code: def testRegression(self):
      # Hardcoded analysis parameters
      sampleRate = 11025
      frameSize = 1024
      hopSize = 512
  
      audio = MonoLoader(
          filename=join(testdata.audio_dir, "recorded/vignesh.wav"),
          sampleRate=sampleRate,
      )()
  
      expected = [
          0.00473826,
          0.08461753,
          0.4031311,
          0.11013637,
          0.07605512,
          0.20765066,
          0.18525994,
          0.21854699,
          0.34972662,
          0.4122374,
          0.14164223,
          0.08753049,
          0.07250968,
          0.02758735,
          0.03375721,
          0.04653678,
          0.0367885,
          0.03222116,
          0.06601233,
          0.04644121,
          0.06116791,
          0.06980634,
          0.0918903,
          0.13866659,
          0.07853713,
          0.04365063,
          0.02569871,
          0.0125964,
          0.01021744,
          0.01130397,
          0.02596227,
          0.03110815,
          0.02377434,
          0.0178348,
          0.01732456,
          0.02468131,
          0.02664435,
          0.00746825,
          0.00207653,
          0.002497,
      ]
  
      tfmf = TensorflowInputTempoCNN()
      frames = [
          tfmf(frame)
          for frame in FrameGenerator(
              audio,
              frameSize=frameSize,
              hopSize=hopSize,
              startFromZero=True,
          )
      ]
      obtained = numpy.mean(array(frames), axis=0)
  
      self.assertAlmostEqualVector(obtained, expected, 1e-1)
  
imports: from essentia_test import *
  import numpy
label_desc: Use image node_id 2 for calling the TestTensorflowInputTempoCNN obj's underlying member method code with example usage: obj.testRegression() without return types