code: def validate(reference_tempi, reference_weight, estimated_tempi):
      
      validate_tempi(reference_tempi, reference=True)
      validate_tempi(estimated_tempi, reference=False)
  
      if reference_weight < 0 or reference_weight > 1:
          raise ValueError('Reference weight must lie in range [0, 1]')
docs: Checks that the input annotations to a metric look like valid tempo
      annotations.
  
      Parameters
      ----------
      reference_tempi : np.ndarray
          reference tempo values, in bpm
  
      reference_weight : float
          perceptual weight of slow vs fast in reference
  
      estimated_tempi : np.ndarray
          estimated tempo values, in bpm