Document what dtype tf.image.resize_images returns.

For consistency, tf.image.resize_images now will always return a float32 when method != ResizeMethod.NEAREST_NEIGHBOR. Before, it returned the same dtype as its input if it could be determined statically that the height and width would not be changed.

PiperOrigin-RevId: 171028825

tensorflow/python/ops/image_ops_impl.py

@@ -709,6 +709,12 @@ def resize_images(images,
     https://en.wikipedia.org/wiki/Bicubic_interpolation)
   *   <b>`ResizeMethod.AREA`</b>: Area interpolation.
 
+  The return value has the same type as `images` if `method` is
+  `ResizeMethod.NEAREST_NEIGHBOR`. It will also have the same type as `images`
+  if the size of `images` can be statically determined to be the same as `size`,
+  because `images` is returned in this case. Otherwise, the return value has
+  type `float32`.
+
   Args:
     images: 4-D Tensor of shape `[batch, height, width, channels]` or
             3-D Tensor of shape `[height, width, channels]`.

tensorflow/python/ops/image_ops_test.py

@@ -1795,6 +1795,21 @@ class ResizeImagesTest(test_util.TensorFlowTestCase):
       _ = image_ops.resize_images(image, [6, None],
                                   image_ops.ResizeMethod.BILINEAR)
 
+  def testReturnDtype(self):
+    target_shapes = [[6, 4], [3, 2], [array_ops.placeholder(dtypes.int32),
+                                      array_ops.placeholder(dtypes.int32)]]
+    for nptype in self.TYPES:
+      image = array_ops.placeholder(nptype, shape=[1, 6, 4, 1])
+      for opt in self.OPTIONS:
+        for target_shape in target_shapes:
+          y = image_ops.resize_images(image, target_shape, opt)
+          if (opt == image_ops.ResizeMethod.NEAREST_NEIGHBOR or
+              target_shape == image.shape[1:3]):
+            expected_dtype = image.dtype
+          else:
+            expected_dtype = dtypes.float32
+          self.assertEqual(y.dtype, expected_dtype)
+
   def testSumTensor(self):
     img_shape = [1, 6, 4, 1]
     # This test is also conducted with int8, so 127 is the maximum