(inputs)
      temp2 = tf.keras.layers.Dense(1)(temp1)
      outputs = reshape_and_sum(temp2)
      return tf.keras.Model(inputs=inputs, outputs=outputs)
  
imports: from collections.abc import Callable, MutableSequence, Sequence
  from typing import Optional
  import numpy
  import tensorflow
  import tensorflow.compat.v2
  from tensorflow_privacy.privacy.fast_gradient_clipping import clip_grads
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.fast_gradient_clipping import type_aliases
label_desc: Use image node_id 11 for calling a global function with example usage: make_two_layer_functional_model(layer_generator, input_dims, output_dims) and returns: tf