From 525e091431b6e6661f5ec6b61b83857791aff441 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Wed, 26 Feb 2020 16:02:42 -0800
Subject: [PATCH] Internal change
PiperOrigin-RevId: 297466825
Change-Id: I8f4990d992478b4783c00119e4c1a23cff699d81
---
.../core/kernels/non_max_suppression_op.cc | 23 -------------------
.../kernels/non_max_suppression_op_test.cc | 2 +-
tensorflow/python/ops/image_ops_test.py | 2 +-
3 files changed, 2 insertions(+), 25 deletions(-)
diff --git a/tensorflow/core/kernels/non_max_suppression_op.cc b/tensorflow/core/kernels/non_max_suppression_op.cc
index c125c673928..20ae3a2e0d0 100644
--- a/tensorflow/core/kernels/non_max_suppression_op.cc
+++ b/tensorflow/core/kernels/non_max_suppression_op.cc
@@ -39,17 +39,6 @@ namespace {
typedef Eigen::ThreadPoolDevice CPUDevice;
-template <typename T>
-bool CheckBoxesCoordinates(const Tensor& boxes, int num_boxes) {
- typename TTypes<T, 2>::ConstTensor boxes_data = boxes.tensor<T, 2>();
- for (int i = 0; i < num_boxes; ++i) {
- if (boxes_data(i, 0) == boxes_data(i, 2) ||
- boxes_data(i, 1) == boxes_data(i, 3))
- return false;
- }
- return true;
-}
-
static inline void CheckScoreSizes(OpKernelContext* context, int num_boxes,
const Tensor& scores) {
// The shape of 'scores' is [num_boxes]
@@ -605,9 +594,6 @@ class NonMaxSuppressionOp : public OpKernel {
int num_boxes = 0;
ParseAndCheckBoxSizes(context, boxes, &num_boxes);
CheckScoreSizes(context, num_boxes, scores);
- OP_REQUIRES(
- context, CheckBoxesCoordinates<float>(boxes, num_boxes),
- errors::InvalidArgument("Boxes are empty (x1 == x2 or y1 == y2)"));
if (!context->status().ok()) {
return;
}
@@ -655,9 +641,6 @@ class NonMaxSuppressionV2Op : public OpKernel {
int num_boxes = 0;
ParseAndCheckBoxSizes(context, boxes, &num_boxes);
CheckScoreSizes(context, num_boxes, scores);
- OP_REQUIRES(
- context, CheckBoxesCoordinates<T>(boxes, num_boxes),
- errors::InvalidArgument("Boxes are empty (x1 == x2 or y1 == y2)"));
if (!context->status().ok()) {
return;
}
@@ -709,9 +692,6 @@ class NonMaxSuppressionV3Op : public OpKernel {
int num_boxes = 0;
ParseAndCheckBoxSizes(context, boxes, &num_boxes);
CheckScoreSizes(context, num_boxes, scores);
- OP_REQUIRES(
- context, CheckBoxesCoordinates<T>(boxes, num_boxes),
- errors::InvalidArgument("Boxes are empty (x1 == x2 or y1 == y2)"));
if (!context->status().ok()) {
return;
}
@@ -766,9 +746,6 @@ class NonMaxSuppressionV4Op : public OpKernel {
int num_boxes = 0;
ParseAndCheckBoxSizes(context, boxes, &num_boxes);
CheckScoreSizes(context, num_boxes, scores);
- OP_REQUIRES(
- context, CheckBoxesCoordinates<T>(boxes, num_boxes),
- errors::InvalidArgument("Boxes are empty (x1 == x2 or y1 == y2)"));
if (!context->status().ok()) {
return;
}
diff --git a/tensorflow/core/kernels/non_max_suppression_op_test.cc b/tensorflow/core/kernels/non_max_suppression_op_test.cc
index 59d5c5e8148..115f7902478 100644
--- a/tensorflow/core/kernels/non_max_suppression_op_test.cc
+++ b/tensorflow/core/kernels/non_max_suppression_op_test.cc
@@ -106,7 +106,7 @@ TEST_F(NonMaxSuppressionOpTest, TestSelectWithNegativeScores) {
TEST_F(NonMaxSuppressionOpTest, TestFirstBoxDegenerate) {
MakeOp(.5);
AddInputFromArray<float>(TensorShape({3, 4}),
- {0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3});
+ {0, 0, 0, 0, 1, 1, 2, 2, 2, 2, 3, 3});
AddInputFromArray<float>(TensorShape({3}), {.9f, .75f, .6f});
AddInputFromArray<int>(TensorShape({}), {3});
TF_ASSERT_OK(RunOpKernel());
diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py
index 3b7f75b141a..f4c0f6926b1 100644
--- a/tensorflow/python/ops/image_ops_test.py
+++ b/tensorflow/python/ops/image_ops_test.py
@@ -4598,7 +4598,7 @@ class NonMaxSuppressionPaddedTest(test_util.TensorFlowTestCase):
"non_max_suppression with dynamic output shape unsupported.")
def testSelectFromContinuousOverLap(self):
boxes_np = [[0, 0, 1, 1], [0, 0.2, 1, 1.2], [0, 0.4, 1, 1.4],
- [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 3]]
+ [0, 0.6, 1, 1.6], [0, 0.8, 1, 1.8], [0, 2, 1, 2]]
scores_np = [0.9, 0.75, 0.6, 0.5, 0.4, 0.3]
max_output_size_np = 3
iou_threshold_np = 0.5