code: def testResize(self, src_sizes, dst_size, v1=False):
      resize = (
          image_ops.resize_images if v1 else image_ops.resize_images_v2
      )
  
      # Construct the input images.
      channels = 3
      images = self.make_image_batch(src_sizes, channels)
      expected_shape = [len(src_sizes)] + list(dst_size) + [channels]
  
      # Resize the ragged batch of images.
      resized_images = resize(images, dst_size)
      self.assertIsInstance(resized_images, tensor.Tensor)
      self.assertEqual(resized_images.shape.as_list(), 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 = resize(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 2 for calling the RaggedResizeImageOpTest obj's underlying member method code with example usage: obj.testResize(src_sizes, dst_size, v1) without return types