Adds builtin ops for NMS & Soft NMS in TFLite
PiperOrigin-RevId: 267028434
This commit is contained in:
Sachin Joglekar
TensorFlower Gardener
parent
b6f70f85ca
commit
cb49525a25
@ -146,6 +146,8 @@ typedef enum {
|
||||
kTfLiteBuiltinHardSwish = 117,
|
||||
kTfLiteBuiltinIf = 118,
|
||||
kTfLiteBuiltinWhile = 119,
|
||||
kTfLiteBuiltinNonMaxSuppressionV4 = 120,
|
||||
kTfLiteBuiltinNonMaxSuppressionV5 = 121,
|
||||
} TfLiteBuiltinOperator;
|
||||
|
||||
#ifdef __cplusplus
|
||||
|
||||
@ -816,6 +816,8 @@ TfLiteStatus ParseOpData(const Operator* op, BuiltinOperator op_type,
|
||||
case BuiltinOperator_WHERE:
|
||||
case BuiltinOperator_RANK:
|
||||
case BuiltinOperator_QUANTIZE:
|
||||
case BuiltinOperator_NON_MAX_SUPPRESSION_V4:
|
||||
case BuiltinOperator_NON_MAX_SUPPRESSION_V5:
|
||||
break;
|
||||
}
|
||||
return kTfLiteOk;
|
||||
|
||||
@ -641,6 +641,40 @@ Outputs {
|
||||
}
|
||||
```
|
||||
|
||||
**NON_MAX_SUPPRESSION_V4**
|
||||
|
||||
```
|
||||
Inputs {
|
||||
0: boxes in format [y1, x1, y2, x2]
|
||||
1: scores
|
||||
2: max number of detections
|
||||
3: IOU threshold
|
||||
4: score threshold
|
||||
}
|
||||
Outputs {
|
||||
0: selected indices
|
||||
1: number of selected indices
|
||||
}
|
||||
```
|
||||
|
||||
**NON_MAX_SUPPRESSION_V5**
|
||||
|
||||
```
|
||||
Inputs {
|
||||
0: boxes in format [y1, x1, y2, x2]
|
||||
1: scores
|
||||
2: max number of detections
|
||||
3: IOU threshold
|
||||
4: score threshold
|
||||
5: soft NMS sigma
|
||||
}
|
||||
Outputs {
|
||||
0: selected indices
|
||||
1: selected scores
|
||||
2: number of selected indices
|
||||
}
|
||||
```
|
||||
|
||||
**PACK**
|
||||
|
||||
```
|
||||
|
||||
@ -466,6 +466,7 @@ cc_library(
|
||||
"mirror_pad.cc",
|
||||
"mul.cc",
|
||||
"neg.cc",
|
||||
"non_max_suppression.cc",
|
||||
"one_hot.cc",
|
||||
"pack.cc",
|
||||
"pad.cc",
|
||||
@ -1853,6 +1854,19 @@ cc_test(
|
||||
],
|
||||
)
|
||||
|
||||
cc_test(
|
||||
name = "non_max_suppression_test",
|
||||
size = "small",
|
||||
srcs = ["non_max_suppression_test.cc"],
|
||||
deps = [
|
||||
":builtin_ops",
|
||||
":test_main",
|
||||
":test_util",
|
||||
"//tensorflow/lite:framework",
|
||||
"@com_google_googletest//:gtest",
|
||||
],
|
||||
)
|
||||
|
||||
filegroup(
|
||||
name = "all_files",
|
||||
srcs = glob(
|
||||
|
||||
@ -300,5 +300,26 @@ TEST(NonMaxSuppression, TestSelectFromThreeClustersWithSoftNMS) {
|
||||
EXPECT_EQ(num_selected_indices, 4);
|
||||
MatchFirstNElements(4, selected_indices, {3, 0, 1, 5});
|
||||
}
|
||||
|
||||
TEST(NonMaxSuppression, TestNullSelectedScoresOutput) {
|
||||
// Inputs
|
||||
std::vector<float> boxes;
|
||||
std::vector<float> scores;
|
||||
InitializeCandidates(&boxes, &scores);
|
||||
const float iou_threshold = 0.5;
|
||||
const float score_threshold = 0.4;
|
||||
int max_output_size;
|
||||
|
||||
// Outputs
|
||||
std::vector<int> selected_indices(6);
|
||||
int num_selected_indices = -1;
|
||||
|
||||
max_output_size = 100;
|
||||
reference_ops::NonMaxSuppression(
|
||||
boxes.data(), kNumBoxes, scores.data(), max_output_size, iou_threshold,
|
||||
score_threshold, /**sigma=**/ 0.0, selected_indices.data(),
|
||||
/**selected_scores=**/ nullptr, &num_selected_indices);
|
||||
EXPECT_EQ(num_selected_indices, 2);
|
||||
}
|
||||
} // namespace
|
||||
} // namespace tflite
|
||||
|
||||
@ -172,7 +172,9 @@ inline void NonMaxSuppression(const float* boxes, const int num_boxes,
|
||||
if (next_candidate.score == original_score) {
|
||||
// Suppression has not occurred, so select next_candidate.
|
||||
selected_indices[*num_selected_indices] = next_candidate.index;
|
||||
if (selected_scores) {
|
||||
selected_scores[*num_selected_indices] = next_candidate.score;
|
||||
}
|
||||
++*num_selected_indices;
|
||||
}
|
||||
if (next_candidate.score > score_threshold) {
|
||||
|
||||
252
tensorflow/lite/kernels/non_max_suppression.cc
Normal file
252
tensorflow/lite/kernels/non_max_suppression.cc
Normal file
@ -0,0 +1,252 @@
|
||||
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
==============================================================================*/
|
||||
#include "tensorflow/lite/kernels/internal/reference/non_max_suppression.h"
|
||||
|
||||
#include <string.h>
|
||||
|
||||
#include <numeric>
|
||||
#include <vector>
|
||||
|
||||
#include "flatbuffers/flexbuffers.h" // TF:flatbuffers
|
||||
#include "tensorflow/lite/c/builtin_op_data.h"
|
||||
#include "tensorflow/lite/c/c_api_internal.h"
|
||||
#include "tensorflow/lite/kernels/internal/tensor.h"
|
||||
#include "tensorflow/lite/kernels/kernel_util.h"
|
||||
#include "tensorflow/lite/kernels/op_macros.h"
|
||||
|
||||
namespace tflite {
|
||||
namespace ops {
|
||||
namespace builtin {
|
||||
namespace non_max_suppression {
|
||||
|
||||
// Boxes in format [y1, x1, y2, x2]. Shape: [num_boxes, 4]
|
||||
// Type: Float.
|
||||
constexpr int kInputTensorBoxes = 0;
|
||||
// Shape: [num_boxes]
|
||||
// Type: Float.
|
||||
constexpr int kInputTensorScores = 1;
|
||||
// Max number of boxes to output. Actual output can be smaller.
|
||||
// Type: Int32.
|
||||
constexpr int kInputTensorMaxOutputSize = 2;
|
||||
// Type: Float.
|
||||
constexpr int kInputTensorIouThreshold = 3;
|
||||
// Type: Float.
|
||||
constexpr int kInputTensorScoreThreshold = 4;
|
||||
// Only applies to NON_MAX_SUPPRESSION_V5.
|
||||
// Type: Float.
|
||||
constexpr int kInputTensorSigma = 5;
|
||||
|
||||
// Indices of selected boxes. Shape: [num_selected_indices]
|
||||
// Type: Int32.
|
||||
constexpr int kNMSOutputTensorSelectedIndices = 0;
|
||||
// Type: Int32.
|
||||
constexpr int kNMSOutputTensorNumSelectedIndices = 1;
|
||||
|
||||
// Indices of selected boxes. Shape: [num_selected_indices]
|
||||
// Type: Int32.
|
||||
constexpr int kSoftNMSOutputTensorSelectedIndices = 0;
|
||||
// Scores of selected boxes. Shape: [num_selected_indices]
|
||||
// Type: Float.
|
||||
constexpr int kSoftNMSOutputTensorSelectedScores = 1;
|
||||
// Type: Int32.
|
||||
constexpr int kSoftNMSOutputTensorNumSelectedIndices = 2;
|
||||
|
||||
TfLiteStatus SetTensorSizes(TfLiteContext* context, TfLiteTensor* tensor,
|
||||
std::initializer_list<int> values) {
|
||||
TfLiteIntArray* size = TfLiteIntArrayCreate(values.size());
|
||||
int index = 0;
|
||||
for (const auto& v : values) {
|
||||
size->data[index++] = v;
|
||||
}
|
||||
return context->ResizeTensor(context, tensor, size);
|
||||
}
|
||||
|
||||
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
|
||||
const int num_inputs = NumInputs(node);
|
||||
const bool is_soft_nms = num_inputs == 6;
|
||||
if (num_inputs != 5 && num_inputs != 6) {
|
||||
context->ReportError(context, "Found NMS op with invalid num inputs: %d",
|
||||
NumInputs(node));
|
||||
return kTfLiteError;
|
||||
}
|
||||
|
||||
// Boxes & Scores.
|
||||
const TfLiteTensor* input_boxes = GetInput(context, node, kInputTensorBoxes);
|
||||
TF_LITE_ENSURE_EQ(context, input_boxes->type, kTfLiteFloat32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_boxes), 2);
|
||||
TF_LITE_ENSURE_EQ(context, SizeOfDimension(input_boxes, 1), 4);
|
||||
const int num_boxes = SizeOfDimension(input_boxes, 0);
|
||||
const TfLiteTensor* input_scores =
|
||||
GetInput(context, node, kInputTensorScores);
|
||||
TF_LITE_ENSURE_EQ(context, input_scores->type, kTfLiteFloat32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_scores), 1);
|
||||
TF_LITE_ENSURE_EQ(context, num_boxes, SizeOfDimension(input_scores, 0));
|
||||
|
||||
// Max output size.
|
||||
const TfLiteTensor* input_max_output_size =
|
||||
GetInput(context, node, kInputTensorMaxOutputSize);
|
||||
TF_LITE_ENSURE_EQ(context, input_max_output_size->type, kTfLiteInt32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_max_output_size), 0);
|
||||
// TODO(b/265135869): Add support for non-constant max_output_size by making
|
||||
// output dynamic?
|
||||
if (!IsConstantTensor(input_max_output_size)) {
|
||||
context->ReportError(context, "Max output size should be a constant");
|
||||
return kTfLiteError;
|
||||
}
|
||||
int max_output_size_value = *GetTensorData<int>(input_max_output_size);
|
||||
TF_LITE_ENSURE(context, (max_output_size_value >= 0));
|
||||
|
||||
// IoU & Score thresholds.
|
||||
const TfLiteTensor* input_iou_threshold =
|
||||
GetInput(context, node, kInputTensorIouThreshold);
|
||||
TF_LITE_ENSURE_EQ(context, input_iou_threshold->type, kTfLiteFloat32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_iou_threshold), 0);
|
||||
const TfLiteTensor* input_score_threshold =
|
||||
GetInput(context, node, kInputTensorScoreThreshold);
|
||||
TF_LITE_ENSURE_EQ(context, input_iou_threshold->type, kTfLiteFloat32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_score_threshold), 0);
|
||||
|
||||
if (is_soft_nms) {
|
||||
const TfLiteTensor* input_sigma =
|
||||
GetInput(context, node, kInputTensorSigma);
|
||||
TF_LITE_ENSURE_EQ(context, input_sigma->type, kTfLiteFloat32);
|
||||
TF_LITE_ENSURE_EQ(context, NumDimensions(input_sigma), 0);
|
||||
|
||||
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 3);
|
||||
TfLiteTensor* output_selected_indices =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorSelectedIndices);
|
||||
output_selected_indices->type = kTfLiteInt32;
|
||||
SetTensorSizes(context, output_selected_indices, {max_output_size_value});
|
||||
TfLiteTensor* output_selected_scores =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorSelectedScores);
|
||||
output_selected_scores->type = kTfLiteFloat32;
|
||||
SetTensorSizes(context, output_selected_scores, {max_output_size_value});
|
||||
TfLiteTensor* output_num_selected_indices =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorNumSelectedIndices);
|
||||
output_num_selected_indices->type = kTfLiteInt32;
|
||||
SetTensorSizes(context, output_num_selected_indices, {});
|
||||
} else {
|
||||
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 2);
|
||||
TfLiteTensor* output_selected_indices =
|
||||
GetOutput(context, node, kNMSOutputTensorSelectedIndices);
|
||||
output_selected_indices->type = kTfLiteInt32;
|
||||
SetTensorSizes(context, output_selected_indices, {max_output_size_value});
|
||||
TfLiteTensor* output_num_selected_indices =
|
||||
GetOutput(context, node, kNMSOutputTensorNumSelectedIndices);
|
||||
output_num_selected_indices->type = kTfLiteInt32;
|
||||
SetTensorSizes(context, output_num_selected_indices, {});
|
||||
}
|
||||
|
||||
return kTfLiteOk;
|
||||
}
|
||||
|
||||
// If num_selected_indices < max_output_size, the output tensor can contain
|
||||
// garbage values initially present in memory. This causes segfault in
|
||||
// downstream ops such as GATHER, since one of the outputs denotes indices and
|
||||
// int garbage values can be pretty large. This method zeroes-out the remaining
|
||||
// values.
|
||||
// NOTE: We ensure memory being reset is valid, by setting pertinent output
|
||||
// tensors to max_output_size length in Prepare.
|
||||
void ResetUnusedElementsToZeroes(const int max_output_size,
|
||||
const int num_selected_indices,
|
||||
int* selected_indices,
|
||||
float* selected_scores) {
|
||||
for (int i = num_selected_indices; i < max_output_size; ++i) {
|
||||
selected_indices[i] = 0;
|
||||
if (selected_scores) {
|
||||
selected_scores[i] = 0.0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
|
||||
const bool is_soft_nms = NumInputs(node) == 6;
|
||||
|
||||
const TfLiteTensor* input_boxes = GetInput(context, node, kInputTensorBoxes);
|
||||
const int num_boxes = SizeOfDimension(input_boxes, 0);
|
||||
const TfLiteTensor* input_scores =
|
||||
GetInput(context, node, kInputTensorScores);
|
||||
const TfLiteTensor* input_max_output_size =
|
||||
GetInput(context, node, kInputTensorMaxOutputSize);
|
||||
const int max_output_size_value = *GetTensorData<int>(input_max_output_size);
|
||||
const TfLiteTensor* input_iou_threshold =
|
||||
GetInput(context, node, kInputTensorIouThreshold);
|
||||
const float iou_threshold = *GetTensorData<float>(input_iou_threshold);
|
||||
const TfLiteTensor* input_score_threshold =
|
||||
GetInput(context, node, kInputTensorScoreThreshold);
|
||||
const float score_threshold = *GetTensorData<float>(input_score_threshold);
|
||||
|
||||
TfLiteTensor* output_selected_indices = nullptr;
|
||||
TfLiteTensor* output_selected_scores = nullptr;
|
||||
TfLiteTensor* output_num_selected_indices = nullptr;
|
||||
|
||||
if (is_soft_nms) {
|
||||
const TfLiteTensor* input_sigma =
|
||||
GetInput(context, node, kInputTensorSigma);
|
||||
const float soft_nms_sigma = *GetTensorData<float>(input_sigma);
|
||||
if (soft_nms_sigma < 0) {
|
||||
context->ReportError(context, "Invalid sigma value for soft NMS: %f",
|
||||
soft_nms_sigma);
|
||||
return kTfLiteError;
|
||||
}
|
||||
|
||||
output_selected_indices =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorSelectedIndices);
|
||||
output_selected_scores =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorSelectedScores);
|
||||
output_num_selected_indices =
|
||||
GetOutput(context, node, kSoftNMSOutputTensorNumSelectedIndices);
|
||||
reference_ops::NonMaxSuppression(
|
||||
input_boxes->data.f, num_boxes, input_scores->data.f,
|
||||
max_output_size_value, iou_threshold, score_threshold, soft_nms_sigma,
|
||||
output_selected_indices->data.i32, output_selected_scores->data.f,
|
||||
output_num_selected_indices->data.i32);
|
||||
ResetUnusedElementsToZeroes(
|
||||
max_output_size_value, *output_num_selected_indices->data.i32,
|
||||
output_selected_indices->data.i32, output_selected_scores->data.f);
|
||||
} else {
|
||||
output_selected_indices =
|
||||
GetOutput(context, node, kNMSOutputTensorSelectedIndices);
|
||||
output_num_selected_indices =
|
||||
GetOutput(context, node, kNMSOutputTensorNumSelectedIndices);
|
||||
reference_ops::NonMaxSuppression(
|
||||
input_boxes->data.f, num_boxes, input_scores->data.f,
|
||||
max_output_size_value, iou_threshold, score_threshold, /**sigma=**/ 0.0,
|
||||
output_selected_indices->data.i32, /**selected_scores=**/ nullptr,
|
||||
output_num_selected_indices->data.i32);
|
||||
ResetUnusedElementsToZeroes(max_output_size_value,
|
||||
*output_num_selected_indices->data.i32,
|
||||
output_selected_indices->data.i32, nullptr);
|
||||
}
|
||||
|
||||
return kTfLiteOk;
|
||||
}
|
||||
} // namespace non_max_suppression
|
||||
|
||||
TfLiteRegistration* Register_NON_MAX_SUPPRESSION_V4() {
|
||||
static TfLiteRegistration r = {nullptr, nullptr, non_max_suppression::Prepare,
|
||||
non_max_suppression::Eval};
|
||||
return &r;
|
||||
}
|
||||
|
||||
TfLiteRegistration* Register_NON_MAX_SUPPRESSION_V5() {
|
||||
static TfLiteRegistration r = {nullptr, nullptr, non_max_suppression::Prepare,
|
||||
non_max_suppression::Eval};
|
||||
return &r;
|
||||
}
|
||||
|
||||
} // namespace builtin
|
||||
} // namespace ops
|
||||
} // namespace tflite
|
||||
176
tensorflow/lite/kernels/non_max_suppression_test.cc
Normal file
176
tensorflow/lite/kernels/non_max_suppression_test.cc
Normal file
@ -0,0 +1,176 @@
|
||||
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
==============================================================================*/
|
||||
#include <gtest/gtest.h>
|
||||
#include "tensorflow/lite/interpreter.h"
|
||||
#include "tensorflow/lite/kernels/register.h"
|
||||
#include "tensorflow/lite/kernels/test_util.h"
|
||||
#include "tensorflow/lite/model.h"
|
||||
|
||||
namespace tflite {
|
||||
namespace {
|
||||
|
||||
using ::testing::ElementsAreArray;
|
||||
|
||||
class BaseNMSOp : public SingleOpModel {
|
||||
public:
|
||||
void SetScores(std::initializer_list<float> data) {
|
||||
PopulateTensor(input_scores_, data);
|
||||
}
|
||||
|
||||
void SetScoreThreshold(float score_threshold) {
|
||||
PopulateTensor(input_score_threshold_, {score_threshold});
|
||||
}
|
||||
|
||||
std::vector<int> GetSelectedIndices() {
|
||||
return ExtractVector<int>(output_selected_indices_);
|
||||
}
|
||||
|
||||
std::vector<float> GetSelectedScores() {
|
||||
return ExtractVector<float>(output_selected_scores_);
|
||||
}
|
||||
|
||||
std::vector<int> GetNumSelectedIndices() {
|
||||
return ExtractVector<int>(output_num_selected_indices_);
|
||||
}
|
||||
|
||||
protected:
|
||||
int input_boxes_;
|
||||
int input_scores_;
|
||||
int input_max_output_size_;
|
||||
int input_iou_threshold_;
|
||||
int input_score_threshold_;
|
||||
int input_sigma_;
|
||||
|
||||
int output_selected_indices_;
|
||||
int output_selected_scores_;
|
||||
int output_num_selected_indices_;
|
||||
};
|
||||
|
||||
class NonMaxSuppressionV4OpModel : public BaseNMSOp {
|
||||
public:
|
||||
explicit NonMaxSuppressionV4OpModel(const int max_output_size,
|
||||
const float iou_threshold) {
|
||||
const int num_boxes = 6;
|
||||
input_boxes_ = AddInput({TensorType_FLOAT32, {num_boxes, 4}});
|
||||
input_scores_ = AddInput({TensorType_FLOAT32, {num_boxes}});
|
||||
input_max_output_size_ = AddConstInput(TensorType_INT32, {max_output_size});
|
||||
input_iou_threshold_ = AddConstInput(TensorType_FLOAT32, {iou_threshold});
|
||||
input_score_threshold_ = AddInput({TensorType_FLOAT32, {}});
|
||||
|
||||
output_selected_indices_ = AddOutput(TensorType_INT32);
|
||||
|
||||
output_num_selected_indices_ = AddOutput(TensorType_INT32);
|
||||
|
||||
SetBuiltinOp(BuiltinOperator_NON_MAX_SUPPRESSION_V4,
|
||||
BuiltinOptions_NonMaxSuppressionV4Options,
|
||||
CreateNonMaxSuppressionV4Options(builder_).Union());
|
||||
BuildInterpreter({GetShape(input_boxes_), GetShape(input_scores_),
|
||||
GetShape(input_max_output_size_),
|
||||
GetShape(input_iou_threshold_),
|
||||
GetShape(input_score_threshold_)});
|
||||
|
||||
// Default data.
|
||||
PopulateTensor<float>(input_boxes_, {
|
||||
1, 1, 0, 0, // Box 0
|
||||
0, 0.1, 1, 1.1, // Box 1
|
||||
0, .9f, 1, -0.1, // Box 2
|
||||
0, 10, 1, 11, // Box 3
|
||||
1, 10.1f, 0, 11.1, // Box 4
|
||||
1, 101, 0, 100 // Box 5
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
TEST(NonMaxSuppressionV4OpModel, TestOutput) {
|
||||
NonMaxSuppressionV4OpModel nms(6, 0.5);
|
||||
nms.SetScores({0.9, 0.75, 0.6, 0.95, 0.5, 0.3});
|
||||
nms.SetScoreThreshold(0.4);
|
||||
nms.Invoke();
|
||||
EXPECT_THAT(nms.GetNumSelectedIndices(), ElementsAreArray({2}));
|
||||
EXPECT_THAT(nms.GetSelectedIndices(), ElementsAreArray({3, 0, 0, 0, 0, 0}));
|
||||
|
||||
nms.SetScoreThreshold(0.99);
|
||||
nms.Invoke();
|
||||
EXPECT_THAT(nms.GetNumSelectedIndices(), ElementsAreArray({0}));
|
||||
// The first two indices should be zeroed-out.
|
||||
EXPECT_THAT(nms.GetSelectedIndices(), ElementsAreArray({0, 0, 0, 0, 0, 0}));
|
||||
}
|
||||
|
||||
TEST(NonMaxSuppressionV4OpModel, TestOutputWithZeroMaxOutput) {
|
||||
NonMaxSuppressionV4OpModel nms(0, 0.5);
|
||||
nms.SetScores({0.9, 0.75, 0.6, 0.95, 0.5, 0.3});
|
||||
nms.SetScoreThreshold(0.4);
|
||||
nms.Invoke();
|
||||
EXPECT_THAT(nms.GetNumSelectedIndices(), ElementsAreArray({0}));
|
||||
}
|
||||
|
||||
class NonMaxSuppressionV5OpModel : public BaseNMSOp {
|
||||
public:
|
||||
explicit NonMaxSuppressionV5OpModel(const int max_output_size,
|
||||
const float iou_threshold,
|
||||
const float sigma) {
|
||||
const int num_boxes = 6;
|
||||
input_boxes_ = AddInput({TensorType_FLOAT32, {num_boxes, 4}});
|
||||
input_scores_ = AddInput({TensorType_FLOAT32, {num_boxes}});
|
||||
input_max_output_size_ = AddConstInput(TensorType_INT32, {max_output_size});
|
||||
input_iou_threshold_ = AddConstInput(TensorType_FLOAT32, {iou_threshold});
|
||||
input_score_threshold_ = AddInput({TensorType_FLOAT32, {}});
|
||||
input_sigma_ = AddConstInput(TensorType_FLOAT32, {sigma});
|
||||
|
||||
output_selected_indices_ = AddOutput(TensorType_INT32);
|
||||
output_selected_scores_ = AddOutput(TensorType_FLOAT32);
|
||||
output_num_selected_indices_ = AddOutput(TensorType_INT32);
|
||||
|
||||
SetBuiltinOp(BuiltinOperator_NON_MAX_SUPPRESSION_V5,
|
||||
BuiltinOptions_NonMaxSuppressionV5Options,
|
||||
CreateNonMaxSuppressionV5Options(builder_).Union());
|
||||
|
||||
BuildInterpreter(
|
||||
{GetShape(input_boxes_), GetShape(input_scores_),
|
||||
GetShape(input_max_output_size_), GetShape(input_iou_threshold_),
|
||||
GetShape(input_score_threshold_), GetShape(input_sigma_)});
|
||||
|
||||
// Default data.
|
||||
PopulateTensor<float>(input_boxes_, {
|
||||
1, 1, 0, 0, // Box 0
|
||||
0, 0.1, 1, 1.1, // Box 1
|
||||
0, .9f, 1, -0.1, // Box 2
|
||||
0, 10, 1, 11, // Box 3
|
||||
1, 10.1f, 0, 11.1, // Box 4
|
||||
1, 101, 0, 100 // Box 5
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
TEST(NonMaxSuppressionV5OpModel, TestOutput) {
|
||||
NonMaxSuppressionV5OpModel nms(6, 0.5, 0.5);
|
||||
nms.SetScores({0.9, 0.75, 0.6, 0.95, 0.5, 0.3});
|
||||
nms.SetScoreThreshold(0.0);
|
||||
nms.Invoke();
|
||||
EXPECT_THAT(nms.GetNumSelectedIndices(), ElementsAreArray({3}));
|
||||
EXPECT_THAT(nms.GetSelectedIndices(), ElementsAreArray({3, 0, 5, 0, 0, 0}));
|
||||
EXPECT_THAT(nms.GetSelectedScores(),
|
||||
ElementsAreArray({0.95, 0.9, 0.3, 0.0, 0.0, 0.0}));
|
||||
|
||||
// No candidate gets selected. But the outputs should be zeroed out.
|
||||
nms.SetScoreThreshold(0.99);
|
||||
nms.Invoke();
|
||||
EXPECT_THAT(nms.GetNumSelectedIndices(), ElementsAreArray({0}));
|
||||
EXPECT_THAT(nms.GetSelectedIndices(), ElementsAreArray({0, 0, 0, 0, 0, 0}));
|
||||
EXPECT_THAT(nms.GetSelectedScores(),
|
||||
ElementsAreArray({0.0, 0.0, 0.0, 0.0, 0.0, 0.0}));
|
||||
}
|
||||
} // namespace
|
||||
} // namespace tflite
|
||||
@ -144,6 +144,8 @@ TfLiteRegistration* Register_MATRIX_DIAG();
|
||||
TfLiteRegistration* Register_QUANTIZE();
|
||||
TfLiteRegistration* Register_MATRIX_SET_DIAG();
|
||||
TfLiteRegistration* Register_HARD_SWISH();
|
||||
TfLiteRegistration* Register_NON_MAX_SUPPRESSION_V4();
|
||||
TfLiteRegistration* Register_NON_MAX_SUPPRESSION_V5();
|
||||
|
||||
const TfLiteRegistration* BuiltinOpResolver::FindOp(tflite::BuiltinOperator op,
|
||||
int version) const {
|
||||
@ -382,6 +384,10 @@ BuiltinOpResolver::BuiltinOpResolver() {
|
||||
/* min_version */ 1,
|
||||
/* max_version */ 2);
|
||||
AddBuiltin(BuiltinOperator_MATRIX_SET_DIAG, Register_MATRIX_SET_DIAG());
|
||||
AddBuiltin(BuiltinOperator_NON_MAX_SUPPRESSION_V4,
|
||||
Register_NON_MAX_SUPPRESSION_V4());
|
||||
AddBuiltin(BuiltinOperator_NON_MAX_SUPPRESSION_V5,
|
||||
Register_NON_MAX_SUPPRESSION_V5());
|
||||
|
||||
// WARNING: Control flow ops are experimental and subject to change.
|
||||
AddBuiltin(BuiltinOperator_IF, tflite::ops::custom::Register_IF());
|
||||
|
||||
@ -233,6 +233,8 @@ enum BuiltinOperator : byte {
|
||||
HARD_SWISH = 117,
|
||||
IF = 118,
|
||||
WHILE = 119,
|
||||
NON_MAX_SUPPRESSION_V4 = 120,
|
||||
NON_MAX_SUPPRESSION_V5 = 121,
|
||||
}
|
||||
|
||||
// Options for the builtin operators.
|
||||
@ -330,7 +332,9 @@ union BuiltinOptions {
|
||||
HardSwishOptions,
|
||||
IfOptions,
|
||||
WhileOptions,
|
||||
DepthToSpaceOptions
|
||||
DepthToSpaceOptions,
|
||||
NonMaxSuppressionV4Options,
|
||||
NonMaxSuppressionV5Options
|
||||
}
|
||||
|
||||
enum Padding : byte { SAME, VALID }
|
||||
@ -802,6 +806,12 @@ table WhileOptions {
|
||||
body_subgraph_index:int;
|
||||
}
|
||||
|
||||
table NonMaxSuppressionV4Options {
|
||||
}
|
||||
|
||||
table NonMaxSuppressionV5Options {
|
||||
}
|
||||
|
||||
// An OperatorCode can be an enum value (BuiltinOperator) if the operator is a
|
||||
// builtin, or a string if the operator is custom.
|
||||
table OperatorCode {
|
||||
|
||||
@ -313,6 +313,12 @@ struct IfOptionsT;
|
||||
struct WhileOptions;
|
||||
struct WhileOptionsT;
|
||||
|
||||
struct NonMaxSuppressionV4Options;
|
||||
struct NonMaxSuppressionV4OptionsT;
|
||||
|
||||
struct NonMaxSuppressionV5Options;
|
||||
struct NonMaxSuppressionV5OptionsT;
|
||||
|
||||
struct OperatorCode;
|
||||
struct OperatorCodeT;
|
||||
|
||||
@ -589,11 +595,13 @@ enum BuiltinOperator {
|
||||
BuiltinOperator_HARD_SWISH = 117,
|
||||
BuiltinOperator_IF = 118,
|
||||
BuiltinOperator_WHILE = 119,
|
||||
BuiltinOperator_NON_MAX_SUPPRESSION_V4 = 120,
|
||||
BuiltinOperator_NON_MAX_SUPPRESSION_V5 = 121,
|
||||
BuiltinOperator_MIN = BuiltinOperator_ADD,
|
||||
BuiltinOperator_MAX = BuiltinOperator_WHILE
|
||||
BuiltinOperator_MAX = BuiltinOperator_NON_MAX_SUPPRESSION_V5
|
||||
};
|
||||
|
||||
inline const BuiltinOperator (&EnumValuesBuiltinOperator())[120] {
|
||||
inline const BuiltinOperator (&EnumValuesBuiltinOperator())[122] {
|
||||
static const BuiltinOperator values[] = {
|
||||
BuiltinOperator_ADD,
|
||||
BuiltinOperator_AVERAGE_POOL_2D,
|
||||
@ -714,7 +722,9 @@ inline const BuiltinOperator (&EnumValuesBuiltinOperator())[120] {
|
||||
BuiltinOperator_ROUND,
|
||||
BuiltinOperator_HARD_SWISH,
|
||||
BuiltinOperator_IF,
|
||||
BuiltinOperator_WHILE
|
||||
BuiltinOperator_WHILE,
|
||||
BuiltinOperator_NON_MAX_SUPPRESSION_V4,
|
||||
BuiltinOperator_NON_MAX_SUPPRESSION_V5
|
||||
};
|
||||
return values;
|
||||
}
|
||||
@ -841,13 +851,15 @@ inline const char * const *EnumNamesBuiltinOperator() {
|
||||
"HARD_SWISH",
|
||||
"IF",
|
||||
"WHILE",
|
||||
"NON_MAX_SUPPRESSION_V4",
|
||||
"NON_MAX_SUPPRESSION_V5",
|
||||
nullptr
|
||||
};
|
||||
return names;
|
||||
}
|
||||
|
||||
inline const char *EnumNameBuiltinOperator(BuiltinOperator e) {
|
||||
if (e < BuiltinOperator_ADD || e > BuiltinOperator_WHILE) return "";
|
||||
if (e < BuiltinOperator_ADD || e > BuiltinOperator_NON_MAX_SUPPRESSION_V5) return "";
|
||||
const size_t index = static_cast<size_t>(e);
|
||||
return EnumNamesBuiltinOperator()[index];
|
||||
}
|
||||
@ -948,11 +960,13 @@ enum BuiltinOptions {
|
||||
BuiltinOptions_IfOptions = 92,
|
||||
BuiltinOptions_WhileOptions = 93,
|
||||
BuiltinOptions_DepthToSpaceOptions = 94,
|
||||
BuiltinOptions_NonMaxSuppressionV4Options = 95,
|
||||
BuiltinOptions_NonMaxSuppressionV5Options = 96,
|
||||
BuiltinOptions_MIN = BuiltinOptions_NONE,
|
||||
BuiltinOptions_MAX = BuiltinOptions_DepthToSpaceOptions
|
||||
BuiltinOptions_MAX = BuiltinOptions_NonMaxSuppressionV5Options
|
||||
};
|
||||
|
||||
inline const BuiltinOptions (&EnumValuesBuiltinOptions())[95] {
|
||||
inline const BuiltinOptions (&EnumValuesBuiltinOptions())[97] {
|
||||
static const BuiltinOptions values[] = {
|
||||
BuiltinOptions_NONE,
|
||||
BuiltinOptions_Conv2DOptions,
|
||||
@ -1048,7 +1062,9 @@ inline const BuiltinOptions (&EnumValuesBuiltinOptions())[95] {
|
||||
BuiltinOptions_HardSwishOptions,
|
||||
BuiltinOptions_IfOptions,
|
||||
BuiltinOptions_WhileOptions,
|
||||
BuiltinOptions_DepthToSpaceOptions
|
||||
BuiltinOptions_DepthToSpaceOptions,
|
||||
BuiltinOptions_NonMaxSuppressionV4Options,
|
||||
BuiltinOptions_NonMaxSuppressionV5Options
|
||||
};
|
||||
return values;
|
||||
}
|
||||
@ -1150,13 +1166,15 @@ inline const char * const *EnumNamesBuiltinOptions() {
|
||||
"IfOptions",
|
||||
"WhileOptions",
|
||||
"DepthToSpaceOptions",
|
||||
"NonMaxSuppressionV4Options",
|
||||
"NonMaxSuppressionV5Options",
|
||||
nullptr
|
||||
};
|
||||
return names;
|
||||
}
|
||||
|
||||
inline const char *EnumNameBuiltinOptions(BuiltinOptions e) {
|
||||
if (e < BuiltinOptions_NONE || e > BuiltinOptions_DepthToSpaceOptions) return "";
|
||||
if (e < BuiltinOptions_NONE || e > BuiltinOptions_NonMaxSuppressionV5Options) return "";
|
||||
const size_t index = static_cast<size_t>(e);
|
||||
return EnumNamesBuiltinOptions()[index];
|
||||
}
|
||||
@ -1541,6 +1559,14 @@ template<> struct BuiltinOptionsTraits<DepthToSpaceOptions> {
|
||||
static const BuiltinOptions enum_value = BuiltinOptions_DepthToSpaceOptions;
|
||||
};
|
||||
|
||||
template<> struct BuiltinOptionsTraits<NonMaxSuppressionV4Options> {
|
||||
static const BuiltinOptions enum_value = BuiltinOptions_NonMaxSuppressionV4Options;
|
||||
};
|
||||
|
||||
template<> struct BuiltinOptionsTraits<NonMaxSuppressionV5Options> {
|
||||
static const BuiltinOptions enum_value = BuiltinOptions_NonMaxSuppressionV5Options;
|
||||
};
|
||||
|
||||
struct BuiltinOptionsUnion {
|
||||
BuiltinOptions type;
|
||||
void *value;
|
||||
@ -2325,6 +2351,22 @@ struct BuiltinOptionsUnion {
|
||||
return type == BuiltinOptions_DepthToSpaceOptions ?
|
||||
reinterpret_cast<const DepthToSpaceOptionsT *>(value) : nullptr;
|
||||
}
|
||||
NonMaxSuppressionV4OptionsT *AsNonMaxSuppressionV4Options() {
|
||||
return type == BuiltinOptions_NonMaxSuppressionV4Options ?
|
||||
reinterpret_cast<NonMaxSuppressionV4OptionsT *>(value) : nullptr;
|
||||
}
|
||||
const NonMaxSuppressionV4OptionsT *AsNonMaxSuppressionV4Options() const {
|
||||
return type == BuiltinOptions_NonMaxSuppressionV4Options ?
|
||||
reinterpret_cast<const NonMaxSuppressionV4OptionsT *>(value) : nullptr;
|
||||
}
|
||||
NonMaxSuppressionV5OptionsT *AsNonMaxSuppressionV5Options() {
|
||||
return type == BuiltinOptions_NonMaxSuppressionV5Options ?
|
||||
reinterpret_cast<NonMaxSuppressionV5OptionsT *>(value) : nullptr;
|
||||
}
|
||||
const NonMaxSuppressionV5OptionsT *AsNonMaxSuppressionV5Options() const {
|
||||
return type == BuiltinOptions_NonMaxSuppressionV5Options ?
|
||||
reinterpret_cast<const NonMaxSuppressionV5OptionsT *>(value) : nullptr;
|
||||
}
|
||||
};
|
||||
|
||||
bool VerifyBuiltinOptions(flatbuffers::Verifier &verifier, const void *obj, BuiltinOptions type);
|
||||
@ -8104,6 +8146,86 @@ inline flatbuffers::Offset<WhileOptions> CreateWhileOptions(
|
||||
|
||||
flatbuffers::Offset<WhileOptions> CreateWhileOptions(flatbuffers::FlatBufferBuilder &_fbb, const WhileOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
|
||||
|
||||
struct NonMaxSuppressionV4OptionsT : public flatbuffers::NativeTable {
|
||||
typedef NonMaxSuppressionV4Options TableType;
|
||||
NonMaxSuppressionV4OptionsT() {
|
||||
}
|
||||
};
|
||||
|
||||
struct NonMaxSuppressionV4Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
|
||||
typedef NonMaxSuppressionV4OptionsT NativeTableType;
|
||||
bool Verify(flatbuffers::Verifier &verifier) const {
|
||||
return VerifyTableStart(verifier) &&
|
||||
verifier.EndTable();
|
||||
}
|
||||
NonMaxSuppressionV4OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
|
||||
void UnPackTo(NonMaxSuppressionV4OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
|
||||
static flatbuffers::Offset<NonMaxSuppressionV4Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
|
||||
};
|
||||
|
||||
struct NonMaxSuppressionV4OptionsBuilder {
|
||||
flatbuffers::FlatBufferBuilder &fbb_;
|
||||
flatbuffers::uoffset_t start_;
|
||||
explicit NonMaxSuppressionV4OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
|
||||
: fbb_(_fbb) {
|
||||
start_ = fbb_.StartTable();
|
||||
}
|
||||
NonMaxSuppressionV4OptionsBuilder &operator=(const NonMaxSuppressionV4OptionsBuilder &);
|
||||
flatbuffers::Offset<NonMaxSuppressionV4Options> Finish() {
|
||||
const auto end = fbb_.EndTable(start_);
|
||||
auto o = flatbuffers::Offset<NonMaxSuppressionV4Options>(end);
|
||||
return o;
|
||||
}
|
||||
};
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(
|
||||
flatbuffers::FlatBufferBuilder &_fbb) {
|
||||
NonMaxSuppressionV4OptionsBuilder builder_(_fbb);
|
||||
return builder_.Finish();
|
||||
}
|
||||
|
||||
flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
|
||||
|
||||
struct NonMaxSuppressionV5OptionsT : public flatbuffers::NativeTable {
|
||||
typedef NonMaxSuppressionV5Options TableType;
|
||||
NonMaxSuppressionV5OptionsT() {
|
||||
}
|
||||
};
|
||||
|
||||
struct NonMaxSuppressionV5Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
|
||||
typedef NonMaxSuppressionV5OptionsT NativeTableType;
|
||||
bool Verify(flatbuffers::Verifier &verifier) const {
|
||||
return VerifyTableStart(verifier) &&
|
||||
verifier.EndTable();
|
||||
}
|
||||
NonMaxSuppressionV5OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
|
||||
void UnPackTo(NonMaxSuppressionV5OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
|
||||
static flatbuffers::Offset<NonMaxSuppressionV5Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
|
||||
};
|
||||
|
||||
struct NonMaxSuppressionV5OptionsBuilder {
|
||||
flatbuffers::FlatBufferBuilder &fbb_;
|
||||
flatbuffers::uoffset_t start_;
|
||||
explicit NonMaxSuppressionV5OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
|
||||
: fbb_(_fbb) {
|
||||
start_ = fbb_.StartTable();
|
||||
}
|
||||
NonMaxSuppressionV5OptionsBuilder &operator=(const NonMaxSuppressionV5OptionsBuilder &);
|
||||
flatbuffers::Offset<NonMaxSuppressionV5Options> Finish() {
|
||||
const auto end = fbb_.EndTable(start_);
|
||||
auto o = flatbuffers::Offset<NonMaxSuppressionV5Options>(end);
|
||||
return o;
|
||||
}
|
||||
};
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(
|
||||
flatbuffers::FlatBufferBuilder &_fbb) {
|
||||
NonMaxSuppressionV5OptionsBuilder builder_(_fbb);
|
||||
return builder_.Finish();
|
||||
}
|
||||
|
||||
flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
|
||||
|
||||
struct OperatorCodeT : public flatbuffers::NativeTable {
|
||||
typedef OperatorCode TableType;
|
||||
BuiltinOperator builtin_code;
|
||||
@ -8522,6 +8644,12 @@ struct Operator FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
|
||||
const DepthToSpaceOptions *builtin_options_as_DepthToSpaceOptions() const {
|
||||
return builtin_options_type() == BuiltinOptions_DepthToSpaceOptions ? static_cast<const DepthToSpaceOptions *>(builtin_options()) : nullptr;
|
||||
}
|
||||
const NonMaxSuppressionV4Options *builtin_options_as_NonMaxSuppressionV4Options() const {
|
||||
return builtin_options_type() == BuiltinOptions_NonMaxSuppressionV4Options ? static_cast<const NonMaxSuppressionV4Options *>(builtin_options()) : nullptr;
|
||||
}
|
||||
const NonMaxSuppressionV5Options *builtin_options_as_NonMaxSuppressionV5Options() const {
|
||||
return builtin_options_type() == BuiltinOptions_NonMaxSuppressionV5Options ? static_cast<const NonMaxSuppressionV5Options *>(builtin_options()) : nullptr;
|
||||
}
|
||||
const flatbuffers::Vector<uint8_t> *custom_options() const {
|
||||
return GetPointer<const flatbuffers::Vector<uint8_t> *>(VT_CUSTOM_OPTIONS);
|
||||
}
|
||||
@ -8934,6 +9062,14 @@ template<> inline const DepthToSpaceOptions *Operator::builtin_options_as<DepthT
|
||||
return builtin_options_as_DepthToSpaceOptions();
|
||||
}
|
||||
|
||||
template<> inline const NonMaxSuppressionV4Options *Operator::builtin_options_as<NonMaxSuppressionV4Options>() const {
|
||||
return builtin_options_as_NonMaxSuppressionV4Options();
|
||||
}
|
||||
|
||||
template<> inline const NonMaxSuppressionV5Options *Operator::builtin_options_as<NonMaxSuppressionV5Options>() const {
|
||||
return builtin_options_as_NonMaxSuppressionV5Options();
|
||||
}
|
||||
|
||||
struct OperatorBuilder {
|
||||
flatbuffers::FlatBufferBuilder &fbb_;
|
||||
flatbuffers::uoffset_t start_;
|
||||
@ -12043,6 +12179,52 @@ inline flatbuffers::Offset<WhileOptions> CreateWhileOptions(flatbuffers::FlatBuf
|
||||
_body_subgraph_index);
|
||||
}
|
||||
|
||||
inline NonMaxSuppressionV4OptionsT *NonMaxSuppressionV4Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
|
||||
auto _o = new NonMaxSuppressionV4OptionsT();
|
||||
UnPackTo(_o, _resolver);
|
||||
return _o;
|
||||
}
|
||||
|
||||
inline void NonMaxSuppressionV4Options::UnPackTo(NonMaxSuppressionV4OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
|
||||
(void)_o;
|
||||
(void)_resolver;
|
||||
}
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV4Options> NonMaxSuppressionV4Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
|
||||
return CreateNonMaxSuppressionV4Options(_fbb, _o, _rehasher);
|
||||
}
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
|
||||
(void)_rehasher;
|
||||
(void)_o;
|
||||
struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NonMaxSuppressionV4OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
|
||||
return tflite::CreateNonMaxSuppressionV4Options(
|
||||
_fbb);
|
||||
}
|
||||
|
||||
inline NonMaxSuppressionV5OptionsT *NonMaxSuppressionV5Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
|
||||
auto _o = new NonMaxSuppressionV5OptionsT();
|
||||
UnPackTo(_o, _resolver);
|
||||
return _o;
|
||||
}
|
||||
|
||||
inline void NonMaxSuppressionV5Options::UnPackTo(NonMaxSuppressionV5OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
|
||||
(void)_o;
|
||||
(void)_resolver;
|
||||
}
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV5Options> NonMaxSuppressionV5Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
|
||||
return CreateNonMaxSuppressionV5Options(_fbb, _o, _rehasher);
|
||||
}
|
||||
|
||||
inline flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
|
||||
(void)_rehasher;
|
||||
(void)_o;
|
||||
struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NonMaxSuppressionV5OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
|
||||
return tflite::CreateNonMaxSuppressionV5Options(
|
||||
_fbb);
|
||||
}
|
||||
|
||||
inline OperatorCodeT *OperatorCode::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
|
||||
auto _o = new OperatorCodeT();
|
||||
UnPackTo(_o, _resolver);
|
||||
@ -12712,6 +12894,14 @@ inline bool VerifyBuiltinOptions(flatbuffers::Verifier &verifier, const void *ob
|
||||
auto ptr = reinterpret_cast<const DepthToSpaceOptions *>(obj);
|
||||
return verifier.VerifyTable(ptr);
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV4Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV4Options *>(obj);
|
||||
return verifier.VerifyTable(ptr);
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV5Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV5Options *>(obj);
|
||||
return verifier.VerifyTable(ptr);
|
||||
}
|
||||
default: return false;
|
||||
}
|
||||
}
|
||||
@ -13106,6 +13296,14 @@ inline void *BuiltinOptionsUnion::UnPack(const void *obj, BuiltinOptions type, c
|
||||
auto ptr = reinterpret_cast<const DepthToSpaceOptions *>(obj);
|
||||
return ptr->UnPack(resolver);
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV4Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV4Options *>(obj);
|
||||
return ptr->UnPack(resolver);
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV5Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV5Options *>(obj);
|
||||
return ptr->UnPack(resolver);
|
||||
}
|
||||
default: return nullptr;
|
||||
}
|
||||
}
|
||||
@ -13488,6 +13686,14 @@ inline flatbuffers::Offset<void> BuiltinOptionsUnion::Pack(flatbuffers::FlatBuff
|
||||
auto ptr = reinterpret_cast<const DepthToSpaceOptionsT *>(value);
|
||||
return CreateDepthToSpaceOptions(_fbb, ptr, _rehasher).Union();
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV4Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV4OptionsT *>(value);
|
||||
return CreateNonMaxSuppressionV4Options(_fbb, ptr, _rehasher).Union();
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV5Options: {
|
||||
auto ptr = reinterpret_cast<const NonMaxSuppressionV5OptionsT *>(value);
|
||||
return CreateNonMaxSuppressionV5Options(_fbb, ptr, _rehasher).Union();
|
||||
}
|
||||
default: return 0;
|
||||
}
|
||||
}
|
||||
@ -13870,6 +14076,14 @@ inline BuiltinOptionsUnion::BuiltinOptionsUnion(const BuiltinOptionsUnion &u) FL
|
||||
value = new DepthToSpaceOptionsT(*reinterpret_cast<DepthToSpaceOptionsT *>(u.value));
|
||||
break;
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV4Options: {
|
||||
value = new NonMaxSuppressionV4OptionsT(*reinterpret_cast<NonMaxSuppressionV4OptionsT *>(u.value));
|
||||
break;
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV5Options: {
|
||||
value = new NonMaxSuppressionV5OptionsT(*reinterpret_cast<NonMaxSuppressionV5OptionsT *>(u.value));
|
||||
break;
|
||||
}
|
||||
default:
|
||||
break;
|
||||
}
|
||||
@ -14347,6 +14561,16 @@ inline void BuiltinOptionsUnion::Reset() {
|
||||
delete ptr;
|
||||
break;
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV4Options: {
|
||||
auto ptr = reinterpret_cast<NonMaxSuppressionV4OptionsT *>(value);
|
||||
delete ptr;
|
||||
break;
|
||||
}
|
||||
case BuiltinOptions_NonMaxSuppressionV5Options: {
|
||||
auto ptr = reinterpret_cast<NonMaxSuppressionV5OptionsT *>(value);
|
||||
delete ptr;
|
||||
break;
|
||||
}
|
||||
default: break;
|
||||
}
|
||||
value = nullptr;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user