code: def testTukeyHHAnalyzersWithNDDenseInputs(self):
      def analyzer_fn(inputs):
          a = inputs["a"]
  
          return {
              "tukey_location": tft.tukey_location(
                  a, reduce_instance_dims=False
              ),
              "tukey_scale": tft.tukey_scale(
                  a, reduce_instance_dims=False
              ),
              "tukey_hl": tft.tukey_h_params(
                  a, reduce_instance_dims=False
              )[0],
              "tukey_hr": tft.tukey_h_params(
                  a, reduce_instance_dims=False
              )[1],
          }
  
      input_data_values = [
          516,
          -871,
          737,
          415,
          584,
          583,
          152,
          479,
          576,
          409,
          591,
          844,
          -16,
          508,
          669,
          617,
          502,
          532,
          517,
          479,
      ]
      input_data = []
      for idx, v in enumerate(input_data_values):
          input_data.append(
              {
                  "a": [
                      [v, -input_data_values[-1 - idx]],
                      [2 * v, -2 * input_data_values[-1 - idx]],
                  ]
              }
          )
      input_metadata = tft.DatasetMetadata.from_feature_spec(
          {"a": tf.io.FixedLenFeature([2, 2], tf.float32)}
      )
      expected_outputs = {
          "tukey_location": np.array(
              [
                  [526.89355, -526.89355],
                  [2.0 * 526.89355, -2.0 * 526.89355],
              ],
              np.float32,
          ),
          "tukey_scale": np.array(
              [
                  [116.73997, 116.73997],
                  [2.0 * 116.73997, 2.0 * 116.73997],
              ],
              np.float32,
          ),
          "tukey_hl": np.array(
              [[0.6629082, 0.11148566], [0.6629082, 0.11148566]],
              np.float32,
          ),
          "tukey_hr": np.array(
              [[0.11148566, 0.6629082], [0.11148566, 0.6629082]],
              np.float32,
          ),
      }
  
      self.assertAnalyzerOutputs(
          input_data,
          input_metadata,
          analyzer_fn,
          expected_outputs,
          desired_batch_size=20,
          # Runs the test deterministically on the whole batch.
          beam_pipeline=beam.Pipeline(),
      )
  
file_path: transform/tensorflow_transform/beam/tukey_hh_params_integration_test.py
imports: import itertools
  import apache_beam
  import numpy
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform.beam import impl
  from tensorflow_transform.beam import impl_test
  from tensorflow_transform.beam import tft_unit
label_desc: Use image node_id 7 for calling the TukeyHHParamsIntegrationTest obj's underlying member method code with example usage: obj.testTukeyHHAnalyzersWithNDDenseInputs() and returns: dict