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openvino/ngraph/test/backend/multiclass_nms.in.cpp
Ilya Churaev faeaf045a9 Graph comparator to ngraph util (#7729) 
* Moved FrameworkNode to nGraph

* Moved graph comparator to ngraph test util

* Fixed build

* Try to fix centos

* Fix export target

* Moved engine utils to separate library

* Removed ONNX util from common library

* Fixed build

* Fixed code style
2021-10-01 07:24:28 +03:00

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// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
// clang-format off
#ifdef ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
#define DEFAULT_FLOAT_TOLERANCE_BITS ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
#endif
#ifdef ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
#define DEFAULT_DOUBLE_TOLERANCE_BITS ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
#endif
// clang-format on
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "engines_util/test_engines.hpp"
#include "engines_util/test_case.hpp"
#include "util/test_control.hpp"
using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_score) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4}; // N 1, C 2, M 6
const auto scores_shape = Shape{1, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 0, 3};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95,
0.00, 0.00, 1.00, 1.00, 0.00, 0.90, 0.00, 0.00,
1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00};
std::vector<int64_t> expected_valid_outputs = {4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({4, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({4, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_class_id) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4}; // N 1, C 2, M 6
const auto scores_shape = Shape{1, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 0, 3};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90,
0.00, 0.00, 1.00, 1.00, 1.00, 0.95, 0.00, 0.00,
1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00};
std::vector<int64_t> expected_valid_outputs = {4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({4, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({4, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_output_type_i32) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
attrs.output_type = element::i32;
const auto boxes_shape = Shape{1, 6, 4}; // N 1, C 2, M 6
const auto scores_shape = Shape{1, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int32_t> expected_selected_indices = {3, 0, 0, 3};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90,
0.00, 0.00, 1.00, 1.00, 1.00, 0.95, 0.00, 0.00,
1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00};
std::vector<int32_t> expected_valid_outputs = {4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({4, 6}, expected_selected_scores);
test_case.add_expected_output<int32_t>({4, 1}, expected_selected_indices);
test_case.add_expected_output<int32_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_two_batches_two_classes_by_score) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 0, 3, 9, 6, 6, 9};
std::vector<float> expected_selected_scores = {
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00,
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00, // 0
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00,
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00}; // 1
std::vector<int64_t> expected_valid_outputs = {4, 4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({8, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({8, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_two_batches_two_classes_by_class_id) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 0, 3, 9, 6, 6, 9};
std::vector<float> expected_selected_scores = {
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00,
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00, // 0
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00,
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00}; // 1
std::vector<int64_t> expected_valid_outputs = {4, 4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({8, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({8, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_two_batches_two_classes_by_score_cross_batch) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
attrs.sort_result_across_batch = true;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 9, 6, 0, 6, 3, 9};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, // 3
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, // 0
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, // 9
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, // 6
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, // 0
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, // 6
1.00, 0.80, 0.00, 10.00, 1.00, 11.00, // 3
1.00, 0.80, 0.00, 10.00, 1.00, 11.00}; // 9
std::vector<int64_t> expected_valid_outputs = {4, 4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({8, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({8, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_two_batches_two_classes_by_class_id_cross_batch) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
attrs.sort_result_across_batch = true;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 9, 6, 0, 3, 6, 9};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, // 3
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, // 0
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, // 9
0.00, 0.90, 0.00, 0.00, 1.00, 1.00, // 6
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, // 0
1.00, 0.80, 0.00, 10.00, 1.00, 11.00, // 3
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, // 6
1.00, 0.80, 0.00, 10.00, 1.00, 11.00}; // 9
std::vector<int64_t> expected_valid_outputs = {4, 4};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({8, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({8, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_flipped_coordinates) {
std::vector<float> boxes_data = {1.0, 1.0, 0.0, 0.0, 0.0, 0.1, 1.0, 1.1, 0.0, 0.9, 1.0, -0.1,
0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4}; // N 1, C 1, M 6
const auto scores_shape = Shape{1, 1, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 1};
std::vector<float> expected_selected_scores =
{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 1.00, 1.00, 0.00, 0.00, 0.00, 0.75, 0.00, 0.10, 1.00, 1.10};
std::vector<int64_t> expected_valid_outputs = {3};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({3, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({3, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_identical_boxes) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0};
std::vector<float> scores_data = {0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 10, 4}; // N 1, C 1, M 10
const auto scores_shape = Shape{1, 1, 10};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {0};
std::vector<float> expected_selected_scores = {0.00, 0.90, 0.00, 0.00, 1.00, 1.00};
std::vector<int64_t> expected_valid_outputs = {1};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({1, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({1, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_limit_output_size) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 2;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4};
const auto scores_shape = Shape{1, 1, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0};
std::vector<float> expected_selected_scores =
{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00};
std::vector<int64_t> expected_valid_outputs = {2};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({2, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({2, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_single_box) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0};
std::vector<float> scores_data = {0.9};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 1, 4};
const auto scores_shape = Shape{1, 1, 1};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {0};
std::vector<float> expected_selected_scores = {0.00, 0.90, 0.00, 0.00, 1.00, 1.00};
std::vector<int64_t> expected_valid_outputs = {1};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({1, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({1, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_IOU) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.2f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4};
const auto scores_shape = Shape{1, 1, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0};
std::vector<float> expected_selected_scores =
{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00};
std::vector<int64_t> expected_valid_outputs = {2};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({2, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({2, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_IOU_and_scores) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.95f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4};
const auto scores_shape = Shape{1, 1, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00};
std::vector<int64_t> expected_valid_outputs = {1};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({1, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({1, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_no_output) {
std::vector<float> boxes_data = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};
std::vector<float> scores_data = {0.9, 0.75, 0.6, 0.95, 0.5, 0.3};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 2.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::SCORE;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{1, 6, 4};
const auto scores_shape = Shape{1, 1, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {};
std::vector<float> expected_selected_scores = {};
std::vector<int64_t> expected_valid_outputs = {0};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({0, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({0, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({1}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_background) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = 0;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {0, 3, 6, 9};
std::vector<float> expected_selected_scores = {
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00, // 0
1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00}; // 1
std::vector<int64_t> expected_valid_outputs = {2, 2};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({4, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({4, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_keep_top_k) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = 3;
attrs.iou_threshold = 0.5f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = 3;
attrs.background_class = -1;
attrs.nms_eta = 1.0f;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 0, 9, 6, 6};
std::vector<float> expected_selected_scores = {0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,
0.00, 1.00, 1.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00, // 0
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,
0.00, 1.00, 1.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00}; // 1
std::vector<int64_t> expected_valid_outputs = {3, 3};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({6, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({6, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, multiclass_nms_by_nms_eta) {
std::vector<float> boxes_data = {
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0, // 0
0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1, 0.0, -0.1, 1.0, 0.9,
0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0 // 1
};
std::vector<float> scores_data = {
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3, // 0
0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3 // 1
};
op::v8::MulticlassNms::Attributes attrs;
attrs.nms_top_k = -1;
attrs.iou_threshold = 1.0f;
attrs.score_threshold = 0.0f;
attrs.sort_result_type = op::v8::MulticlassNms::SortResultType::CLASSID;
attrs.keep_top_k = -1;
attrs.background_class = -1;
attrs.nms_eta = 0.1f;
const auto boxes_shape = Shape{2, 6, 4}; // N 2, C 2, M 6
const auto scores_shape = Shape{2, 2, 6};
const auto boxes = make_shared<op::Parameter>(element::f32, boxes_shape);
const auto scores = make_shared<op::Parameter>(element::f32, scores_shape);
auto nms = make_shared<op::v8::MulticlassNms>(boxes, scores, attrs);
auto f = make_shared<Function>(nms, ParameterVector{boxes, scores});
std::vector<int64_t> expected_selected_indices = {3, 0, 5, 0, 3, 5, 9, 6, 11, 6, 9, 11};
std::vector<float> expected_selected_scores = {
0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00, 0.00, 0.30, 0.00,
100.00, 1.00, 101.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
1.00, 0.30, 0.00, 100.00, 1.00, 101.00, 0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,
0.00, 1.00, 1.00, 0.00, 0.30, 0.00, 100.00, 1.00, 101.00, 1.00, 0.95, 0.00, 0.00, 1.00, 1.00,
1.00, 0.80, 0.00, 10.00, 1.00, 11.00, 1.00, 0.30, 0.00, 100.00, 1.00, 101.00};
std::vector<int64_t> expected_valid_outputs = {6, 6};
auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(f);
test_case.add_multiple_inputs<float>({boxes_data, scores_data});
test_case.add_expected_output<float>({12, 6}, expected_selected_scores);
test_case.add_expected_output<int64_t>({12, 1}, expected_selected_indices);
test_case.add_expected_output<int64_t>({2}, expected_valid_outputs);
test_case.run();
}
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