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authorGravatar A. Unique TensorFlower <gardener@tensorflow.org>2017-06-26 12:54:12 -0700
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2017-06-26 12:57:46 -0700
commitf3c89936e97c99dead1ca3310246691c1b221adf (patch)
tree3c99b66936ed59028b32609115a239f52798907d /tensorflow/core/kernels/non_max_suppression_op.cc
parent0b9b09a8531004b44b133a52c3fcc67bc6759bd8 (diff)
Merge changes from github.
END_PUBLIC Note: this CL will break builds. cl/159887762 to follow to fix all the breakages. --- Commit 2336cdf7f authored by Maxwell Paul Brickner<mbrickn@users.noreply.github.com> Committed by gunan<gunan@google.com>: Updated link to use HTTPS (#10998) Howdy! I just updated a link to use https instead of http. Thanks! --- Commit ad0892df1 authored by Luke Iwanski<luke@codeplay.com> Committed by Luke Iwanski<luke@codeplay.com>: [OpenCL] Fixes run_metadata_test for SYCL This test is designed to test CUDA specific behavior --- Commit 6b37a0725 authored by Todd Wang<toddwang@gmail.com> Committed by GitHub<noreply@github.com>: Update comments --- Commit 1699d904a authored by John Lawson<john@codeplay.com> Committed by Luke Iwanski<luke@codeplay.com>: [OpenCL] Fixes CUDA specific test run on SYCL (#56) The testBadParentValuesOnGPU should only be run on CUDA devices, as the test checks for particular CUDA behaviour. We don't actually provide a SYCL kernel for GatherTree and so it's not a problem that the tests don't target SYCL. --- Commit 3c1946230 authored by myPrecious<Moriadry@users.noreply.github.com> Committed by Shanqing Cai<cais@google.com>: Java API to get the size of specified input list of operations. (#10865) * Java API to get the size of specified input list of operations * remove unnecessary explain to avoid bring a new term to users. --- Commit e911c7480 authored by Luke Iwanski<luke@codeplay.com> Committed by Luke Iwanski<luke@codeplay.com>: [OpenCL] REGISTER -> REGISTER6 --- Commit fbf6c4cec authored by superryanguo<superryanguo@gmail.com> Committed by superryanguo<superryanguo@gmail.com>: Simplify the Quickstart section with the weblink is better --- Commit 72e2918cc authored by Taehoon Lee<taehoonlee@snu.ac.kr> Committed by Taehoon Lee<taehoonlee@snu.ac.kr>: Fix typos --- Commit 90c4406b7 authored by Rishabh Patel<patelrishabh@users.noreply.github.com> Committed by GitHub<noreply@github.com>: Correct the learning rate as per the code snippet --- Commit 03da61134 authored by Todd Wang<toddwang@gmail.com> Committed by GitHub<noreply@github.com>: Update ir_array.cc --- Commit 2df6cd3ac authored by Todd Wang<toddwang@gmail.com> Committed by GitHub<noreply@github.com>: Another try --- Commit af0cbace1 authored by Luke Iwanski<luke@codeplay.com> Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>: [OpenCL] Transpose to go through Eigen (#10321) --- Commit fc7361081 authored by Luke Iwanski<luke@codeplay.com> Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>: [OpenCL] Registers RGBToHSV and HSVToRGB (#91) (#10848) * [OpenCL] Added RGBToHSV and HSVToRGB * Aligning '\' --- Commit 832894ef8 authored by Luke Iwanski<luke@codeplay.com> Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>: [OpenCL] Registers AdjustContrastv2 (#10949) * [OpenCL] Registers AdjustContrastv2 (#93) * [OpenCL] Extended adjust_contrast_op_benchmark_test for OpenCL (#96) * [OpenCL] Extended adjust_contrast_op_benchmark_test for OpenCL * simplified to #ifndef * Changed to "#if GOOGLE_CUDA" * Update adjust_contrast_op_benchmark_test.cc * Added comments --- Commit cb4c2f8d1 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Make TransferBufferToInFeed not virual so it compiles. --- Commit e89f04d80 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Fix calling Literal member functions. --- Commit 15a8df724 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Fix mac build clone from meheff's change: [XLA] Change return type of DeviceAssignment::Deserialize to fix build breakage on mac. The mac build had the following error: error: incomplete type 'xla::DeviceAssignment' used in type trait expression This was due to a static method returning a StatusOr<DeviceAssignment> inside of the definition of DeviceAssignment. --- Commit a54d43fa4 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Replace LiteralUtil to Literal in compiler/plugin/executor --- Commit 88a6bb80c authored by Guenther Schmuelling<guschmue@microsoft.com> Committed by Guenther Schmuelling<guschmue@microsoft.com>: expand inline for debug builds to limit number of symbols --- Commit 62fb49d31 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Fix visibility error for contrib/remote_fused_graph/pylib/BUILD. --- Commit 4c75252f2 authored by Mark Neumann<markn@allenai.org> Committed by Mark Neumann<markn@allenai.org>: fix initial test values to avoid numerical instability --- Commit b58d98353 authored by sj6077<epik03sj@gmail.com> Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>: Fixes of AutoParallel bug (#10368) * Fix the bug that auto_parallel could replicate variable snapshot name * Use NodeName in grappler:utils instead of substr, convert variables->variable_def of grappler item * remove variable_def from grappler item, exclude snapshot nodes from dont_replicate_nodes in auto_parallel --- Commit a286b7db8 authored by Yifei Feng<yifeif@google.com> Committed by Yifei Feng<yifeif@google.com>: Make debug_test slice integer. --- Commit 97fcfdfa6 authored by Toby Boyd<tobyboyd@google.com> Committed by GitHub<noreply@github.com>: Fixed path to seq2seq.py and minor formatting --- Commit 63c1befb8 authored by Anish Shah<shah.anish07@gmail.com> Committed by Anish Shah<shah.anish07@gmail.com>: Improve docs for tf.nn.depthwise_conv2d_native --- Commit 8d42202b2 authored by Yong Tang<yong.tang.github@outlook.com> Committed by Yong Tang<yong.tang.github@outlook.com>: Fix mismatched delete in mkl_tfconv_op.cc This fix fixes mismatched new[]-delete in mkl_tfconv_op.cc (the file went through clang-format so there are some additional changes) Signed-off-by: Yong Tang <yong.tang.github@outlook.com> --- Commit 26301bd55 authored by Danny Goodman<goodman.danny@gmail.com> Committed by Danny Goodman<goodman.danny@gmail.com>: fix error format --- Commit b3f33ad46 authored by Yao Zhang<yaozhang@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Make changes to prepare for the fused option of batch norm to be set to None (None means using fused batch norm if possible). PiperOrigin-RevId: 159649743 --- Commit a4a469832 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: [XLA] Add tests for select ops and while loops that produce tuples that contain predicates. PiperOrigin-RevId: 159645900 --- Commit 980d3f2be authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Use C API to implement Operation.name property This name property is used in many existing tests including those that already run with C API enabled (math_ops_test, framework_ops_test, session_test, session_partial_run_test, math_ops_test_gpu, etc). PiperOrigin-RevId: 159645767 --- Commit 26239c706 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Previously we didn't have an implementation of BatchNormInference and BatchNormTraining, which gives a linker error if anyone ever tries to call that. A dummy implementation is friendlier than a linker error. PiperOrigin-RevId: 159645612 --- Commit f671c5caa authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: BEGIN_PUBLIC Automated g4 rollback of changelist 159570549 PiperOrigin-RevId: 160182040
Diffstat (limited to 'tensorflow/core/kernels/non_max_suppression_op.cc')
-rw-r--r--tensorflow/core/kernels/non_max_suppression_op.cc36
1 files changed, 20 insertions, 16 deletions
diff --git a/tensorflow/core/kernels/non_max_suppression_op.cc b/tensorflow/core/kernels/non_max_suppression_op.cc
index 9ffe71e031..dc95f67ff0 100644
--- a/tensorflow/core/kernels/non_max_suppression_op.cc
+++ b/tensorflow/core/kernels/non_max_suppression_op.cc
@@ -90,20 +90,24 @@ static inline float ComputeIOU(typename TTypes<float, 2>::ConstTensor boxes,
return intersection_area / (area_i + area_j - intersection_area);
}
-void DoNonMaxSuppressionOp(OpKernelContext* context, const Tensor& boxes,
- const Tensor& scores, const Tensor& max_output_size,
+void DoNonMaxSuppressionOp(OpKernelContext* context,
+ const Tensor& boxes,
+ const Tensor& scores,
+ const Tensor& max_output_size,
const float iou_threshold) {
OP_REQUIRES(context, iou_threshold >= 0 && iou_threshold <= 1,
- errors::InvalidArgument("iou_threshold must be in [0, 1]"));
-
+ errors::InvalidArgument("iou_threshold must be in [0, 1]"));
+
int num_boxes = 0;
ParseAndCheckBoxSizes(context, boxes, scores, &num_boxes);
if (!context->status().ok()) {
return;
}
- const int output_size = std::min(max_output_size.scalar<int>()(), num_boxes);
- typename TTypes<float, 2>::ConstTensor boxes_data = boxes.tensor<float, 2>();
+ const int output_size =
+ std::min(max_output_size.scalar<int>()(), num_boxes);
+ typename TTypes<float, 2>::ConstTensor boxes_data =
+ boxes.tensor<float, 2>();
std::vector<float> scores_data(num_boxes);
std::copy_n(scores.flat<float>().data(), num_boxes, scores_data.begin());
@@ -123,7 +127,7 @@ void DoNonMaxSuppressionOp(OpKernelContext* context, const Tensor& boxes,
for (int j = i + 1; j < num_boxes; ++j) {
if (active[j]) {
float iou =
- ComputeIOU(boxes_data, sorted_indices[i], sorted_indices[j]);
+ ComputeIOU(boxes_data, sorted_indices[i], sorted_indices[j]);
if (iou > iou_threshold) {
active[j] = false;
num_active--;
@@ -141,7 +145,7 @@ void DoNonMaxSuppressionOp(OpKernelContext* context, const Tensor& boxes,
std::copy_n(selected.begin(), selected.size(), selected_indices_data.data());
}
-} // namespace
+} // namespace
template <typename Device>
class NonMaxSuppressionOp : public OpKernel {
@@ -163,8 +167,7 @@ class NonMaxSuppressionOp : public OpKernel {
errors::InvalidArgument("max_output_size must be 0-D, got shape ",
max_output_size.shape().DebugString()));
- DoNonMaxSuppressionOp(context, boxes, scores, max_output_size,
- iou_threshold_);
+ DoNonMaxSuppressionOp(context, boxes, scores, max_output_size, iou_threshold_);
}
private:
@@ -175,7 +178,8 @@ template <typename Device>
class NonMaxSuppressionV2Op : public OpKernel {
public:
explicit NonMaxSuppressionV2Op(OpKernelConstruction* context)
- : OpKernel(context) {}
+ : OpKernel(context) {
+ }
void Compute(OpKernelContext* context) override {
// boxes: [num_boxes, 4]
@@ -190,14 +194,14 @@ class NonMaxSuppressionV2Op : public OpKernel {
max_output_size.shape().DebugString()));
// iou_threshold: scalar
const Tensor& iou_threshold = context->input(3);
- OP_REQUIRES(context, TensorShapeUtils::IsScalar(iou_threshold.shape()),
- errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
- iou_threshold.shape().DebugString()));
+ OP_REQUIRES(
+ context, TensorShapeUtils::IsScalar(iou_threshold.shape()),
+ errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
+ iou_threshold.shape().DebugString()));
const float iou_threshold_val = iou_threshold.scalar<float>()();
- DoNonMaxSuppressionOp(context, boxes, scores, max_output_size,
- iou_threshold_val);
+ DoNonMaxSuppressionOp(context, boxes, scores, max_output_size, iou_threshold_val);
}
};