code: def regression(self, parameters, aggregation_method="majority"):
      # The expected values were self-generated with TempoCNN
      # from commit deb334ba01f849e74b0e6e8554b2e17d73bc6966
      # The retrieved tempo values were manually validated (Pablo Alonso)
      expected_global_tempo = 125.0
      expected_local_tempo = [125.0, 125.0, 125.0, 125.0]
      expected_local_probs = [
          0.9679363,
          0.9600502,
          0.9681525,
          0.9627014,
      ]
  
      filename = join(testdata.audio_dir, "recorded", "techno_loop.wav")
  
      audio = MonoLoader(filename=filename, sampleRate=11025)()
      global_tempo, local_tempo, local_probs = TempoCNN(**parameters)(
          audio
      )
  
      self.assertEqual(global_tempo, expected_global_tempo)
      self.assertEqualVector(local_tempo, expected_local_tempo)
      self.assertAlmostEqualVector(
          local_probs, expected_local_probs, 1e-6
      )
  
file_path: essentia/test/src/unittests/rhythm/test_tempocnn.py
imports: from essentia_test import *
label_desc: Use image node_id 1 for calling the TestTempoCNN obj's underlying member method code with example usage: obj.regression(parameters, aggregation_method) without return types