Merge pull request #41140 from srjoglekar246/cherrypicks_5EM5L

r2.3 cherry-pick request: Shift padded NMS compat window forward to fix TFLite conversion

tensorflow/compiler/tests/image_ops_test.py

@@ -30,6 +30,7 @@ from six.moves import xrange  # pylint: disable=redefined-builtin
 from tensorflow.compiler.tests import xla_test
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import gen_image_ops
 from tensorflow.python.ops import image_ops
@@ -774,6 +775,7 @@ class ResizeBilinearNonAlignCornersTest(xla_test.XLATestCase):
 
 class NonMaxSuppressionTest(xla_test.XLATestCase):
 
+  @test_util.disable_mlir_bridge("%1")
   def testNMS128From1024(self):
     num_boxes = 1024
     boxes_np = np.random.normal(50, 10, (num_boxes, 4)).astype("f4")
@@ -808,6 +810,7 @@ class NonMaxSuppressionTest(xla_test.XLATestCase):
 
       self.assertEqual(indices_tf.size, max_output_size)
 
+  @test_util.disable_mlir_bridge("%1")
   def testNMS3From6Boxes(self):
     # Three boxes are selected based on IOU.
     boxes_data = [[0, 0, 1, 1], [0, 0.1, 1, 1.1], [0, -0.1, 1, 0.9],
@@ -849,6 +852,7 @@ class NonMaxSuppressionTest(xla_test.XLATestCase):
       self.assertEqual(num_valid, 3)
       self.assertAllClose(indices_tf[:num_valid], [3, 0, 5])
 
+  @test_util.disable_mlir_bridge("%1")
   def testNMS3Then2WithScoreThresh(self):
     # Three boxes are selected based on IOU.
     # One is filtered out by score threshold.
@@ -891,6 +895,7 @@ class NonMaxSuppressionTest(xla_test.XLATestCase):
       self.assertEqual(num_valid, 2)
       self.assertAllClose(indices_tf[:num_valid], [3, 0])
 
+  @test_util.disable_mlir_bridge("%1")
   def testNMS3Then1WithScoreMaxThresh(self):
     # Three boxes are selected based on IOU.
     # One is filtered out by score threshold.
@@ -934,6 +939,7 @@ class NonMaxSuppressionTest(xla_test.XLATestCase):
       self.assertEqual(num_valid, 1)
       self.assertAllClose(indices_tf[:num_valid], [3])
 
+  @test_util.disable_mlir_bridge("%1")
   def testSelectFromContinuousOverLap(self):
     # Tests that a suppressed box does not itself suppress other boxes.
 
@@ -978,6 +984,7 @@ class NonMaxSuppressionTest(xla_test.XLATestCase):
 
 class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSFrom6(self):
     boxes_data = [[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                    [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],
@@ -1015,6 +1022,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
                         indices_output)
     self.assertAllEqual([5, 4], num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSFrom6Max3(self):
     boxes_data = [[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                    [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],
@@ -1048,6 +1056,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([[0, 1, 2], [0, 1, 3]], indices_output)
     self.assertAllEqual([3, 3], num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSSingleFrom6Max3(self):
     boxes_data = [[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                   [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]]
@@ -1078,6 +1087,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([0, 1, 2], indices_output)
     self.assertAllEqual(3, num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSSingleFrom6NoPad(self):
     boxes_data = [[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                   [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]]
@@ -1107,6 +1117,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([0, 1, 2, 4, 5], indices_output)
     self.assertAllEqual(5, num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSBatchDimsFrom6Max3(self):
     boxes_data = [[[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                     [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],
@@ -1140,6 +1151,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([[[0, 1, 2], [0, 1, 3]]], indices_output)
     self.assertAllEqual([[3, 3]], num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSScoreThresholdFrom6Max3(self):
     boxes_data = [[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                    [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],
@@ -1175,6 +1187,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([3, 2], num_valid_output)
     self.assertAllEqual([[0, 1, 2], [0, 1, invalid_index]], indices_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSUnsortedInputFrom6(self):
     boxes_data = [[[0, 2, 1, 2], [3, 3, 4, 4], [0, 0, 1, 1],
                    [0, 0.4, 1, 1.4], [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8]],
@@ -1211,6 +1224,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
                         indices_output)
     self.assertAllEqual([5, 4], num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSNoncanonicalizedInputFrom6(self):
     boxes_data = [[[1, 0, 0, 1], [4, 3, 3, 4], [1, 0.4, 0, 1.4],
                    [1, 0.6, 0, 1.6], [1, 0.8, 0, 1.8], [1, 2, 0, 2]],
@@ -1248,6 +1262,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
                         indices_output)
     self.assertAllEqual([5, 4], num_valid_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSScoreThresholdCanInputsFrom6Max3(self):
     boxes_data = [[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                    [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],
@@ -1283,6 +1298,7 @@ class BatchedNonMaxSuppressionCorrectnessTest(xla_test.XLATestCase):
     self.assertAllEqual([3, 2], num_valid_output)
     self.assertAllEqual([[0, 1, 2], [0, 1, invalid_index]], indices_output)
 
+  @test_util.disable_mlir_bridge("%1")
   def testBatchedNMSFrom6DynamicInput(self):
     boxes_data = [[[0, 0, 1, 1], [3, 3, 4, 4], [0, 0.4, 1, 1.4],
                    [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]],

tensorflow/python/ops/image_ops_impl.py

@@ -4579,11 +4579,11 @@ def non_max_suppression_padded(boxes,
    Raises:
     ValueError: When set pad_to_max_output_size to False for batched input.
   """
-  # if no new arguments are used and no later than 2020/4/20, use the old
-  # version to give us time to fix TFLite conversion
+  # if no new arguments are used and no later than 2020/6/23, use the old
+  # version to give us time to fix TFLite conversion after the TF 2.3 release.
   if (not sorted_input) and \
       (not canonicalized_coordinates) and \
-      tile_size == 512 and not compat.forward_compatible(2020, 4, 20):
+      tile_size == 512 and not compat.forward_compatible(2020, 6, 23):
     return non_max_suppression_padded_v1(
         boxes, scores, max_output_size, iou_threshold, score_threshold,
         pad_to_max_output_size, name)