code: def test_with_masking_layer_layernorm_rnn():
      inputs = np.random.random((2, 3, 4))
      targets = np.abs(np.random.random((2, 3, 5)))
      targets /= targets.sum(axis=-1, keepdims=True)
      model = keras.models.Sequential()
      model.add(keras.layers.Masking(input_shape=(3, 4)))
      model.add(
          keras.layers.RNN(
              LayerNormSimpleRNNCell(units=5),
              return_sequences=True,
              unroll=False,
          )
      )
      model.compile(
          loss="categorical_crossentropy", optimizer="rmsprop"
      )
      model.fit(inputs, targets, epochs=1, batch_size=2, verbose=1)
  
imports: import numpy
  import tensorflow.keras
  from tensorflow_addons.rnn import LayerNormSimpleRNNCell
label_desc: Use image node_id 2 for calling a global function with example usage: test_with_masking_layer_layernorm_rnn() without return types