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refactoring
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@ndemashov
ndemashov committed Apr 4, 2022
1 parent 26765ac commit 90e33cf
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Showing 10 changed files with 25 additions and 72 deletions.
3 changes: 0 additions & 3 deletions src/common/low_precision_transformations/include/low_precision/network_helper.hpp
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Expand Up @@ -253,9 +253,6 @@ class LP_TRANSFORMATIONS_API NetworkHelper {
float& updatedOutputLowValue,
float& updatedOutputHighValue);

static std::shared_ptr<ov::Node> fakeQuantizeWraper
(const std::shared_ptr<ov::Node> parameter);

private:
static std::shared_ptr<Node> foldFakeQuantize(
const std::shared_ptr<opset1::FakeQuantize>& fq,
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1 change: 1 addition & 0 deletions src/common/low_precision_transformations/include/low_precision/recurrent_cell.hpp
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Expand Up @@ -20,6 +20,7 @@ class LP_TRANSFORMATIONS_API RecurrentCellTransformation : public LayerTransform
bool canBeTransformed(const TransformationContext& context, std::shared_ptr<Node> layer) const override;
bool isPrecisionPreserved(std::shared_ptr<Node> layer) const noexcept override;
void propagateSkipCleanupAttribute(std::shared_ptr<Node> dequantization_multiply);
static std::shared_ptr<ov::Node> wrap_fake_quantize(const std::shared_ptr<ov::Node> parameter);
};

} // namespace low_precision
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8 changes: 0 additions & 8 deletions ...on/low_precision_transformations/include/low_precision/rt_info/skip_cleanup_attribute.hpp
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Expand Up @@ -4,16 +4,8 @@

#pragma once

#include <memory>
#include <set>
#include <unordered_set>
#include <vector>

#include <ngraph/node.hpp>
#include <ngraph/pass/graph_rewrite.hpp>
#include <ngraph/variant.hpp>

#include "low_precision/lpt_visibility.hpp"
#include "low_precision/rt_info/attribute_parameters.hpp"

namespace ngraph {
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15 changes: 0 additions & 15 deletions src/common/low_precision_transformations/src/network_helper.cpp
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Expand Up @@ -1982,21 +1982,6 @@ void NetworkHelper::insertDequantizationAfter(
}
}
}

std::shared_ptr<ov::Node> NetworkHelper::fakeQuantizeWraper(
const std::shared_ptr<ov::Node> parameter) {
const auto input_low = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto input_high = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto output_low = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto output_high = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
return ngraph::pattern::wrap_type<opset1::FakeQuantize>({
parameter,
input_low,
input_high,
output_low,
output_high});
}

} // namespace low_precision
} // namespace pass
} // namespace ngraph
22 changes: 18 additions & 4 deletions src/common/low_precision_transformations/src/recurrent_cell.cpp
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Expand Up @@ -28,10 +28,10 @@ RecurrentCellTransformation::RecurrentCellTransformation(const Params& params) :
const auto R = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto B = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();

const auto fq_X = NetworkHelper::fakeQuantizeWraper(X);
const auto fq_H = NetworkHelper::fakeQuantizeWraper(H);
const auto fq_W = NetworkHelper::fakeQuantizeWraper(W);
const auto fq_R = NetworkHelper::fakeQuantizeWraper(R);
const auto fq_X = wrap_fake_quantize(X);
const auto fq_H = wrap_fake_quantize(H);
const auto fq_W = wrap_fake_quantize(W);
const auto fq_R = wrap_fake_quantize(R);

const auto dequantization_convert_X = ngraph::pattern::wrap_type<ngraph::opset1::Convert>({ngraph::pattern::any_input()});
const auto dequantization_convert_H = ngraph::pattern::wrap_type<ngraph::opset1::Convert>({ngraph::pattern::any_input()});
Expand Down Expand Up @@ -160,6 +160,20 @@ void RecurrentCellTransformation::propagateSkipCleanupAttribute(std::shared_ptr<
}
}

std::shared_ptr<ov::Node> RecurrentCellTransformation::wrap_fake_quantize(
const std::shared_ptr<ov::Node> parameter) {
const auto input_low = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto input_high = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto output_low = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
const auto output_high = ngraph::pattern::wrap_type<ngraph::opset1::Constant>();
return ngraph::pattern::wrap_type<opset1::FakeQuantize>({
parameter,
input_low,
input_high,
output_low,
output_high});
}

} // namespace low_precision
} // namespace pass
} // namespace ngraph
7 changes: 0 additions & 7 deletions src/plugins/intel_cpu/src/nodes/tensoriterator.h
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Expand Up @@ -108,13 +108,6 @@ class TensorIterator : public Node {

void setExtManager(const ExtensionManager::Ptr& extMgr) { ext_mng = extMgr; }

Graph getSubGraph() const {
return sub_graph;
}
std::shared_ptr<ov::Node> getOriginalOp() const {
return ngraphOp;
}

protected:
// needShapeInfer() should return false
// because we cannot resolve the output dimensions before the inference is completed
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26 changes: 3 additions & 23 deletions src/tests/functional/inference_engine/lp_transformations/recurrent_cell_transformation.cpp
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Expand Up @@ -4,7 +4,6 @@

#include <gtest/gtest.h>

#include <low_precision/common/operation_per_tensor_quantization_restriction.hpp>
#include <low_precision/common/operation_precision_restriction.hpp>
#include <low_precision/recurrent_cell.hpp>
#include <low_precision/fold_convert.hpp>
Expand Down Expand Up @@ -69,18 +68,12 @@ class RecurrentCellTransformationTestValues {
: params(params),
type(type),
actual(actual),
result(result),
addNotPrecisionPreservedOperation(addNotPrecisionPreservedOperation),
checkIntervalsAlignmentAttributes(checkIntervalsAlignmentAttributes) {}
result(result) {}

TestTransformationParams params;
RecurrentCellFunction::RNNType type;
RecurrentCellTransformationValues actual;
RecurrentCellTransformationValues result;
// add not precision preserved operation to set output precision for FakeQuantize
// don't set to 'true' by default to keep test cases with tested operation as output
bool addNotPrecisionPreservedOperation;
bool checkIntervalsAlignmentAttributes;
};

inline std::ostream& operator<<(std::ostream& out, const RecurrentCellTransformationTestValues& values) {
Expand Down Expand Up @@ -119,10 +112,7 @@ class RecurrentCellTransformation : public LayerTransformation, public testing::
testValues.actual.dequantization_H,
testValues.actual.dequantization_W,
testValues.actual.dequantization_R
},
{},
ngraph::element::undefined,
{});
});

const auto params = TestTransformationParams::toParams(testValues.params);

Expand All @@ -143,13 +133,6 @@ class RecurrentCellTransformation : public LayerTransformation, public testing::
testValues.result.dequantizationAfter.multiply.outPrecision = precision;
}

if (!testValues.params.updatePrecisions && (precision == ngraph::element::f32) &&
!testValues.result.dequantizationAfter.convert.empty()) {
testValues.result.dequantizationAfter.convert = {};
}

IntervalsAlignmentSharedValue::Interval interval{-1.28f, 2.55f};

referenceFunction =
ngraph::builder::subgraph::RecurrentCellFunction::get(precision,
activations_shapes,
Expand All @@ -172,10 +155,7 @@ class RecurrentCellTransformation : public LayerTransformation, public testing::
testValues.result.dequantization_H,
testValues.result.dequantization_W,
testValues.result.dequantization_R
},
{},
testValues.result.precisionAfterOperation,
testValues.result.dequantizationAfter);
});
}

static std::string getTestCaseName(testing::TestParamInfo<RecurrentCellTransformationParams> obj) {
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5 changes: 1 addition & 4 deletions ...ctional/plugin/shared/src/low_precision_transformations/recurrent_cell_transformation.cpp
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Expand Up @@ -66,10 +66,7 @@ void RecurrentCellTransformation::SetUp() {
param.dequantization_H,
param.dequantization_W,
param.dequantization_R
},
{},
ngraph::element::undefined,
{});
});
}

void RecurrentCellTransformation::Run() {
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5 changes: 1 addition & 4 deletions ...aph_helpers/lpt_ngraph_functions/include/lpt_ngraph_functions/recurrent_cell_function.hpp
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Expand Up @@ -26,10 +26,7 @@ class RecurrentCellFunction {
const RNNType type,
const std::vector<FakeQuantizeOnDataWithConstant>& fqOnDatas,
const std::vector<DequantizationOperations::Convert>& converts,
const std::vector<DequantizationOperations>& dequantizations,
const std::vector<ov::Any>& concatAttributes,
const ngraph::element::Type precisionAfterOperation,
const DequantizationOperations& dequantizationAfter);
const std::vector<DequantizationOperations>& dequantizations);
};

std::shared_ptr<Node> makeQuantizationAndDequantization(const std::shared_ptr<Node> input,
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5 changes: 1 addition & 4 deletions src/tests/ngraph_helpers/lpt_ngraph_functions/src/recurrent_cell_function.cpp
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Expand Up @@ -30,10 +30,7 @@ std::shared_ptr<ngraph::Function> RecurrentCellFunction::get(
const RNNType type,
const std::vector<FakeQuantizeOnDataWithConstant>& fqOnDatas,
const std::vector<DequantizationOperations::Convert>& converts,
const std::vector<DequantizationOperations>& dequantizations,
const std::vector<ov::Any>& concatAttributes,
const ngraph::element::Type precisionAfterOperation,
const DequantizationOperations& dequantizationAfter) {
const std::vector<DequantizationOperations>& dequantizations) {
auto X = std::make_shared<opset5::Parameter>(inputPrecision, inputActivationsShapes[0]);
X->set_friendly_name("X");
std::shared_ptr<Node> parent_X = makeQuantizationAndDequantization(X,
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