code: def test_call_without_circular_padding(self):
      context_features = {
          "context_feature_1": tf.constant([[1], [0]], dtype=tf.float32)
      }
      example_features = {
          "example_feature_1": tf.constant(
              [[[1], [0], [-1]], [[0], [1], [0]]], dtype=tf.float32
          )
      }
      mask = tf.constant(
          [[True, True, False], [True, False, False]], dtype=tf.bool
      )
      expected_context_features = {
          "context_feature_1": tf.constant(
              [[1], [1], [1], [0], [0], [0]], dtype=tf.float32
          )
      }
      expected_example_features = {
          "example_feature_1": tf.constant(
              [[1], [0], [-1], [0], [1], [0]], dtype=tf.float32
          )
      }
      (
          flattened_context_features,
          flattened_example_features,
      ) = layers.FlattenList(circular_padding=False)(
          inputs=(context_features, example_features, mask)
      )
      self.assertAllClose(
          expected_context_features, flattened_context_features
      )
      self.assertAllClose(
          expected_example_features, flattened_example_features
      )
  
imports: import tensorflow
  from tensorflow_ranking.python.keras import layers
label_desc: Use image node_id 2 for calling the FlattenListTest obj's underlying member method code with example usage: obj.test_call_without_circular_padding() without return types