[CPU Plugin][Func Test] Upgrade ConvWithZeroPointFuseSubgraphTest to API 2.0 (#21330)
Signed-off-by: Zhai, Xuejun <xuejun.zhai@intel.com>
This commit is contained in:
Xuejun Zhai
GitHub
parent
164d101295
commit
441427abc8
@ -4,23 +4,23 @@
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#pragma once
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#include <string>
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#include <tuple>
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#include <vector>
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#include <string>
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#include "test_utils/cpu_test_utils.hpp"
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#include "shared_test_classes/base/layer_test_utils.hpp"
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#include "ov_models/utils/ov_helpers.hpp"
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#include "ov_models/builders.hpp"
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#include "ov_models/utils/ov_helpers.hpp"
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#include "shared_test_classes/base/ov_subgraph.hpp"
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#include "test_utils/cpu_test_utils.hpp"
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using namespace CPUTestUtils;
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namespace SubgraphTestsDefinitions {
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namespace ov {
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namespace test {
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using convConcatCPUParams = std::tuple<
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nodeType, // Ngraph convolution type
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InferenceEngine::SizeVector // Input shapes
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>;
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using convConcatCPUParams = std::tuple<nodeType, // Node convolution type
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ov::Shape // Input shapes
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>;
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// Subgraph:
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/*
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@ -44,7 +44,7 @@ using convConcatCPUParams = std::tuple<
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class ConvWithZeroPointFuseSubgraphTest : public testing::WithParamInterface<convConcatCPUParams>,
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public CPUTestsBase,
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virtual public LayerTestsUtils::LayerTestsCommon {
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virtual public SubgraphBaseStaticTest {
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public:
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static std::string getTestCaseName(testing::TestParamInfo<convConcatCPUParams> obj);
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@ -53,4 +53,5 @@ protected:
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std::string pluginTypeNode;
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};
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} // namespace SubgraphTestsDefinitions
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} // namespace test
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} // namespace ov
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@ -2,19 +2,21 @@
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "ngraph/opsets/opset1.hpp"
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#include "test_utils/convolution_params.hpp"
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#include "subgraph_tests/include/conv_with_zero_point_fuse.hpp"
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using namespace InferenceEngine;
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#include "common_test_utils/node_builders/convolution.hpp"
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#include "common_test_utils/node_builders/group_convolution.hpp"
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#include "test_utils/convolution_params.hpp"
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using namespace CPUTestUtils;
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namespace SubgraphTestsDefinitions {
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namespace ov {
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namespace test {
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std::string ConvWithZeroPointFuseSubgraphTest::getTestCaseName(testing::TestParamInfo<convConcatCPUParams> obj) {
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std::ostringstream result;
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nodeType type;
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SizeVector inputShapes;
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ov::Shape inputShapes;
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std::tie(type, inputShapes) = obj.param;
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result << "Type=" << nodeType2str(type) << "_";
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@ -26,115 +28,110 @@ std::string ConvWithZeroPointFuseSubgraphTest::getTestCaseName(testing::TestPara
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void ConvWithZeroPointFuseSubgraphTest::SetUp() {
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targetDevice = ov::test::utils::DEVICE_CPU;
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nodeType type;
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SizeVector inputShapes;
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ov::Shape inputShapes;
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std::tie(type, inputShapes) = this->GetParam();
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pluginTypeNode = nodeType2PluginType(type);
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const ngraph::op::PadType paddingType { ngraph::op::PadType::EXPLICIT };
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const ov::op::PadType paddingType{ov::op::PadType::EXPLICIT};
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const size_t numOutChannels = 256;
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const SizeVector dilation { 1, 1 };
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const SizeVector kernelSize { 1, 1 };
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const SizeVector strides { 1, 1 };
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const std::vector<ptrdiff_t> padBegin { 0, 0 };
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const std::vector<ptrdiff_t> padEnd { 0, 0 };
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const std::vector<size_t> dilation{1, 1};
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const std::vector<size_t> kernelSize{1, 1};
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const std::vector<size_t> strides{1, 1};
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const std::vector<ptrdiff_t> padBegin{0, 0};
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const std::vector<ptrdiff_t> padEnd{0, 0};
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selectedType = ".*_I8";
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selectedType = ".*_i8";
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ov::ParameterVector inputParams {std::make_shared<ov::op::v0::Parameter>(ngraph::element::f32, ov::Shape(inputShapes))};
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const auto fq = ngraph::builder::makeFakeQuantize(
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inputParams[0],
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ov::element::f32,
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256,
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{1, 1, 1, 1},
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{-12.8f},
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{12.7f},
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{-12.8f},
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{12.7f});
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ov::ParameterVector inputParams{std::make_shared<ov::op::v0::Parameter>(ov::element::f32, inputShapes)};
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const auto fq = ngraph::builder::makeFakeQuantize(inputParams[0],
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ov::element::f32,
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256,
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{1, 1, 1, 1},
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{-12.8f},
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{12.7f},
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{-12.8f},
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{12.7f});
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std::vector<std::shared_ptr<ngraph::Node>> branches(2);
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{
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ngraph::Strides strides{1, 1};
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ngraph::Shape pads_begin{0, 0}, pads_end{0, 0}, kernel{1, 1};
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branches[0] = std::make_shared<ngraph::opset1::MaxPool>(fq,
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strides,
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pads_begin,
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pads_end,
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kernel);
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ov::Strides strides{1, 1};
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ov::Shape pads_begin{0, 0}, pads_end{0, 0}, kernel{1, 1};
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branches[0] = std::make_shared<ov::op::v1::MaxPool>(fq, strides, pads_begin, pads_end, kernel);
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}
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{
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const auto fq_conv_data = ngraph::builder::makeFakeQuantize(
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fq,
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ov::element::f32,
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256,
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{1, 1, 1, 1},
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{-12.8f},
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{12.7f},
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{-12.8f},
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{12.7f});
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const auto fq_conv_data = ngraph::builder::makeFakeQuantize(fq,
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ov::element::f32,
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256,
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{1, 1, 1, 1},
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{-12.8f},
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{12.7f},
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{-12.8f},
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{12.7f});
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const InferenceEngine::SizeVector weights_const_shape = {numOutChannels, inputShapes[1], kernelSize[0], kernelSize[1]};
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const auto weights_const_values = std::vector<int>(ngraph::shape_size(weights_const_shape), 1);
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const auto weights_const = ngraph::builder::makeConstant(ov::element::i8, weights_const_shape, weights_const_values);
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const ov::Shape weights_const_shape = {numOutChannels, inputShapes[1], kernelSize[0], kernelSize[1]};
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const auto weights_const_values = std::vector<int>(ov::shape_size(weights_const_shape), 1);
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const auto weights_const =
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ngraph::builder::makeConstant(ov::element::i8, weights_const_shape, weights_const_values);
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const auto weights_convert = std::make_shared<ov::op::v0::Convert>(weights_const, ov::element::f32);
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const auto weights_multiply = std::make_shared<ov::opset10::Multiply>(
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weights_convert,
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ngraph::builder::makeConstant(ov::element::f32,
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{numOutChannels, 1, 1, 1},
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std::vector<float>(numOutChannels, 1.0)));
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{numOutChannels, 1, 1, 1},
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std::vector<float>(numOutChannels, 1.0)));
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switch (type) {
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case nodeType::convolution: {
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branches[1] = ngraph::builder::makeConvolution(fq_conv_data,
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weights_multiply,
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ngraph::element::f32,
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kernelSize,
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strides,
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padBegin,
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padEnd,
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dilation,
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paddingType,
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numOutChannels);
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break;
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}
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case nodeType::groupConvolution: {
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branches[1] = ngraph::builder::makeGroupConvolution(
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fq_conv_data,
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std::make_shared<ov::opset10::Reshape>(
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weights_multiply,
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ngraph::builder::makeConstant(
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ov::element::i32,
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{5},
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std::vector<size_t>{1, numOutChannels, inputShapes[1], kernelSize[0], kernelSize[1]}),
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true),
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ngraph::element::f32,
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strides,
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padBegin,
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padEnd,
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dilation,
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paddingType);
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break;
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}
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default: {
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throw std::runtime_error("Subgraph concat test doesn't support this type of operation");
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}
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case nodeType::convolution: {
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branches[1] = ov::test::utils::make_convolution(fq_conv_data,
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weights_multiply,
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ov::element::f32,
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kernelSize,
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strides,
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padBegin,
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padEnd,
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dilation,
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paddingType,
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numOutChannels);
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break;
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}
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case nodeType::groupConvolution: {
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branches[1] = ov::test::utils::make_group_convolution(
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fq_conv_data,
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std::make_shared<ov::opset10::Reshape>(
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weights_multiply,
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ngraph::builder::makeConstant(
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ov::element::i32,
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{5},
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std::vector<size_t>{1, numOutChannels, inputShapes[1], kernelSize[0], kernelSize[1]}),
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true),
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ov::element::f32,
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strides,
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padBegin,
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padEnd,
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dilation,
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paddingType);
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break;
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}
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default: {
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throw std::runtime_error("Subgraph concat test doesn't support this type of operation");
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}
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}
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}
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auto concat = std::make_shared<ov::op::v0::Concat>(ov::NodeVector{branches[0], branches[1]}, 1);
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ngraph::ResultVector results{std::make_shared<ngraph::opset4::Result>(concat)};
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function = std::make_shared<ngraph::Function>(results, inputParams, "ConvWithZeroPointFuseSubgraphTest");
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ov::ResultVector results{std::make_shared<ov::op::v0::Result>(concat)};
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function = std::make_shared<ov::Model>(results, inputParams, "ConvWithZeroPointFuseSubgraphTest");
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}
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TEST_P(ConvWithZeroPointFuseSubgraphTest, CompareWithRefs) {
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Run();
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run();
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CheckPluginRelatedResults(executableNetwork, pluginTypeNode);
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CheckPluginRelatedResults(compiledModel, pluginTypeNode);
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};
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const SizeVector inputShapes2D = {1, 32, 136, 136};
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const ov::Shape inputShapes2D = {1, 32, 136, 136};
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const auto params2DConv = ::testing::Combine(::testing::ValuesIn({nodeType::convolution, nodeType::groupConvolution}),
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::testing::Values(inputShapes2D));
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@ -144,4 +141,5 @@ INSTANTIATE_TEST_SUITE_P(smoke_ConvWithZeroPointFuse,
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params2DConv,
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ConvWithZeroPointFuseSubgraphTest::getTestCaseName);
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} // namespace SubgraphTestsDefinitions
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} // namespace test
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} // namespace ov
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