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| author |  Yong Tang <yong.tang.github@outlook.com> | 2018-08-14 16:45:21 +0000 |
|---|---|---|
| committer | Yong Tang <yong.tang.github@outlook.com> | 2018-09-04 06:56:03 +0000 |
| commit | 141d5d666694a37cda65c440315c135d9a6a48a7 (patch) | |
| tree | 804c4ccfeb8881f4d49e37b28692cbca40a68940 | |
| parent | bf64fc285e88d36bb82f80757c4a1afd722347e0 (diff) | |
Add test cases for float16 support for non_max_suppression
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
| -rw-r--r-- | tensorflow/python/ops/image_ops_test.py | 41 |
1 files changed, 41 insertions, 0 deletions
diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py index f7502c4018..ee76d3d1dc 100644 --- a/tensorflow/python/ops/image_ops_test.py +++ b/tensorflow/python/ops/image_ops_test.py @@ -3657,6 +3657,47 @@ class NonMaxSuppressionTest(test_util.TensorFlowTestCase): scores = constant_op.constant([0.9]) image_ops.non_max_suppression(boxes, scores, 3, [[0.5]]) + def testDataTypes(self): + # Test case for GitHub issue 20199. + boxes_np = [[0, 0, 1, 1], [0, 0.1, 1, 1.1], [0, -0.1, 1, 0.9], + [0, 10, 1, 11], [0, 10.1, 1, 11.1], [0, 100, 1, 101]] + scores_np = [0.9, 0.75, 0.6, 0.95, 0.5, 0.3] + max_output_size_np = 3 + iou_threshold_np = 0.5 + # Note: There are multiple versions of non_max_suppression v2, v3, v4. + # gen_image_ops.non_max_suppression_v2: + for dtype in [np.float16, np.float32]: + with self.test_session(): + boxes = constant_op.constant(boxes_np, dtype=dtype) + scores = constant_op.constant(scores_np, dtype=dtype) + max_output_size = constant_op.constant(max_output_size_np) + iou_threshold = constant_op.constant(iou_threshold_np) + selected_indices = gen_image_ops.non_max_suppression_v2( + boxes, scores, max_output_size, iou_threshold).eval() + self.assertAllClose(selected_indices, [3, 0, 5]) + # image_ops.non_max_suppression = gen_image_ops.non_max_suppression_v3. + for dtype in [np.float16, np.float32]: + with self.test_session(): + boxes = constant_op.constant(boxes_np, dtype=dtype) + scores = constant_op.constant(scores_np, dtype=dtype) + max_output_size = constant_op.constant(max_output_size_np) + iou_threshold = constant_op.constant(iou_threshold_np) + selected_indices = image_ops.non_max_suppression( + boxes, scores, max_output_size, iou_threshold).eval() + self.assertAllClose(selected_indices, [3, 0, 5]) + # gen_image_ops.non_max_suppression_v4. + score_threshold=float('-inf') + for dtype in [np.float16, np.float32]: + with self.test_session(): + boxes = constant_op.constant(boxes_np, dtype=dtype) + scores = constant_op.constant(scores_np, dtype=dtype) + max_output_size = constant_op.constant(max_output_size_np) + iou_threshold = constant_op.constant(iou_threshold_np) + selected_indices, _ = gen_image_ops.non_max_suppression_v4( + boxes, scores, max_output_size, iou_threshold, score_threshold) + selected_indices = selected_indices.eval() + self.assertAllClose(selected_indices, [3, 0, 5]) + class NonMaxSuppressionPaddedTest(test_util.TensorFlowTestCase): |