131 lines
5.6 KiB
C++
131 lines
5.6 KiB
C++
// Copyright (C) 2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "bfloat16_helpers.hpp"
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#include <memory>
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#include <tuple>
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#include <vector>
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#include <string>
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#include <functional>
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#include <map>
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#include <utility>
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#include <ie_core.hpp>
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#include "functional_test_utils/blob_utils.hpp"
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#include "common_test_utils/common_utils.hpp"
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#include "ngraph/opsets/opset1.hpp"
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using namespace std;
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using namespace ngraph;
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using namespace InferenceEngine;
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namespace LayerTestsDefinitions {
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class ConvConv : public BasicBF16Test {
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protected:
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std::shared_ptr<ngraph::Function> createGraph(InferenceEngine::Precision netPrecision) override {
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// ScaleShift (FP32)
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// |
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// Conv (BF16)
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// |
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// Conv (BF16)
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ngraph::element::Type ntype = (netPrecision == Precision::FP32) ? ngraph::element::f32 : ngraph::element::bf16;
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// multiply
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auto input1 = std::make_shared<opset1::Parameter>(ngraph::element::f32, ngraph::Shape{inputShapes});
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auto const1 = opset1::Constant::create(ngraph::element::f32, Shape{1}, { 2.0f });
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auto mulNode = std::make_shared<opset1::Multiply>(input1, const1);
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// add
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auto const2 = opset1::Constant::create(ngraph::element::f32, Shape{1}, { 1.0f });
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auto addNode = std::make_shared<opset1::Add>(mulNode, const2);
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addNode->set_friendly_name("ADD_1");
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// convolution
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std::shared_ptr<ngraph::opset1::Constant> weightsNode = nullptr;
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auto channelsCount = inputShapes[1];
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ngraph::Shape convFilterShape = { channelsCount, channelsCount, 3, 3 }; // out channel, /input channels, kernel h, kernel w
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if (netPrecision == Precision::FP32) {
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std::vector<float> weightValuesFP32;
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weightValuesFP32.resize(channelsCount * channelsCount * 3 * 3);
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FuncTestUtils::fillInputsBySinValues(weightValuesFP32.data(), weightValuesFP32.size());
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weightsNode = std::make_shared<ngraph::opset1::Constant>(ntype, convFilterShape, weightValuesFP32);
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} else {
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std::vector<short> weightValuesBF16;
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weightValuesBF16.resize(channelsCount * channelsCount * 3 * 3);
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FuncTestUtils::fillInputsBySinValues(weightValuesBF16.data(), weightValuesBF16.size());
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weightsNode = std::make_shared<ngraph::opset1::Constant>(ntype, convFilterShape, weightValuesBF16.data());
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}
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std::shared_ptr<ngraph::Node> convNode1 = std::make_shared<ngraph::opset1::Convolution>(
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addNode, weightsNode,
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ngraph::Strides({ 1, 1 }), // strides
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ngraph::CoordinateDiff({ 1, 1 }), // pad begin
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ngraph::CoordinateDiff({ 1, 1 }), // pad end
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ngraph::Strides({ 1, 1 }), // dilation
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ngraph::op::PadType::EXPLICIT); // pad type
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convNode1->set_friendly_name("CONV_1");
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// Convolution
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ngraph::Shape convFilterShape2 = { channelsCount, channelsCount, 3, 3 }; // out channel, /input channels, kernel h, kernel w
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std::vector<float> weightValues2;
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weightValues2.resize(channelsCount * channelsCount * 3 * 3);
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FuncTestUtils::fillInputsBySinValues(weightValues2.data(), weightValues2.size());
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auto weightsNode2 = std::make_shared<ngraph::opset1::Constant>(ngraph::element::f32, convFilterShape2, weightValues2);
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std::shared_ptr<ngraph::Node> convNode2 = std::make_shared<ngraph::opset1::Convolution>(
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convNode1, weightsNode2,
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ngraph::Strides({ 1, 1 }), // strides
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ngraph::CoordinateDiff({ 0, 0 }), // pad begin
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ngraph::CoordinateDiff({ 0, 0 }), // pad end
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ngraph::Strides({ 1, 1 }), // dilation
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ngraph::op::PadType::EXPLICIT); // pad type
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convNode2->set_friendly_name("CONV_2");
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return std::make_shared<ngraph::Function>(ngraph::NodeVector{convNode2}, ngraph::ParameterVector{input1});
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}
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void SetUp() override {
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std::tie(inputPrecision, netPrecision, inputShapes, newInputShapes, targetDevice) = this->GetParam();
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fnPtr = createGraph(netPrecision);
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// STAGE1:
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threshold = 1.0f; // Max in fp32 network by output CONV_2: 49.3427
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// STAGE2:
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// filling of expected precision of layer execution defined by precisoin of input tensor to the primitive and reflected in
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// performance counters
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expectedPrecisions["ADD_1"] = "FP32";
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expectedPrecisions["CONV_1"] = "BF16";
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expectedPrecisions["CONV_2"] = "BF16";
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}
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};
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TEST_P(ConvConv, CompareWithRefImpl) {
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test();
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};
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INSTANTIATE_TEST_CASE_P(FP32_bfloat16_NoReshape, ConvConv,
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::testing::Combine(
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::testing::Values(Precision::FP32),
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::testing::Values(Precision::FP32),
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::testing::Values(SizeVector({ 1, 3, 40, 40 })),
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::testing::Values(SizeVector()),
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::testing::Values(CommonTestUtils::DEVICE_CPU)),
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ConvConv::getTestCaseName);
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INSTANTIATE_TEST_CASE_P(BF16_bfloat16_NoReshape, ConvConv,
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::testing::Combine(
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::testing::Values(Precision::FP32),
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::testing::Values(Precision::FP32),
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::testing::Values(SizeVector({ 1, 3, 40, 40 })),
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::testing::Values(SizeVector()),
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::testing::Values(CommonTestUtils::DEVICE_CPU)),
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ConvConv::getTestCaseName);
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} // namespace LayerTestsDefinitions
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