code: def test_concat_features():
      concat = NumpyConcatenateInnerFeatures()
      # ND arrays
      data1 = np.random.random((10, 4, 5, 2))
      data2 = np.random.random((10, 4, 5, 10))
      expected_all_data = np.concatenate([data1, data2], axis=-1)
  
      concat, received_all_data = concat.fit_transform([data1, data2])
  
      assert tuple(received_all_data.shape) == tuple(
          expected_all_data.shape
      )
      assert (received_all_data == expected_all_data).all()
  
imports: import numpy
  from neuraxle.steps.numpy import NumpyConcatenateInnerFeatures, NumpyFlattenDatum, NumpyShapePrinter, NumpyTranspose, NumpyFFT, NumpyRavel
label_desc: Use image node_id 2 for calling a global function with example usage: test_concat_features() without return types