fix resize image bug

tensorflow/python/ops/image_ops_impl.py

@@ -1201,20 +1201,17 @@ def _resize_images_common(images, resizer_fn, size, preserve_aspect_ratio, name,
     if not size.get_shape().is_compatible_with([2]):
       raise ValueError('\'size\' must be a 1-D Tensor of 2 elements: '
                        'new_height, new_width')
-    size_const_as_shape = tensor_util.constant_value_as_shape(size)
-    new_height_const = size_const_as_shape.dims[0].value
-    new_width_const = size_const_as_shape.dims[1].value
 
     if preserve_aspect_ratio:
       # Get the current shapes of the image, even if dynamic.
       _, current_height, current_width, _ = _ImageDimensions(images, rank=4)
 
       # do the computation to find the right scale and height/width.
       scale_factor_height = (
-          math_ops.cast(new_height_const, dtypes.float32) /
+          math_ops.cast(size[0], dtypes.float32) /
           math_ops.cast(current_height, dtypes.float32))
       scale_factor_width = (
-          math_ops.cast(new_width_const, dtypes.float32) /
+          math_ops.cast(size[1], dtypes.float32) /
           math_ops.cast(current_width, dtypes.float32))
       scale_factor = math_ops.minimum(scale_factor_height, scale_factor_width)
       scaled_height_const = math_ops.cast(
@@ -1230,9 +1227,10 @@ def _resize_images_common(images, resizer_fn, size, preserve_aspect_ratio, name,
       size = ops.convert_to_tensor([scaled_height_const, scaled_width_const],
                                    dtypes.int32,
                                    name='size')
-      size_const_as_shape = tensor_util.constant_value_as_shape(size)
-      new_height_const = size_const_as_shape.dims[0].value
-      new_width_const = size_const_as_shape.dims[1].value
+
+    size_const_as_shape = tensor_util.constant_value_as_shape(size)
+    new_height_const = size_const_as_shape.dims[0].value
+    new_width_const = size_const_as_shape.dims[1].value
 
     # If we can determine that the height and width will be unmodified by this
     # transformation, we avoid performing the resize.

tensorflow/python/ops/image_ops_test.py

@@ -2712,7 +2712,8 @@ def _ResizeImageCall(self, x, max_h, max_w, preserve_aspect_ratio,
       feed_dict = {}
 
     y = image_ops.resize_images(
-        x_tensor, target_max, preserve_aspect_ratio=preserve_aspect_ratio)
+        x_tensor, ops.convert_to_tensor(target_max),
+        preserve_aspect_ratio=preserve_aspect_ratio)
 
     with self.cached_session(use_gpu=True):
       return y.eval(feed_dict=feed_dict)
@@ -2753,11 +2754,15 @@ def _assertResizeCheckShape(self,
 
   @test_util.run_deprecated_v1
   def testPreserveAspectRatioMultipleImages(self):
-    x_shape = [10, 100, 100, 10]
+    x_shape = [10, 100, 80, 10]
     x = np.random.uniform(size=x_shape)
-
-    self._assertResizeCheckShape(
-        x, x_shape, [250, 250], [10, 250, 250, 10], preserve_aspect_ratio=False)
+    for preserve_aspect_ratio in [True, False]:
+      with self.subTest(preserve_aspect_ratio=preserve_aspect_ratio):
+        expect_shape = [10, 250, 200, 10] if preserve_aspect_ratio \
+            else [10, 250, 250, 10]
+        self._assertResizeCheckShape(
+            x, x_shape, [250, 250], expect_shape,
+            preserve_aspect_ratio=preserve_aspect_ratio)
 
   @test_util.run_deprecated_v1
   def testPreserveAspectRatioNoOp(self):