[XLA] Implement resize_images(BILINEAR, align_corners=false)

PiperOrigin-RevId: 210129265

1 files changed, 24 insertions, 2 deletions

diff --git a/tensorflow/compiler/tests/image_ops_test.py b/tensorflow/compiler/tests/image_ops_test.py
index 1a82fcbb2a..6fe5a66e0e 100644
--- a/tensorflow/compiler/tests/image_ops_test.py
+++ b/tensorflow/compiler/tests/image_ops_test.py
@@ -410,13 +410,14 @@ class ResizeBilinearTest(xla_test.XLATestCase):
                                       image_np,
                                       target_shape,
                                       expected=None,
-                                      large_tolerance=False):
+                                      large_tolerance=False,
+                                      align_corners=True):
     if expected is None:
       self.fail("expected must be specified")
     with self.cached_session() as sess, self.test_scope():
       image = array_ops.placeholder(image_np.dtype)
       resized = gen_image_ops.resize_bilinear(
-          image, target_shape, align_corners=True)
+          image, target_shape, align_corners=align_corners)
       out = sess.run(resized, {image: image_np[np.newaxis, :, :, np.newaxis]})
       if large_tolerance:
         self.assertAllClose(
@@ -579,6 +580,27 @@ class ResizeBilinearTest(xla_test.XLATestCase):
                 dtype=np.float32)),
         large_tolerance=True)
 
+  def testNonAlignCorners3x2To6x4(self):
+    input_data = [[64, 32], [32, 64], [50, 100]]
+    expected_data = [[64.0, 48.0, 32.0, 32.0], [48.0, 48.0, 48.0, 48.0],
+                     [32.0, 48.0, 64.0, 64.0], [41.0, 61.5, 82.0, 82.0],
+                     [50.0, 75.0, 100.0, 100.0], [50.0, 75.0, 100.0, 100.0]]
+    for dtype in self.float_types:
+      self._assertForwardOpMatchesExpected(
+          np.array(input_data, dtype=dtype), [6, 4],
+          expected=np.array(expected_data, dtype=np.float32),
+          align_corners=False)
+
+  def testNonAlignCorners6x4To3x2(self):
+    input_data = [[127, 127, 64, 64], [127, 127, 64, 64], [64, 64, 127, 127],
+                  [64, 64, 127, 127], [50, 50, 100, 100], [50, 50, 100, 100]]
+    expected_data = [[127, 64], [64, 127], [50, 100]]
+    for dtype in self.float_types:
+      self._assertForwardOpMatchesExpected(
+          np.array(input_data, dtype=dtype), [3, 2],
+          expected=np.array(expected_data, dtype=dtype),
+          align_corners=False)
+
 
 class NonMaxSuppressionTest(xla_test.XLATestCase):