code: def __test_cqt_size(
      y,
      sr,
      hop_length,
      fmin,
      n_bins,
      bins_per_octave,
      tuning,
      filter_scale,
      norm,
      sparsity,
      res_type,
  ):
      cqt_output = np.abs(
          librosa.cqt(
              y,
              sr=sr,
              hop_length=hop_length,
              fmin=fmin,
              n_bins=n_bins,
              bins_per_octave=bins_per_octave,
              tuning=tuning,
              filter_scale=filter_scale,
              norm=norm,
              sparsity=sparsity,
              res_type=res_type,
          )
      )
  
      assert cqt_output.shape[0] == n_bins
  
      return cqt_output
  
imports: from __future__ import division
  import warnings
  import os
  from typing import Optional
  import librosa
  import numpy
  import scipy.stats
  import pytest
  from test_core import srand
label_desc: Use image node_id 1 for calling a global function with example usage: __test_cqt_size(y, sr, hop_length, fmin, n_bins, bins_per_octave, tuning, filter_scale, norm, sparsity, res_type) and returns: cqt_output