code: def build_sequential_model():
      "Define the model architecture."
  
      return keras.Sequential(
          [
              keras.layers.InputLayer(input_shape=(28, 28)),
              keras.layers.Reshape(target_shape=(28, 28, 1)),
              keras.layers.Conv2D(
                  filters=12, kernel_size=(3, 3), activation="relu"
              ),
              keras.layers.MaxPooling2D(pool_size=(2, 2)),
              keras.layers.Flatten(),
              keras.layers.Dense(10),
          ]
      )
  
file_path: model-optimization/tensorflow_model_optimization/python/examples/clustering/keras/mnist/mnist_cnn.py
imports: from __future__ import print_function
  import datetime
  import os
  from absl import app
  from absl import flags
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_callbacks
label_desc: Use image node_id 2 for calling a global function with example usage: build_sequential_model() and returns: keras