code: def test_fast_exp():
      X = np.linspace(-5, 0, 5000, endpoint=True)
  
      # Ground truth
      Y = np.exp(X)
  
      # Approximation at double precision
      _y_f64 = np.array([fast_exp["float64_t"](x) for x in X])
  
      # Approximation at single precision
      _y_f32 = np.array(
          [fast_exp["float32_t"](x) for x in X.astype("float32")],
          dtype="float32",
      )
  
      for _y in [_y_f64, _y_f32]:
          assert np.abs(Y - _y).mean() < 3e-3
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_fast_exp() without return types