code: def test_channel_swap_correctness(n_ch, data_format, data_type):
      len_src = 256
      src_mono, batch_src, input_shape = get_audio(
          data_format=data_format, n_ch=n_ch, length=len_src
      )
  
      model = tf.keras.Sequential()
      model.add(
          ChannelSwap(
              input_shape=input_shape,
          )
      )
      # consistent during inference
      kapre_ref = model.predict(batch_src)
      for _ in range(100):
          kapre_again = model.predict(batch_src)
          np.testing.assert_equal(kapre_ref, kapre_again)
      ch_axis = 1 if data_format == _CH_FIRST_STR else 2
  
file_path: kapre/tests/test_augmentation.py
imports: import pytest
  import numpy
  import tensorflow
  from kapre.augmentation import ChannelSwap, SpecAugment
  from kapre.backend import _CH_FIRST_STR, _CH_LAST_STR, _CH_DEFAULT_STR
  from utils import get_audio, get_spectrogram, save_load_compare
label_desc: Use image node_id 1 for calling a global function with example usage: test_channel_swap_correctness(n_ch, data_format, data_type) without return types