code: def test_saturation():
      # Same params
      scale_and_zp = {
          "lhs_scale": 0.125,
          "lhs_zp": 0,
          "rhs_scale": 0.125,
          "rhs_zp": 0,
          "output_scale": 0.125,
          "output_zp": 0,
      }
      x_data = [np.array((255, 1, 1, 0)).reshape((1, 4))]
      y_data = [np.array((255, 255, 128, 0)).reshape((1, 4))]
      golden_output = [np.array((0, 0, 0, 0)).reshape((1, 4))]
      qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)
  
      # Same params, different scale
      scale_and_zp = {
          "lhs_scale": 0.125,
          "lhs_zp": 0,
          "rhs_scale": 0.125,
          "rhs_zp": 0,
          "output_scale": 0.25,
          "output_zp": 0,
      }
      x_data = [np.array((255, 1, 200, 0)).reshape((1, 4))]
      y_data = [np.array((255, 255, 127, 0)).reshape((1, 4))]
      golden_output = [np.array((0, 0, 36, 0)).reshape((1, 4))]
      qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)
  
      # All params different
      scale_and_zp = {
          "lhs_scale": 0.5,
          "lhs_zp": 0,
          "rhs_scale": 0.25,
          "rhs_zp": 0,
          "output_scale": 0.125,
          "output_zp": 0,
      }
      x_data = [np.array((255, 0, 1, 0)).reshape((1, 4))]
      y_data = [np.array((0, 128, 64, 0)).reshape((1, 4))]
      golden_output = [np.array((255, 0, 0, 0)).reshape((1, 4))]
      qnn_subtract_driver(x_data, y_data, golden_output, scale_and_zp)
  
imports: import tvm
  import numpy
  from tvm import relay
label_desc: Use image node_id 4 for calling a global function with example usage: test_saturation() without return types