code: def test_concatenate_frequency_map(data_format):
      shape = (4, 10, 5, 3)
  
      time_axis, freq_axis, ch_axis = (
          (1, 2, 3) if data_format == "channels_last" else (2, 3, 1)
      )  # todo - replace it with CH_LAST_STR
      batch_size, n_freq, n_time, n_ch = (
          shape[0],
          shape[freq_axis],
          shape[time_axis],
          shape[ch_axis],
      )
  
      x = tf.random.normal(shape, dtype=tf.float32)
      concat_freq_map = ConcatenateFrequencyMap(data_format=data_format)
      x_concat = concat_freq_map(x).numpy()
  
      # test shape
      new_shape = list(shape)
      new_shape[ch_axis] += 1
      np.testing.assert_equal(tuple(new_shape), x_concat.shape)
      # test freq map
      freq_map = (
          x_concat[0, 0, :, -1]
          if data_format == "channels_last"
          else x_concat[0, -1, 0, :]
      )
      np.testing.assert_allclose(
          freq_map, np.linspace(0, 1, num=n_freq)
      )
      # test original input
      other_channels = (
          x_concat[:, :, :, :-1]
          if data_format == "channels_last"
          else x_concat[:, :-1, :, :]
      )
      np.testing.assert_equal(x, other_channels)
  
imports: import pytest
  import numpy
  import tensorflow
  import tensorflow.keras
  import librosa
  from kapre import STFT, Magnitude, Phase, Delta, InverseSTFT, ApplyFilterbank, ConcatenateFrequencyMap, STFTTflite, MagnitudeTflite, PhaseTflite
  from kapre.composed import get_melspectrogram_layer, get_log_frequency_spectrogram_layer, get_stft_mag_phase, get_perfectly_reconstructing_stft_istft, get_stft_magnitude_layer, get_frequency_aware_conv2d
  from utils import get_audio, save_load_compare, predict_using_tflite
label_desc: Use image node_id 16 for calling a global function with example usage: test_concatenate_frequency_map(data_format) without return types