code: def testRGBToHSVGradRandomCase(self):
      def f(x):
          return gen_image_ops.rgb_to_hsv(x)
  
      np.random.seed(0)
      # Building a simple input tensor to avoid any discontinuity
      x = np.random.rand(1, 5, 5, 3).astype(np.float32)
      rgb_input_tensor = constant_op.constant(x, shape=x.shape)
      # Computing Analytical and Numerical gradients of f(x)
      self.assertLess(
          gradient_checker_v2.max_error(
              *gradient_checker_v2.compute_gradient(
                  f, [rgb_input_tensor]
              )
          ),
          1e-4,
      )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_image_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import image_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the RGBToHSVOpTestBase obj's underlying member method code with example usage: obj.testRGBToHSVGradRandomCase() and returns: gen_image_ops