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NMS-5 calculate upper-bound (#17332)

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* NMS-5 calculate upper-bound

* Test
This commit is contained in:
Evgenya Stepyreva
2023-05-03 15:22:08 +04:00
committed by GitHub
parent 1141e90435
commit bf829eead4
3 changed files with 27 additions and 9 deletions
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13
src/core/src/op/non_max_suppression.cpp
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@@ -805,15 +805,12 @@ void op::v5::NonMaxSuppression::validate_and_infer_types() {
validate();
if (boxes_ps.rank().is_static() && scores_ps.rank().is_static() && get_input_size() > 2) {
const auto num_boxes_boxes = boxes_ps[1];
if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static() &&
has_and_set_equal_bounds(input_value(2))) {
const auto num_boxes = num_boxes_boxes.get_length();
const auto num_classes = scores_ps[1].get_length();
const auto num_boxes = boxes_ps[1].get_max_length();
const auto num_classes = scores_ps[1].get_max_length();
const auto batch = scores_ps[0].get_max_length();
if (num_boxes != -1 && batch != -1 && num_classes != -1 && has_and_set_equal_bounds(input_value(2))) {
const auto max_output_boxes_per_class = max_boxes_output_from_input();
out_shape[0] =
Dimension(0, std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0].get_length());
out_shape[0] = Dimension(0, std::min(num_boxes, max_output_boxes_per_class) * num_classes * batch);
}
}

21
src/core/tests/type_prop/non_max_suppression.cpp
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@@ -595,6 +595,27 @@ TEST(type_prop, nms_v5_output_shape_3) {
EXPECT_EQ(nms->get_output_shape(2), (Shape{1}));
}
TEST(type_prop, nms_v5_output_shape_4) {
const auto boxes = make_shared<op::Parameter>(element::f32, PartialShape{{0, 2}, {0, 7}, 4});
const auto scores = make_shared<op::Parameter>(element::f32, PartialShape{{0, 2}, {0, 5}, {0, 7}});
const auto max_output_boxes_per_class = op::Constant::create(element::i16, Shape{}, {1000});
const auto iou_threshold = make_shared<op::Parameter>(element::f32, Shape{});
const auto score_threshold = make_shared<op::Parameter>(element::f32, Shape{});
const auto nms = make_shared<op::v5::NonMaxSuppression>(boxes,
scores,
max_output_boxes_per_class,
iou_threshold,
score_threshold);
ASSERT_EQ(nms->get_output_element_type(0), element::i64);
ASSERT_EQ(nms->get_output_element_type(1), element::f32);
ASSERT_EQ(nms->get_output_element_type(2), element::i64);
EXPECT_EQ(nms->get_output_partial_shape(0), PartialShape({Dimension(0, 70), Dimension(3)}));
EXPECT_EQ(nms->get_output_partial_shape(1), PartialShape({Dimension(0, 70), Dimension(3)}));
EXPECT_EQ(nms->get_output_shape(2), (Shape{1}));
}
TEST(type_prop, nms_v5_output_shape_i32) {
const auto boxes = make_shared<op::Parameter>(element::f32, Shape{2, 7, 4});
const auto scores = make_shared<op::Parameter>(element::f32, Shape{2, 5, 7});

2
src/inference/src/cnn_network_ngraph_impl.cpp
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@@ -423,7 +423,7 @@ void collect_dynamism_signature(const std::shared_ptr<ov::Model>& ov_model,
std::map<std::string, std::map<std::string, size_t>>& signatures,
bool obfuscate) {
for (const auto& op : ov_model->get_ordered_ops()) {
const auto& type_name = string(op->get_type_info().name) + "_" + to_string(op->get_type_info().version);
const auto& type_name = string(op->get_type_info().name) + "_" + op->get_type_info().version_id;
std::stringstream shape_representation;
for (const auto& input : op->input_values()) {