code: def testResizeWithPartialStaticShape(
      self, src_shape, src_sizes, dst_size
  ):
      channels = src_shape[-1] or 3
      images = self.make_image_batch(src_sizes, channels)
      rt_spec = ragged_tensor.RaggedTensorSpec(
          src_shape, ragged_rank=images.ragged_rank
      )
      expected_shape = [len(src_sizes)] + list(dst_size) + [channels]
  
      # Use @tf.function to erase static shape information.
      @def_function.function(input_signature=[rt_spec])
      def do_resize(images):
          return image_ops.resize_images_v2(images, dst_size)
  
      resized_images = do_resize(images)
      self.assertIsInstance(resized_images, tensor.Tensor)
      self.assertTrue(
          resized_images.shape.is_compatible_with(expected_shape)
      )
  
      # Check that results for each image matches what we'd get with the
      # non-batch version of tf.images.resize.
      for i in range(len(src_sizes)):
          actual = resized_images[i]
          expected = image_ops.resize_images_v2(
              images[i].to_tensor(), dst_size
          )
          self.assertAllClose(actual, expected)
  
file_path: tensorflow-upstream/tensorflow/python/ops/ragged/ragged_resize_image_op_test.py
imports: from absl.testing import parameterized
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import image_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_concat_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 3 for calling the RaggedResizeImageOpTest obj's underlying member method code with example usage: obj.testResizeWithPartialStaticShape(src_shape, src_sizes, dst_size) and returns: image_ops