code: def testRGBToHSVGradSimpleCase(self):
      def f(x):
          return gen_image_ops.rgb_to_hsv(x)
  
      for nptype in self.TYPES:
          # Building a simple input tensor to avoid any discontinuity
          x = np.array(
              [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]]
          ).astype(nptype)
          rgb_input_tensor = constant_op.constant(x, shape=x.shape)
          # Computing Analytical and Numerical gradients of f(x)
          analytical, numerical = gradient_checker_v2.compute_gradient(
              f, [rgb_input_tensor]
          )
          self.assertAllClose(numerical, analytical, atol=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 2 for calling the RGBToHSVOpTestBase obj's underlying member method code with example usage: obj.testRGBToHSVGradSimpleCase() and returns: gen_image_ops