diff options
Diffstat (limited to 'tensorflow/python/ops/image_ops_test.py')
| -rw-r--r-- | tensorflow/python/ops/image_ops_test.py | 76 |
1 files changed, 54 insertions, 22 deletions
diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py index 51c49e9da3..b4f4f87d06 100644 --- a/tensorflow/python/ops/image_ops_test.py +++ b/tensorflow/python/ops/image_ops_test.py @@ -741,7 +741,14 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): image_ops.ResizeMethod.AREA] TYPES = [np.uint8, np.int8, np.int16, np.int32, np.int64, - np.float, np.double] + np.float32, np.float64] + + def availableGPUModes(self, opt, nptype): + if opt == image_ops.ResizeMethod.NEAREST_NEIGHBOR \ + and nptype in [np.float32, np.float64]: + return [True, False] + else: + return [False] def testNoOp(self): img_shape = [1, 6, 4, 1] @@ -761,13 +768,14 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): img_np = np.array(data, dtype=nptype).reshape(img_shape) for opt in self.OPTIONS: - with self.test_session() as sess: - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - yshape = array_ops.shape(y) - resized, newshape = sess.run([y, yshape]) - self.assertAllEqual(img_shape, newshape) - self.assertAllClose(resized, img_np, atol=1e-5) + for use_gpu in self.availableGPUModes(opt, nptype): + with self.test_session(use_gpu=use_gpu) as sess: + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + yshape = array_ops.shape(y) + resized, newshape = sess.run([y, yshape]) + self.assertAllEqual(img_shape, newshape) + self.assertAllClose(resized, img_np, atol=1e-5) # Resizing with a single image must leave the shape unchanged also. with self.test_session(): @@ -857,12 +865,13 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): img_np = np.array(data, dtype=nptype).reshape(img_shape) for opt in self.OPTIONS: - with self.test_session(): - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - expected = np.array(expected_data).reshape(target_shape) - resized = y.eval() - self.assertAllClose(resized, expected, atol=1e-5) + for use_gpu in self.availableGPUModes(opt, nptype): + with self.test_session(use_gpu=use_gpu): + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + expected = np.array(expected_data).reshape(target_shape) + resized = y.eval() + self.assertAllClose(resized, expected, atol=1e-5) def testResizeUp(self): img_shape = [1, 3, 2, 1] @@ -899,14 +908,15 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): image_ops.ResizeMethod.BILINEAR, image_ops.ResizeMethod.NEAREST_NEIGHBOR, image_ops.ResizeMethod.AREA]: - with self.test_session(): - img_np = np.array(data, dtype=nptype).reshape(img_shape) - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - resized = y.eval() - expected = np.array(expected_data[opt]).reshape( - [1, target_height, target_width, 1]) - self.assertAllClose(resized, expected, atol=1e-05) + for use_gpu in self.availableGPUModes(opt, nptype): + with self.test_session(use_gpu=use_gpu): + img_np = np.array(data, dtype=nptype).reshape(img_shape) + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + resized = y.eval() + expected = np.array(expected_data[opt]).reshape( + [1, target_height, target_width, 1]) + self.assertAllClose(resized, expected, atol=1e-05) def testResizeUpBicubic(self): img_shape = [1, 6, 6, 1] @@ -964,6 +974,28 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): self.assertAllClose(resized, expected, atol=1) + def testCompareNearestNeighbor(self): + input_shape = [1, 5, 6, 3] + target_height = 8 + target_width = 12 + for nptype in [np.float32, np.float64]: + for align_corners in [True, False]: + img_np = np.arange(0, np.prod(input_shape), dtype=nptype).reshape(input_shape) + with self.test_session(use_gpu=True): + image = constant_op.constant(img_np, shape=input_shape) + out_op = image_ops.resize_images(image, target_height, target_width, + image_ops.ResizeMethod.NEAREST_NEIGHBOR, + align_corners=align_corners) + gpu_val = out_op.eval() + with self.test_session(use_gpu=False): + image = constant_op.constant(img_np, shape=input_shape) + out_op = image_ops.resize_images(image, target_height, target_width, + image_ops.ResizeMethod.NEAREST_NEIGHBOR, + align_corners=align_corners) + cpu_val = out_op.eval() + self.assertAllClose(cpu_val, gpu_val, rtol=1e-5, atol=1e-5) + + class ResizeImageWithCropOrPadTest(test_util.TensorFlowTestCase): def _ResizeImageWithCropOrPad(self, original, original_shape, |