message: Fix tf.image.ssim_multiscale execution issue
  This fix tries to address the issue raised in 28241 where
  tf.image.ssim_multiscale will throw out error if the input
  is numpy array instead of tensor.
  This fix adds the conversion (also removed duplicated shape checking).
  This fix fixes 28241.
diff: @@ -3060,12 +3060,11 @@ def ssim_multiscale(img1, img2, max_val, power_factors=_MSSSIM_WEIGHTS):
  are in range [0, 1]. Returns a tensor with shape:
  broadcast(img1.shape[:-3], img2.shape[:-3]).
  """
  - # Shape checking.
  - shape1 = img1.get_shape().with_rank_at_least(3)
  - shape2 = img2.get_shape().with_rank_at_least(3)
  - shape1[-3:].merge_with(shape2[-3:])
  -
  with ops.name_scope(None, 'MS-SSIM', [img1, img2]):
  + # Convert to tensor if needed.
  + img1 = ops.convert_to_tensor(img1, name='img1')
  + img2 = ops.convert_to_tensor(img2, name='img2')
  + # Shape checking.
  shape1, shape2, checks = _verify_compatible_image_shapes(img1, img2)
  with ops.control_dependencies(checks):
  img1 = array_ops.identity(img1)
  