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[LPT] Precision restriction customization extending: tests (#17196)

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* [LPT] Precision restriction customization extending

* comments fix: refactoring

* [LPT] Precision restriction customization extending: tests
This commit is contained in:
Edward Shogulin 2023-04-26 13:53:04 +01:00 committed by GitHub
parent 546581bcce
commit 14a14ecd76
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 84 additions and 30 deletions
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33
src/plugins/intel_cpu/tests/functional/shared_tests_instances/low_precision_transformations/group_convolution_transformation.cpp
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@ -262,4 +262,37 @@ INSTANTIATE_TEST_SUITE_P(smoke_LPT, GroupConvolutionTransformation,
::testing::ValuesIn(addPrecisionPreserved)),
GroupConvolutionTransformation::getTestCaseName);
} // namespace depthwise
namespace i8_3d {
const std::vector<std::pair<ngraph::PartialShape, ngraph::Shape>> inputShapes = {
{{1, 6, 1, 24, 24}, {1, 24, 1, 18, 18}},
{{1, 24, 8, 12, 12}, {1, 24, 1, 1, 1}}
};
const std::vector<LayerTestsDefinitions::GroupConvolutionTransformationParam> params = {
// group convolution, tensor quantization
{
3ul,
-1,
{256ul, ngraph::Shape{1, 1, 1, 1, 1}, {-12.8f}, {12.7f}, {-12.8f}, {12.7f}},
{255ul, ngraph::Shape { 1, 1, 1, 1, 1 }, { 0.f }, { 254.f }, { -127.f }, { 127.f }},
true,
"Convolution",
"I8"
},
};
const std::vector<bool> addPrecisionPreserved = {false};
INSTANTIATE_TEST_SUITE_P(smoke_LPT, GroupConvolutionTransformation,
::testing::Combine(
::testing::ValuesIn(netPrecisions),
::testing::Values(CommonTestUtils::DEVICE_CPU),
::testing::ValuesIn(trasformationParamValues),
::testing::ValuesIn(inputShapes),
::testing::ValuesIn(params),
::testing::ValuesIn(addPrecisionPreserved)),
GroupConvolutionTransformation::getTestCaseName);
} // namespace i8_3d
} // namespace

2
src/tests/ngraph_helpers/lpt_ngraph_functions/src/fake_quantize_and_convolution_function.cpp
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@ -20,7 +20,7 @@ std::shared_ptr<ngraph::Function> FakeQuantizeAndConvolutionFunction::get(
const FakeQuantizeOnData& fqOnData,
const FakeQuantizeOnWeights& fqOnWeights) {
const auto rankLength = inputShape.rank().is_dynamic() ? 4 : inputShape.rank().get_length();
OPENVINO_ASSERT(rankLength == 3ul || rankLength == 4ul, "not supported input shape rank: ", rankLength);
OPENVINO_ASSERT(rankLength == 3ul || rankLength == 4ul || rankLength == 5ul, "not supported input shape rank: ", rankLength);
const auto input = std::make_shared<ngraph::opset1::Parameter>(precision, inputShape);
const auto fakeQuantizeOnActivations = fqOnData.empty() ?

47
src/tests/ngraph_helpers/lpt_ngraph_functions/src/group_convolution_function.cpp
View File

@ -45,6 +45,7 @@ std::shared_ptr<Node> createWeightsOriginal(
weightsValues);
} else {
const size_t inputChannelsPerGroup = inputChannelsCount / groupCount;
if ((rankLength == 3) || (rankLength == 4)) {
weights = ngraph::opset1::Constant::create(
precision,
addReshape ?
@ -61,6 +62,13 @@ std::shared_ptr<Node> createWeightsOriginal(
outputChannelsCount * kernelSize * kernelSize * inputChannelsPerGroup,
weightsValues[0]) :
weightsValues);
} else {
const ngraph::Shape shape{outputChannelsCount, inputChannelsPerGroup, 1ull, kernelSize, kernelSize};
const std::vector<float> values = weightsValues.size() == 1ull ?
std::vector<float>(shape_size(shape), weightsValues[0]) :
weightsValues;
weights = ngraph::opset1::Constant::create(precision, shape, values);
}
if (!fakeQuantizeOnWeights.empty()) {
Shape constantShape;
@ -91,23 +99,36 @@ std::shared_ptr<Node> createWeightsOriginal(
}
if (addReshape) {
std::vector<int64_t> values;
if (rankLength == 3ll) {
values = std::vector<int64_t>{
calculatedDimention == 0 ? -1 : static_cast<int64_t>(groupCount),
calculatedDimention == 1 ? -1 : static_cast<int64_t>(outputChannelsCount / groupCount),
static_cast<int64_t>(inputChannelsPerGroup),
static_cast<int64_t>(kernelSize)};
} else if (rankLength == 4ll) {
values = std::vector<int64_t>{
calculatedDimention == 0 ? -1 : static_cast<int64_t>(groupCount),
calculatedDimention == 1 ? -1 : static_cast<int64_t>(outputChannelsCount / groupCount),
static_cast<int64_t>(inputChannelsPerGroup),
static_cast<int64_t>(kernelSize),
static_cast<int64_t>(kernelSize)};
} else if (rankLength == 5ll) {
values = std::vector<int64_t>{
calculatedDimention == 0 ? -1 : static_cast<int64_t>(groupCount),
calculatedDimention == 1 ? -1 : static_cast<int64_t>(outputChannelsCount / groupCount),
static_cast<int64_t>(inputChannelsPerGroup),
1,
static_cast<int64_t>(kernelSize),
static_cast<int64_t>(kernelSize)};
}
weights = std::make_shared<ngraph::opset1::Reshape>(
weights,
ngraph::opset1::Constant::create(
element::i64,
Shape{ static_cast<size_t>(rankLength) + 1ul },
rankLength == 3 ?
std::vector<int64_t> {
calculatedDimention == 0 ? -1 : static_cast<int64_t>(groupCount),
calculatedDimention == 1 ? -1 : static_cast<int64_t>(outputChannelsCount / groupCount),
static_cast<int64_t>(inputChannelsPerGroup),
static_cast<int64_t>(kernelSize) } :
std::vector<int64_t> {
calculatedDimention == 0 ? -1 : static_cast<int64_t>(groupCount),
calculatedDimention == 1 ? -1 : static_cast<int64_t>(outputChannelsCount / groupCount),
static_cast<int64_t>(inputChannelsPerGroup),
static_cast<int64_t>(kernelSize),
static_cast<int64_t>(kernelSize) }),
values),
true);
}
}
@ -175,7 +196,7 @@ std::shared_ptr<ngraph::Function> GroupConvolutionFunction::getOriginal(
const bool addReshape,
const bool addPrecisionPreserved) {
const auto rankLength = inputShape.rank().is_dynamic() ? 4 : inputShape.rank().get_length();
OPENVINO_ASSERT(rankLength == 3 || rankLength == 4, "not supported input shape rank: ", rankLength);
OPENVINO_ASSERT(rankLength == 3 || rankLength == 4 || rankLength == 5, "not supported input shape rank: ", rankLength);
const auto input = std::make_shared<ngraph::opset1::Parameter>(precision, inputShape);