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_concat_tensor = tf.constant(
          [
              [[1.0, 1.0], [1.0, 0.0], [1.0, -1.0]],
              [[0.0, 0.0], [0.0, 1.0], [0.0, 0.0]],
          ],
          dtype=tf.float32,
      )
      concat_tensor = layers.ConcatFeatures(circular_padding=False)(
          (context_features, example_features, mask)
      )
      self.assertAllClose(expected_concat_tensor, concat_tensor)
  
imports: import tensorflow
  from tensorflow_ranking.python.keras import layers
label_desc: Use image node_id 2 for calling the ConcatFeaturesTest obj's underlying member method code with example usage: obj.test_call_without_circular_padding() without return types