code: def test_make_identity_transform_fn(self):
      features = {
          "context": tf.convert_to_tensor(  # Input size: (batch_size=2, num_features=2).
              value=[[1.0, 1.0], [1.0, 1.0]]
          ),
          "per_example": tf.convert_to_tensor(
              value=[[[10.0]], [[10.0]]]
          ),
      }
      transform_fn = feature_lib.make_identity_transform_fn(["context"])
      context_features, per_example_features = transform_fn(features, 1)
      self.assertCountEqual(["context"], context_features)
      self.assertAllEqual(
          [[1.0, 1.0], [1.0, 1.0]], context_features["context"]
      )
  
      self.assertCountEqual(["per_example"], per_example_features)
      self.assertAllEqual(
          [[[10.0]], [[10.0]]], per_example_features["per_example"]
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow import estimator
  from google.protobuf import text_format
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow_ranking.python import feature
label_desc: Use image node_id 1 for calling the FeatureLibTest obj's underlying member method code with example usage: obj.test_make_identity_transform_fn() without return types