code: def build_keras_model(keras_module, num_classes):
      input_shape = (28, 28, 1)
  
      model = keras_module.Sequential(
          [
              keras_module.Input(shape=input_shape),
              keras_module.layers.Conv2D(
                  32, kernel_size=(3, 3), activation="relu"
              ),
              keras_module.layers.MaxPooling2D(pool_size=(2, 2)),
              keras_module.layers.Conv2D(
                  64, kernel_size=(3, 3), activation="relu"
              ),
              keras_module.layers.MaxPooling2D(pool_size=(2, 2)),
              keras_module.layers.Flatten(),
              keras_module.layers.Dense(
                  num_classes, activation="softmax"
              ),
          ]
      )
  
      model.summary()
      return model
  
file_path: keras/integration_tests/numerical_test.py
imports: import keras
  import numpy
  from tensorflow import keras
label_desc: Use image node_id 2 for calling a global function with example usage: build_keras_model(keras_module, num_classes) and returns: model