code: def test_feature_spec_input_creator(self):
      context_feature_spec = {
          "c_ragged": tf.io.RaggedFeature(dtype=tf.int64)
      }
      example_feature_spec = {
          "fixed_len": tf.io.FixedLenFeature(
              shape=(1,), dtype=tf.float32, default_value=0.0
          ),
          "var_len": tf.io.VarLenFeature(dtype=tf.string),
          "ragged": tf.io.RaggedFeature(dtype=tf.string),
      }
      input_creator = model_lib.FeatureSpecInputCreator(
          context_feature_spec, example_feature_spec
      )
      context_inputs, example_inputs = input_creator()
      self.assertAllEqual(
          context_inputs["c_ragged"].shape, [None, None]
      )
      self.assertAllEqual(
          example_inputs["fixed_len"].shape, [None, None, 1]
      )
      self.assertAllEqual(
          example_inputs["var_len"].shape, [None, None, 1]
      )
      self.assertAllEqual(
          example_inputs["ragged"].shape, [None, None, None]
      )
  
imports: from absl.testing import parameterized
  import tensorflow
  from google.protobuf import text_format
  from tensorflow_ranking.python import data
  from tensorflow_ranking.python.keras import feature
  from tensorflow_ranking.python.keras import losses
  from tensorflow_ranking.python.keras import metrics
  from tensorflow_ranking.python.keras import model
  from tensorflow_ranking.python.keras import network
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 1 for calling the InputCreatorTest obj's underlying member method code with example usage: obj.test_feature_spec_input_creator() without return types