Migrate ngraph backend test/convolution backprop (#7997)
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now * update repo * add draft reference of binary convolution * build test * fix build error * add binary_convolution reference test and ngraph visitor api test * remove ngraph backend test of binary_convolution * add reference test and remove ngraph backend test of convolution_backprop * add f64 case for convolution_backprop
This commit is contained in:
Wilson Seok
GitHub
parent
a9688bac54
commit
34fce43ab0
@ -0,0 +1,316 @@
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// Copyright (C) 2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <gtest/gtest.h>
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#include <ngraph_functions/builders.hpp>
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#include "openvino/op/binary_convolution.hpp"
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#include "base_reference_test.hpp"
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#include "openvino/opsets/opset8.hpp"
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using namespace reference_tests;
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using namespace ov;
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namespace {
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struct BinaryConvolutionParams {
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template <class T>
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BinaryConvolutionParams(const PartialShape& inputShape,
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const Shape& filterShape,
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const PartialShape& outputShape,
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const element::Type& iType,
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const std::vector<T>& iValues,
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const std::vector<uint8_t>& filterValues,
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const std::vector<T>& oValues,
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const Strides& strides,
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const CoordinateDiff& padBegin,
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const CoordinateDiff& padEnd,
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const Strides& dialations,
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const float padValue = 0,
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const std::string& test_name = "")
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: inputShape(inputShape),
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filterShape(filterShape),
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outputShape(outputShape),
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inType(iType),
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outType(iType),
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inputData(CreateTensor(iType, iValues)),
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filterData(filterValues),
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refData(CreateTensor(iType, oValues)),
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strides(strides),
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padBegin(padBegin),
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padEnd(padEnd),
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dialations(dialations),
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padValue(padValue) {}
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PartialShape inputShape;
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Shape filterShape;
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PartialShape outputShape;
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ov::element::Type inType;
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ov::element::Type outType;
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ov::runtime::Tensor inputData;
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std::vector<uint8_t> filterData;
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ov::runtime::Tensor refData;
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ov::Strides strides;
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ov::CoordinateDiff padBegin;
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ov::CoordinateDiff padEnd;
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ov::Strides dialations;
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ov::op::v1::BinaryConvolution::BinaryConvolutionMode mode = ov::op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT;
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float padValue;
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std::string testcaseName;
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};
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class ReferenceBinaryConvolutionLayerTest : public testing::TestWithParam<BinaryConvolutionParams>, public CommonReferenceTest {
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public:
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void SetUp() override {
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auto params = GetParam();
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function = CreateFunction(params, params.filterData);
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inputData = {params.inputData};
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refOutData = {params.refData};
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}
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static std::string getTestCaseName(const testing::TestParamInfo<BinaryConvolutionParams>& obj) {
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auto param = obj.param;
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std::ostringstream result;
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result << "inputShape=" << param.inputShape << "_";
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result << "filterShape=" << param.filterShape << "_";
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result << "outputShape=" << param.outputShape << "_";
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result << "iType=" << param.inType << "_";
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result << "oType=" << param.outType << "_";
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result << "strides=" << param.strides << "_";
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result << "padBegin=" << param.padBegin << "_";
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result << "padEnd=" << param.padEnd << "_";
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result << "dialations=" << param.dialations << "_";
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if (param.testcaseName != "") {
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result << "padValue=" << param.padValue << "_";
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result << param.testcaseName;
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} else {
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result << "padValue=" << param.padValue;
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}
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return result.str();
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}
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private:
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static std::shared_ptr<Function> CreateFunction(const BinaryConvolutionParams& params, const std::vector<uint8_t>& filterData) {
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const op::PadType auto_pad{op::PadType::EXPLICIT};
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const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
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auto filter = std::make_shared<opset8::Constant>(ov::element::u1, params.filterShape, &filterData[0]);
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const auto BinaryConvolution = std::make_shared<op::v1::BinaryConvolution>(in,
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filter,
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params.strides,
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params.padBegin,
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params.padEnd,
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params.dialations,
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params.mode,
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params.padValue,
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auto_pad);
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return std::make_shared<ov::Function>(NodeVector {BinaryConvolution}, ParameterVector {in});
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}
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};
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TEST_P(ReferenceBinaryConvolutionLayerTest, CompareWithRefs) {
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Exec();
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}
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template <element::Type_t IN_ET>
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std::vector<BinaryConvolutionParams> generateBinaryConvolutionParams() {
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using T = typename element_type_traits<IN_ET>::value_type;
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std::vector<BinaryConvolutionParams> binaryConvolutionParams {
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// --------------------- 2D BinaryConvolution ------------------------------------------
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BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 2, 2},
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IN_ET,
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std::vector<T>{1, 0, 0, 1,
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1, 1, 0, 0,
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0, 0, 0, 1,
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1, 0, 1, 1},
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std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
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std::vector<T>{1, 1,
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3, -1},
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{1, 1},
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{0, 0},
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{0, 0},
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{1, 1}),
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BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 4, 4},
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IN_ET,
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std::vector<T>{1, 0, 0, 1,
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1, 1, 0, 0,
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0, 0, 0, 1,
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1, 0, 1, 1},
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std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
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std::vector<T>{1, -3, -1, 1,
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-3, 1, 1, -5,
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-3, 3, -1, 1,
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1, -5, 1, -3},
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{1, 1},
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{1, 1},
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{1, 1},
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{1, 1}),
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BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 4, 4},
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IN_ET,
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std::vector<T>{1, 0, 0, 1,
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1, 1, 0, 0,
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0, 0, 0, 1,
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1, 0, 1, 1},
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std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
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std::vector<T>{3, -1, 1, 3,
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-1, 1, 1, -3,
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-1, 3, -1, 3,
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3, -3, 3, -1},
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{1, 1},
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{1, 1},
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{1, 1},
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{1, 1},
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1.0f),
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BinaryConvolutionParams(PartialShape {1, 1, 5, 5},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 2, 2},
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IN_ET,
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std::vector<T>{0, 1, 1, 0, 1,
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1, 1, 0, 1, 0,
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0, 0, 1, 0, 1,
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1, 1, 0, 1, 0,
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0, 0, 1, 1, 1},
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std::vector<uint8_t>{0x2E, 0x00}, // 10101010 10000000
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std::vector<T>{-1, 3,
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1, 1},
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{2, 2},
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{0, 0},
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{0, 0},
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{1, 1}),
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BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 3, 3},
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IN_ET,
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std::vector<T>{1, 1, 0, 0, 0, 1, 0,
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0, 0, 1, 0, 1, 0, 0,
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1, 1, 1, 1, 0, 1, 1,
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0, 0, 0, 1, 1, 1, 0,
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0, 1, 0, 0, 1, 1, 1,
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1, 0, 1, 1, 0, 0, 0,
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1, 1, 1, 0, 1, 0, 0},
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std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
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std::vector<T>{-5, -3, -5,
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5, 1, 3,
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-1, -1, 3},
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{1, 1},
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{0, 0},
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{0, 0},
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{2, 2}),
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BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 4, 4},
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IN_ET,
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std::vector<T>{1, 1, 0, 0, 0, 1, 0,
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0, 0, 1, 0, 1, 0, 0,
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1, 1, 1, 1, 0, 1, 1,
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0, 0, 0, 1, 1, 1, 0,
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0, 1, 0, 0, 1, 1, 1,
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1, 0, 1, 1, 0, 0, 0,
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1, 1, 1, 0, 1, 0, 0},
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std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
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std::vector<T>{1, 1, -1, 1,
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1, -5, -5, 5,
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3, -1, 3, 3,
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-1, -1, 3, -3},
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{2, 2},
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{2, 2},
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{2, 2},
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{2, 2}),
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BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
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Shape {1, 1, 3, 3},
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PartialShape {1, 1, 4, 4},
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IN_ET,
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std::vector<T>{1, 1, 0, 0, 0, 1, 0,
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0, 0, 1, 0, 1, 0, 0,
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1, 1, 1, 1, 0, 1, 1,
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0, 0, 0, 1, 1, 1, 0,
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0, 1, 0, 0, 1, 1, 1,
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1, 0, 1, 1, 0, 0, 0,
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1, 1, 1, 0, 1, 0, 0},
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std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
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std::vector<T>{3, 3, 1, -1,
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-1, -5, -5, 3,
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1, -1, 3, 1,
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-3, 1, 5, -1},
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{2, 2},
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{2, 2},
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{2, 2},
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{2, 2},
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1.0f),
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BinaryConvolutionParams(PartialShape {1, 2, 4, 4},
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Shape {1, 2, 3, 3},
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PartialShape {1, 1, 2, 2},
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IN_ET,
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std::vector<T>{
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// channel 1
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1, 0, 0, 1,
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1, 1, 0, 0,
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0, 0, 0, 1,
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1, 0, 1, 1,
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// channel 2
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0, 1, 1, 0,
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0, 0, 1, 1,
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1, 1, 1, 0,
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0, 1, 0, 0},
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std::vector<uint8_t>{0xAA, 0xAA, 0x80}, // 10101010 10000000
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std::vector<T>{2, 2,
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6, -2},
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{1, 1},
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{0, 0},
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{0, 0},
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{1, 1}),
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BinaryConvolutionParams(PartialShape {2, 1, 4, 4},
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Shape {1, 1, 3, 3},
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PartialShape {2, 1, 2, 2},
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IN_ET,
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std::vector<T>{
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// batch 1
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1, 0, 0, 1,
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1, 1, 0, 0,
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0, 0, 0, 1,
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1, 0, 1, 1,
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// batch 2
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0, 0, 0, 0,
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1, 1, 1, 0,
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1, 1, 0, 1,
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1, 0, 1, 0},
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std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
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std::vector<T>{
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// batch 1
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1, 1,
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3, -1,
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// batch 2
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-3, 3,
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5, -7},
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{1, 1},
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{0, 0},
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{0, 0},
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{1, 1})
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};
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return binaryConvolutionParams;
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}
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std::vector<BinaryConvolutionParams> generateBinaryConvolutionCombinedParams() {
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const std::vector<std::vector<BinaryConvolutionParams>> binaryConvolutionTypeParams {
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generateBinaryConvolutionParams<element::Type_t::f32>(),
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generateBinaryConvolutionParams<element::Type_t::f16>(),
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generateBinaryConvolutionParams<element::Type_t::i64>(),
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generateBinaryConvolutionParams<element::Type_t::i32>()
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};
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std::vector<BinaryConvolutionParams> combinedParams;
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for (const auto& params : binaryConvolutionTypeParams) {
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combinedParams.insert(combinedParams.end(), params.begin(), params.end());
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}
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return combinedParams;
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}
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INSTANTIATE_TEST_SUITE_P(smoke_BinaryConvolution_With_Hardcoded_Refs, ReferenceBinaryConvolutionLayerTest,
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testing::ValuesIn(generateBinaryConvolutionCombinedParams()), ReferenceBinaryConvolutionLayerTest::getTestCaseName);
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} // namespace
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File diff suppressed because it is too large
Load Diff
@ -268,6 +268,7 @@ set(SRC
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visitors/op/atanh.cpp
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visitors/op/atanh.cpp
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visitors/op/batch_norm.cpp
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visitors/op/batch_norm.cpp
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visitors/op/batch_to_space.cpp
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visitors/op/batch_to_space.cpp
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visitors/op/binary_convolution.cpp
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visitors/op/broadcast.cpp
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visitors/op/broadcast.cpp
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visitors/op/bucketize.cpp
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visitors/op/bucketize.cpp
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visitors/op/ceiling.cpp
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visitors/op/ceiling.cpp
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@ -464,8 +465,6 @@ set(MULTI_TEST_SRC
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backend/ceiling.in.cpp
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backend/ceiling.in.cpp
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backend/concat.in.cpp
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backend/concat.in.cpp
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backend/constant.in.cpp
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backend/constant.in.cpp
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backend/convolution_backprop.in.cpp
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backend/binary_convolution.in.cpp
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backend/ctc_greedy_decoder.in.cpp
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backend/ctc_greedy_decoder.in.cpp
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backend/ctc_greedy_decoder_seq_len.in.cpp
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backend/ctc_greedy_decoder_seq_len.in.cpp
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backend/deformable_psroi_pooling.in.cpp
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backend/deformable_psroi_pooling.in.cpp
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@ -1,646 +0,0 @@
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// Copyright (C) 2018-2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "engines_util/execute_tools.hpp"
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#include "gtest/gtest.h"
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#include "ngraph/ngraph.hpp"
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#include "ngraph/runtime/tensor.hpp"
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#include "runtime/backend.hpp"
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#include "util/all_close.hpp"
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#include "util/all_close_f.hpp"
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#include "util/test_control.hpp"
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using namespace std;
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using namespace ngraph;
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static string s_manifest = "${MANIFEST}";
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template <typename T_IN, typename T_KERN>
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|
||||||
static void BinaryConvolutionTest(const std::vector<T_IN>& inputs,
|
|
||||||
const Shape inputs_shape,
|
|
||||||
const std::vector<T_KERN>& filters,
|
|
||||||
const Shape filters_shape,
|
|
||||||
const std::vector<T_IN>& outputs,
|
|
||||||
const Shape outputs_shape,
|
|
||||||
const Strides& strides,
|
|
||||||
const CoordinateDiff& padding,
|
|
||||||
const Strides& dilations,
|
|
||||||
const float pad_value = 0.0f) {
|
|
||||||
const CoordinateDiff pads_begin{padding};
|
|
||||||
const CoordinateDiff pads_end{padding};
|
|
||||||
const op::PadType auto_pad{op::PadType::EXPLICIT};
|
|
||||||
|
|
||||||
auto inputs_param = make_shared<op::Parameter>(element::from<T_IN>(), inputs_shape);
|
|
||||||
auto filters_const = make_shared<op::Constant>(element::u1, filters_shape, &filters[0]);
|
|
||||||
auto bin_conv =
|
|
||||||
make_shared<op::v1::BinaryConvolution>(inputs_param,
|
|
||||||
filters_const,
|
|
||||||
strides,
|
|
||||||
pads_begin,
|
|
||||||
pads_end,
|
|
||||||
dilations,
|
|
||||||
op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT,
|
|
||||||
pad_value,
|
|
||||||
auto_pad);
|
|
||||||
auto f = make_shared<Function>(bin_conv, ParameterVector{inputs_param});
|
|
||||||
|
|
||||||
auto backend = runtime::Backend::create("${BACKEND_NAME}");
|
|
||||||
|
|
||||||
auto input_tensor = backend->create_tensor(element::from<T_IN>(), inputs_shape);
|
|
||||||
copy_data(input_tensor, inputs);
|
|
||||||
auto result = backend->create_tensor(element::from<T_IN>(), outputs_shape);
|
|
||||||
|
|
||||||
auto handle = backend->compile(f);
|
|
||||||
handle->call_with_validate({result}, {input_tensor});
|
|
||||||
EXPECT_TRUE(test::all_close_f((outputs), read_vector<T_IN>(result), MIN_FLOAT_TOLERANCE_BITS));
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T_IN>
|
|
||||||
static void ConvolutionTest(const std::vector<T_IN>& inputs,
|
|
||||||
const Shape inputs_shape,
|
|
||||||
const std::vector<T_IN>& filters,
|
|
||||||
const Shape filters_shape,
|
|
||||||
const std::vector<T_IN>& outputs,
|
|
||||||
const Shape outputs_shape,
|
|
||||||
const Strides& strides,
|
|
||||||
const CoordinateDiff& padding,
|
|
||||||
const Strides& dilations) {
|
|
||||||
const CoordinateDiff pads_begin{padding};
|
|
||||||
const CoordinateDiff pads_end{padding};
|
|
||||||
const op::PadType auto_pad{op::PadType::EXPLICIT};
|
|
||||||
|
|
||||||
auto inputs_param = make_shared<op::Parameter>(element::from<T_IN>(), inputs_shape);
|
|
||||||
auto filters_param = make_shared<op::Parameter>(element::from<T_IN>(), filters_shape);
|
|
||||||
auto conv = make_shared<op::v1::Convolution>(inputs_param,
|
|
||||||
filters_param,
|
|
||||||
strides,
|
|
||||||
pads_begin,
|
|
||||||
pads_end,
|
|
||||||
dilations,
|
|
||||||
auto_pad);
|
|
||||||
auto f = make_shared<Function>(conv, ParameterVector{inputs_param, filters_param});
|
|
||||||
|
|
||||||
auto backend = runtime::Backend::create("${BACKEND_NAME}");
|
|
||||||
|
|
||||||
auto input_tensor = backend->create_tensor(element::from<T_IN>(), inputs_shape);
|
|
||||||
copy_data(input_tensor, inputs);
|
|
||||||
auto filters_tensor = backend->create_tensor(element::from<T_IN>(), filters_shape);
|
|
||||||
copy_data(filters_tensor, filters);
|
|
||||||
auto result = backend->create_tensor(element::from<T_IN>(), outputs_shape);
|
|
||||||
|
|
||||||
auto handle = backend->compile(f);
|
|
||||||
handle->call_with_validate({result}, {input_tensor, filters_tensor});
|
|
||||||
EXPECT_TRUE(test::all_close_f((outputs), read_vector<T_IN>(result), MIN_FLOAT_TOLERANCE_BITS));
|
|
||||||
}
|
|
||||||
|
|
||||||
// clang-format off
|
|
||||||
// --------------------- 2D convolution ------------------------------------------
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const CoordinateDiff padding{0, 0};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
|
|
||||||
const Shape inputs_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> inputs_conv{1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f};
|
|
||||||
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 2, 2};
|
|
||||||
const std::vector<float> outputs{1.0f, 1.0f,
|
|
||||||
3.0f, -1.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_padding_pad_val_0)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_conv{0, 0};
|
|
||||||
const Shape inputs_conv_shape{1, 1, 6, 6};
|
|
||||||
const std::vector<float> inputs_conv{-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_bin_conv{1, 1};
|
|
||||||
const Shape inputs_bin_conv_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f};
|
|
||||||
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> outputs{1.0f, -3.0f, -1.0f, 1.0f,
|
|
||||||
-3.0f, 1.0f, 1.0f, -5.0f,
|
|
||||||
-3.0f, 3.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -5.0f, 1.0f, -3.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_bin_conv_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_bin_conv,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_conv_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_conv,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_padding_pad_val_1)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
const float pad_value = 1.0f;
|
|
||||||
|
|
||||||
const CoordinateDiff padding_conv{0, 0};
|
|
||||||
const Shape inputs_conv_shape{1, 1, 6, 6};
|
|
||||||
const std::vector<float> inputs_conv{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_bin_conv{1, 1};
|
|
||||||
const Shape inputs_bin_conv_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f};
|
|
||||||
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> outputs{3.0f, -1.0f, 1.0f, 3.0f,
|
|
||||||
-1.0f, 1.0f, 1.0f, -3.0f,
|
|
||||||
-1.0f, 3.0f, -1.0f, 3.0f,
|
|
||||||
3.0f, -3.0f, 3.0f, -1.0f,};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_bin_conv_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_bin_conv,
|
|
||||||
dilations,
|
|
||||||
pad_value);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_conv_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_conv,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_stride)
|
|
||||||
{
|
|
||||||
const Strides strides{2, 2};
|
|
||||||
const CoordinateDiff padding{0, 0};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
|
|
||||||
const Shape inputs_shape{1, 1, 5, 5};
|
|
||||||
const std::vector<float> inputs_conv{-1.0f, 1.0f, 1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const std::vector<float> inputs_bin_conv{0.0f, 1.0f, 1.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{-1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, -1.0f};
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0x2E, 0x00}; // 00101110 00000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 2, 2};
|
|
||||||
const std::vector<float> outputs{-1.0f, 3.0f,
|
|
||||||
1.0f, 1.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_dilation)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const CoordinateDiff padding{0, 0};
|
|
||||||
const Strides dilations{2, 2};
|
|
||||||
|
|
||||||
const Shape inputs_shape{1, 1, 7, 7};
|
|
||||||
const std::vector<float> inputs_conv{1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f};
|
|
||||||
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f};
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> outputs{-5.0f, -3.0f, -5.0f,
|
|
||||||
5.0f, 1.0f, 3.0f,
|
|
||||||
-1.0f, -1.0f, 3.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME},
|
|
||||||
bin_convolution_2D_1batch_1channel_strides_dilation_padding_pad_val_0)
|
|
||||||
{
|
|
||||||
const Strides strides{2, 2};
|
|
||||||
const Strides dilations{2, 2};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_conv{0, 0};
|
|
||||||
const Shape inputs_conv_shape{1, 1, 11, 11};
|
|
||||||
const std::vector<float> inputs_conv{
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,-1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_bin_conv{2, 2};
|
|
||||||
const Shape inputs_bin_conv_shape{1, 1, 7, 7};
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f};
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> outputs{1.0f, 1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -5.0f, -5.0f, 5.0f,
|
|
||||||
3.0f, -1.0f, 3.0f, 3.0f,
|
|
||||||
-1.0f, -1.0f, 3.0f, -3.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_bin_conv_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_bin_conv,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_conv_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_conv,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME},
|
|
||||||
bin_convolution_2D_1batch_1channel_strides_dilation_padding_pad_val_1)
|
|
||||||
{
|
|
||||||
const Strides strides{2, 2};
|
|
||||||
const Strides dilations{2, 2};
|
|
||||||
const float pad_value = 1.0f;
|
|
||||||
|
|
||||||
const CoordinateDiff padding_conv{0, 0};
|
|
||||||
const Shape inputs_conv_shape{1, 1, 11, 11};
|
|
||||||
const std::vector<float> inputs_conv{
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f};
|
|
||||||
|
|
||||||
const CoordinateDiff padding_bin_conv{2, 2};
|
|
||||||
const Shape inputs_bin_conv_shape{1, 1, 7, 7};
|
|
||||||
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f};
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 4, 4};
|
|
||||||
const std::vector<float> outputs{3.0f, 3.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -5.0f, -5.0f, 3.0f,
|
|
||||||
1.0f, -1.0f, 3.0f, 1.0f,
|
|
||||||
-3.0f, 1.0f, 5.0f, -1.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_bin_conv_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_bin_conv,
|
|
||||||
dilations,
|
|
||||||
pad_value);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_conv_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding_conv,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_2channel)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const CoordinateDiff padding{0, 0};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
|
|
||||||
const Shape inputs_shape{1, 2, 4, 4};
|
|
||||||
const std::vector<float> inputs_conv{
|
|
||||||
// channel 1
|
|
||||||
1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
// channel 2
|
|
||||||
-1.0f, 1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, -1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f, -1.0f};
|
|
||||||
const std::vector<float> inputs_bin_conv{
|
|
||||||
// channel 1
|
|
||||||
1.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
// channel 2
|
|
||||||
0.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
0.0f, 1.0f, 0.0f, 0.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 2, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{
|
|
||||||
// channel 1
|
|
||||||
1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f,
|
|
||||||
// channel 2
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f};
|
|
||||||
// 10101010 10101010 10000000
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0xAA, 0xAA, 0x80};
|
|
||||||
|
|
||||||
const Shape outputs_shape{1, 1, 2, 2};
|
|
||||||
const std::vector<float> outputs{2.0f, 2.0f,
|
|
||||||
6.0f, -2.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
|
|
||||||
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_2batch_1channel)
|
|
||||||
{
|
|
||||||
const Strides strides{1, 1};
|
|
||||||
const CoordinateDiff padding{0, 0};
|
|
||||||
const Strides dilations{1, 1};
|
|
||||||
|
|
||||||
const Shape inputs_shape{2, 1, 4, 4};
|
|
||||||
const std::vector<float> inputs_conv{
|
|
||||||
// batch 1
|
|
||||||
1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, -1.0f,
|
|
||||||
-1.0f, -1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f, 1.0f,
|
|
||||||
// batch 2
|
|
||||||
-1.0f, -1.0f, -1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, 1.0f, -1.0f, 1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f, -1.0f};
|
|
||||||
const std::vector<float> inputs_bin_conv{
|
|
||||||
// batch 1
|
|
||||||
1.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 0.0f,
|
|
||||||
0.0f, 0.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 1.0f,
|
|
||||||
// batch 2
|
|
||||||
0.0f, 0.0f, 0.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 1.0f, 0.0f,
|
|
||||||
1.0f, 1.0f, 0.0f, 1.0f,
|
|
||||||
1.0f, 0.0f, 1.0f, 0.0f};
|
|
||||||
|
|
||||||
const Shape filters_shape{1, 1, 3, 3};
|
|
||||||
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
|
|
||||||
-1.0f, 1.0f, -1.0f,
|
|
||||||
1.0f, -1.0f, 1.0f};
|
|
||||||
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
|
|
||||||
|
|
||||||
const Shape outputs_shape{2, 1, 2, 2};
|
|
||||||
const std::vector<float> outputs{
|
|
||||||
// batch 1
|
|
||||||
1.0f, 1.0f,
|
|
||||||
3.0f, -1.0f,
|
|
||||||
// batch 2
|
|
||||||
-3.0f, 3.0f,
|
|
||||||
5.0f, -7.0f};
|
|
||||||
|
|
||||||
BinaryConvolutionTest(
|
|
||||||
inputs_bin_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_bin_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
|
|
||||||
ConvolutionTest(
|
|
||||||
inputs_conv,
|
|
||||||
inputs_shape,
|
|
||||||
filters_conv,
|
|
||||||
filters_shape,
|
|
||||||
outputs,
|
|
||||||
outputs_shape,
|
|
||||||
strides,
|
|
||||||
padding,
|
|
||||||
dilations);
|
|
||||||
}
|
|
||||||
// clang-format on
|
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ngraph/test/visitors/op/binary_convolution.cpp
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ngraph/test/visitors/op/binary_convolution.cpp
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// Copyright (C) 2018-2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "gtest/gtest.h"
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#include "ngraph/ngraph.hpp"
|
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#include "ngraph/op/util/attr_types.hpp"
|
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#include "ngraph/opsets/opset1.hpp"
|
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#include "ngraph/opsets/opset3.hpp"
|
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#include "ngraph/opsets/opset4.hpp"
|
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|
#include "ngraph/opsets/opset5.hpp"
|
||||||
|
#include "util/visitor.hpp"
|
||||||
|
|
||||||
|
using namespace std;
|
||||||
|
using namespace ngraph;
|
||||||
|
using ngraph::test::NodeBuilder;
|
||||||
|
using ngraph::test::ValueMap;
|
||||||
|
|
||||||
|
TEST(attributes, bin_convolution) {
|
||||||
|
NodeBuilder::get_ops().register_factory<op::v1::Convolution>();
|
||||||
|
const PartialShape data_batch_shape{1, 1, 5, 5};
|
||||||
|
const PartialShape filters_shape{1, 1, 3, 3};
|
||||||
|
Strides strides{1, 1};
|
||||||
|
CoordinateDiff pads_begin{0, 0};
|
||||||
|
CoordinateDiff pads_end{0, 0};
|
||||||
|
Strides dilations{1, 1};
|
||||||
|
const auto mode = op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT;
|
||||||
|
const float pad_value = 1.0f;
|
||||||
|
const auto auto_pad = op::PadType::SAME_LOWER;
|
||||||
|
|
||||||
|
auto data_batch = make_shared<op::Parameter>(element::f32, data_batch_shape);
|
||||||
|
auto filters = make_shared<op::Parameter>(element::u1, filters_shape);
|
||||||
|
|
||||||
|
auto conv = make_shared<op::v1::BinaryConvolution>(data_batch,
|
||||||
|
filters,
|
||||||
|
strides,
|
||||||
|
pads_begin,
|
||||||
|
pads_end,
|
||||||
|
dilations,
|
||||||
|
mode,
|
||||||
|
pad_value,
|
||||||
|
auto_pad);
|
||||||
|
NodeBuilder builder(conv);
|
||||||
|
auto g_convolution = ov::as_type_ptr<op::v1::BinaryConvolution>(builder.create());
|
||||||
|
|
||||||
|
// attribute count
|
||||||
|
const auto expected_attr_count = 7;
|
||||||
|
EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);
|
||||||
|
|
||||||
|
EXPECT_EQ(g_convolution->get_strides(), conv->get_strides());
|
||||||
|
EXPECT_EQ(g_convolution->get_pads_begin(), conv->get_pads_begin());
|
||||||
|
EXPECT_EQ(g_convolution->get_pads_end(), conv->get_pads_end());
|
||||||
|
EXPECT_EQ(g_convolution->get_dilations(), conv->get_dilations());
|
||||||
|
EXPECT_EQ(g_convolution->get_auto_pad(), conv->get_auto_pad());
|
||||||
|
EXPECT_EQ(g_convolution->get_mode(), conv->get_mode());
|
||||||
|
EXPECT_EQ(g_convolution->get_pad_value(), conv->get_pad_value());
|
||||||
|
}
|
||||||
Loading…
Reference in New Issue
Block a user