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Proposal reference implementation (#3924)
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* Reference implementation for Proposal, enable CPU SLT

* code style fix

* add type prop test for invalid anchor count

* add unit test

* fix shapes in attribute test

* temp workaround- disable maring end of boxes list

* Disable CPU smoke test- spec misalignment

* code style fixes

* add some details to the specification

* disable myriadx proposal slt

* review changes, using usigned int and size_t

* improve proposal op shape inference to cover dynamic too, add unit test coverage

* remove unused variable in test body

* remove batch size in tests where its not used

* add post nms topn initialization in tests where it was missing

* review comments

* style fix

* style fix 2

* add tests, remove unused variables, change shape inference checks

* style fix

* add input tensors type checks and test coverage

* align input type in attribute and ngraphreader tests to match specification

* fix wrong dimension in error message

* proposalv4 ref impl

* enable single layer and unit tests for proposalv4 ref impl

* align output termination with cpu, enable cpu slt

* custom slt compares to detect less-than-predicted number of boxes

* custom slt compares to detect less-than-predicted number of boxes

* Clarify output termination in spec

* review comments

* smaller input data for unit tests

* add check for batch_dim being static

* disable gpu slt for proposal

* test data style fix

* test data style fix 2

* add type section to specification

* shape inference improvement

* multiply expected 1st dim in tests by post_nms_topn

* add checks and testcases for dynamic ranks

* indentation, review comments

* reduce code redundancy in ref implementation

* remove comment

* Fix typo in proposal1 spec

* Fix typo in proposal4 spec
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Bartosz Lesniewski authored Feb 8, 2021
1 parent 56b6e10 commit 210ad81
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19 changes: 12 additions & 7 deletions docs/ops/detection/Proposal_1.md
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Expand Up @@ -8,7 +8,7 @@

**Detailed description**

*Proposal* has three inputs: a tensor with probabilities whether particular bounding box corresponds to background and foreground, a tensor with bbox_deltas for each of the bounding boxes, a tensor with input image size in the [`image_height`, `image_width`, `scale_height_and_width`] or [`image_height`, `image_width`, `scale_height`, `scale_width`] format. The produced tensor has two dimensions `[batch_size * post_nms_topn, 5]`.
*Proposal* has three inputs: a tensor with probabilities whether particular bounding box corresponds to background and foreground, a tensor with bbox_deltas for each of the bounding boxes, a tensor with input image size in the [`image_height`, `image_width`, `scale_height_and_width`] or [`image_height`, `image_width`, `scale_height`, `scale_width`] format. The produced tensor has two dimensions `[batch_size * post_nms_topn, 5]`, and for each output box contains batch index and box coordinates.
*Proposal* layer does the following with the input tensor:
1. Generates initial anchor boxes. Left top corner of all boxes is at (0, 0). Width and height of boxes are calculated from *base_size* with *scale* and *ratio* attributes.
2. For each point in the first input tensor:
Expand All @@ -19,8 +19,9 @@
5. Takes top *pre_nms_topn* proposals
6. Calculates intersections for boxes and filter out all boxes with \f$intersection/union > nms\_thresh\f$
7. Takes top *post_nms_topn* proposals
8. Returns top proposals
8. Returns top proposals, if there is not enough proposals to fill the whole output tensor, the valid proposals will be terminated with a single -1.

**Attributes**:

* *base_size*

Expand Down Expand Up @@ -136,15 +137,19 @@

**Inputs**:

* **1**: 4D input floating point tensor with class prediction scores. Required.
* **1**: 4D tensor of type *T* and shape `[batch_size, 2*K, H, W]` with class prediction scores. Required.

* **2**: 4D input floating point tensor with box bbox_deltas. Required.
* **2**: 4D tensor of type *T* and shape `[batch_size, 4*K, H, W]` with deltas for each bounding box. Required.

* **3**: 1D input floating tensor 3 or 4 elements: [`image_height`, `image_width`, `scale_height_and_width`] or [`image_height`, `image_width`, `scale_height`, `scale_width`]. Required.
* **3**: 1D tensor of type *T* with 3 or 4 elements: `[image_height, image_width, scale_height_and_width]` or `[image_height, image_width, scale_height, scale_width]`. Required.

**Outputs**:

* **1**: Floating point tensor of shape `[batch_size * post_nms_topn, 5]`.
* **1**: Tensor of type *T* and shape `[batch_size * post_nms_topn, 5]`.

**Types**

* *T*: floating point type.

**Example**

Expand All @@ -155,4 +160,4 @@
<input> ... </input>
<output> ... </output>
</layer>
```
```
5 changes: 4 additions & 1 deletion docs/ops/detection/Proposal_4.md
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Expand Up @@ -26,8 +26,11 @@ the second optional tensor of shape `[batch_size * post_nms_topn]` with probabil
5. Takes top *pre_nms_topn* proposals
6. Calculates intersections for boxes and filter out all boxes with \f$intersection/union > nms\_thresh\f$
7. Takes top *post_nms_topn* proposals
8. Returns top proposals and optionally their probabilities
8. Returns the results:
* Top proposals, if there is not enough proposals to fill the whole output tensor, the valid proposals will be terminated with a single -1.
* Optionally returns probabilities for each proposal, which are not terminated by any special value.

**Attributes**:

* *base_size*

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Expand Up @@ -32,9 +32,9 @@ TEST_F(NGraphReaderTests, ReadProposalNetwork) {
</output>
</layer>
<layer id="2" name="in3" type="Const" version="opset1">
<data element_type="i64" offset="0" shape="3" size="24"/>
<data element_type="f32" offset="0" shape="3" size="24"/>
<output>
<port id="0" precision="I64">
<port id="0" precision="FP32">
<dim>3</dim>
</port>
</output>
Expand Down Expand Up @@ -85,7 +85,7 @@ TEST_F(NGraphReaderTests, ReadProposalNetwork) {
std::string model_v6 = R"V0G0N(
<net name="Network" version="6" batch="1">
<layers>
<layer name="in3" type="Const" precision="I64" id="4">
<layer name="in3" type="Const" precision="FP32" id="4">
<output>
<port id="2">
<dim>1</dim>
Expand Down Expand Up @@ -183,9 +183,9 @@ TEST_F(NGraphReaderTests, ReadProposalNetwork_2) {
</output>
</layer>
<layer id="2" name="in3" type="Const" version="opset1">
<data element_type="i64" offset="0" shape="4" size="32"/>
<data element_type="f32" offset="0" shape="4" size="32"/>
<output>
<port id="0" precision="I64">
<port id="0" precision="FP32">
<dim>4</dim>
</port>
</output>
Expand Down Expand Up @@ -236,7 +236,7 @@ TEST_F(NGraphReaderTests, ReadProposalNetwork_2) {
std::string model_v6 = R"V0G0N(
<net name="Network" version="6" batch="1">
<layers>
<layer name="in3" type="Const" precision="I64" id="4">
<layer name="in3" type="Const" precision="FP32" id="4">
<output>
<port id="2">
<dim>1</dim>
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Expand Up @@ -45,5 +45,4 @@ INSTANTIATE_TEST_CASE_P(smoke_Proposal_tests, ProposalLayerTest,
::testing::Values(CommonTestUtils::DEVICE_CPU)),
ProposalLayerTest::getTestCaseName
);

} // namespace
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Expand Up @@ -51,6 +51,8 @@ std::vector<std::string> disabledTestPatterns() {
R"(.*(LSTMSequence).*mode=CONVERT_TO_TI_RAND_SEQ_LEN.*)",
R"(.*(smoke_DetectionOutput3In).*)",
R"(.*(smoke_DetectionOutput5In).*)",
// TODO: Issue: 47773
R"(.*(ProposalLayerTest).*)",

// INT8 StridedSlice not supported
R"(.*(LPT/StridedSliceTransformation).*)",
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Expand Up @@ -31,6 +31,8 @@ std::vector<std::string> disabledTestPatterns() {
R"(.*(DSR_GatherND).*)",
// TODO: Issue 26090
".*DSR_GatherStaticDataDynamicIdx.*f32.*1.3.200.304.*",
// TODO: Issue 47315
".*ProposalLayerTest.*",
// TODO: Issue 46755
".*DSR_GatherElements.*"
};
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Expand Up @@ -58,10 +58,44 @@ class ProposalLayerTest
static std::string getTestCaseName(testing::TestParamInfo<proposalLayerTestParamsSet> obj);
static std::string SerializeProposalSpecificParams(proposalSpecificParams& params);
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo &info) const override;
void Compare(const std::vector<std::vector<std::uint8_t>> &expectedOutputs, const std::vector<InferenceEngine::Blob::Ptr> &actualOutputs) override;
template <class T>
void Compare(const T *expected, const T *actual, std::size_t size,
T threshold, const std::size_t output_index) {
for (std::size_t i = 0; i < size; ++i) {
const auto &ref = expected[i];
const auto &res = actual[i];

// verify until first -1 appears in the 1st output.
if (output_index == 0 &&
CommonTestUtils::ie_abs(ref - static_cast<T>(-1)) <= threshold) {
// output0 shape = {x, 5}
// output1 shape = {x}
// setting the new_size for output1 verification
num_selected_boxes = i / 5;
return;
}

const auto absoluteDifference = CommonTestUtils::ie_abs(res - ref);
if (absoluteDifference <= threshold) {
continue;
}

const auto max = std::max(CommonTestUtils::ie_abs(res),
CommonTestUtils::ie_abs(ref));
float diff =
static_cast<float>(absoluteDifference) / static_cast<float>(max);
ASSERT_TRUE(max != 0 && (diff <= static_cast<float>(threshold)))
<< "Relative comparison of values expected: " << ref
<< " and actual: " << res << " at index " << i
<< " with threshold " << threshold << " failed";
}
}
protected:
void SetUp() override;
void Validate() override;

private:
size_t num_selected_boxes;
};

} // namespace LayerTestsDefinitions
Original file line number Diff line number Diff line change
Expand Up @@ -63,6 +63,54 @@ std::string ProposalLayerTest::getTestCaseName(testing::TestParamInfo<proposalLa
return proposalPramString + result.str();
}

void ProposalLayerTest::Compare(
const std::vector<std::vector<std::uint8_t>> &expectedOutputs,
const std::vector<InferenceEngine::Blob::Ptr> &actualOutputs) {
num_selected_boxes = 0;
for (std::size_t outputIndex = 0; outputIndex < expectedOutputs.size(); ++outputIndex) {
const auto &expected = expectedOutputs[outputIndex];
const auto &actual = actualOutputs[outputIndex];
ASSERT_EQ(expected.size(), actual->byteSize());
const auto &expectedBuffer = expected.data();

auto memory = InferenceEngine::as<InferenceEngine::MemoryBlob>(actual);
IE_ASSERT(memory);
const auto lockedMemory = memory->rmap();
const auto actualBuffer = lockedMemory.as<const std::uint8_t *>();

const auto &precision = actual->getTensorDesc().getPrecision();
auto size = actual->size();

// verifying the first output if there was less proposals than space
// provided,
// num_selected_boxes was set, take this into consideration while verifying the 2nd
// output
if (outputIndex == 1 && num_selected_boxes) {
size = num_selected_boxes;
}

switch (precision) {
case InferenceEngine::Precision::BF16:
Compare(reinterpret_cast<const ngraph::bfloat16 *>(expectedBuffer),
reinterpret_cast<const ngraph::bfloat16 *>(actualBuffer), size,
ngraph::bfloat16(threshold), outputIndex);
break;
case InferenceEngine::Precision::FP16:
Compare(reinterpret_cast<const ngraph::float16 *>(expectedBuffer),
reinterpret_cast<const ngraph::float16 *>(actualBuffer), size,
ngraph::float16(threshold), outputIndex);
break;
case InferenceEngine::Precision::FP32:
Compare<float>(reinterpret_cast<const float *>(expectedBuffer),
reinterpret_cast<const float *>(actualBuffer), size,
threshold, outputIndex);
break;
default:
FAIL() << "Comparator for " << precision << " precision isn't supported";
}
}
}

void ProposalLayerTest::SetUp() {
proposalSpecificParams proposalParams;
std::vector<float> img_info = {225.0f, 225.0f, 1.0f};
Expand Down Expand Up @@ -98,10 +146,11 @@ void ProposalLayerTest::SetUp() {
std::vector<size_t> imageInfoShape = {3};

auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(InferenceEngine::Precision::FP16);
auto params = ngraph::builder::makeParams(ngPrc, {{"scores", scoresShape}, {"boxes", boxesShape}});
// a_ and b_ are a workaround to solve alphabetic param sorting that destroys ordering
auto params = ngraph::builder::makeParams(ngPrc, {{"a_scores", scoresShape}, {"b_boxes", boxesShape}});
auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ngraph::op::Parameter>(params));

auto proposal = std::dynamic_pointer_cast<ngraph::opset1::Proposal>(
auto proposal = std::dynamic_pointer_cast<ngraph::opset4::Proposal>(
ngraph::builder::makeProposal(paramOuts[0], paramOuts[1], img_info, ngPrc,
base_size,
pre_nms_topn,
Expand All @@ -118,23 +167,22 @@ void ProposalLayerTest::SetUp() {
box_coordinate_scale,
framework));

ngraph::ResultVector results{std::make_shared<ngraph::opset1::Result>(proposal)};
ngraph::ResultVector results{
std::make_shared<ngraph::opset1::Result>(proposal->output(0)),
std::make_shared<ngraph::opset1::Result>(proposal->output(1))};
function = std::make_shared<ngraph::Function>(results, params, "proposal");
}

InferenceEngine::Blob::Ptr ProposalLayerTest::GenerateInput(const InferenceEngine::InputInfo &info) const {
InferenceEngine::Blob::Ptr blobPtr;

const std::string name = info.name();
if (name == "scores") {
if (name == "a_scores") {
blobPtr = FuncTestUtils::createAndFillBlobFloat(info.getTensorDesc(), 1, 0, 1000, 8234231);
} else if (name == "boxes") {
} else if (name == "b_boxes") {
blobPtr = FuncTestUtils::createAndFillBlobFloatNormalDistribution(info.getTensorDesc(), 0.0f, 0.2f, 7235346);
}

return blobPtr;
}

// TODO: for validation, reference version is required (#28373)
void ProposalLayerTest::Validate() {}
} // namespace LayerTestsDefinitions
Original file line number Diff line number Diff line change
Expand Up @@ -44,10 +44,11 @@ std::shared_ptr<Node> makeProposal(const ngraph::Output<Node> &class_probs,
attrs.box_size_scale = box_size_scale;
attrs.box_coordinate_scale = box_coordinate_scale;
attrs.framework = framework;
attrs.infer_probs = true;

auto image_shape = makeConstant(ngraph::element::Type_t::f32, {3}, image_info);

return std::make_shared<opset1::Proposal>(class_probs, class_logits, image_shape, attrs);
return std::make_shared<opset4::Proposal>(class_probs, class_logits, image_shape, attrs);
}

} // namespace builder
Expand Down
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