[CPU]Fix regression issue. (#23904)
### Details: - *Add callback fun param for selectPreferPrimitiveDescriptor* - *Update Snippet node selectPreferPrimitiveDescriptor algorithm.* - *Add test* ### Tickets: - *137307* --------- Signed-off-by: xipingya <xiping.yan@intel.com>
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Xiping Yan
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f32c023c91
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@ -283,6 +283,75 @@ void Snippet::initSupportedPrimitiveDescriptors() {
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}
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void Snippet::selectOptimalPrimitiveDescriptor() {
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// Check if memory desc is in SupportedPrimitiveDescriptors.
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auto memDescInSupportedPD = [&](const ov::intel_cpu::MemoryDescPtr& parentMemDesc,
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const size_t& idx,
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size_t& supportedPDIdx) {
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for (auto& type : getImplPriority()) {
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for (size_t i = 0; i < getSupportedPrimitiveDescriptors().size(); i++) {
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const auto& supportedPrimitiveDesc = getSupportedPrimitiveDescriptors()[i];
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const impl_desc_type supportedType = supportedPrimitiveDesc.getImplementationType();
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if (supportedType == type) {
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const auto& supportedMemDesc = supportedPrimitiveDesc.getConfig().inConfs[idx].getMemDesc();
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// Static shape + same shape + same precision + same layout
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if (parentMemDesc->getShape().isStatic() && supportedMemDesc->getShape().isStatic() &&
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parentMemDesc->getShape() == supportedMemDesc->getShape() &&
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parentMemDesc->getPrecision() == supportedMemDesc->getPrecision()) {
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if ((parentMemDesc->hasLayoutType(LayoutType::ncsp) &&
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supportedMemDesc->hasLayoutType(LayoutType::ncsp)) ||
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(parentMemDesc->hasLayoutType(LayoutType::nspc) &&
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supportedMemDesc->hasLayoutType(LayoutType::nspc))) {
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supportedPDIdx = i;
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return true;
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}
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}
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}
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}
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}
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return false;
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};
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if (getParentEdges().size() == 3u) {
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auto check_special_shape = [](const ov::intel_cpu::Shape& shape) {
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// SShape=[1,?,1,1]
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if (shape.isStatic()) {
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const auto& dims = shape.getDims();
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if (dims.size() == 4u) {
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return dims[0] == 1u && dims[1] > 1u && dims[2] == 1u && dims[3] == 1u;
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}
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}
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return false;
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};
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int num_sshape_ncsp = 0;
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int num_nonsshape_nspc = 0;
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size_t selectedPDIdx = 0;
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for (size_t i = 0; i < getParentEdges().size(); i++) {
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auto parentEdge = getParentEdgeAt(i);
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auto parentPtr = parentEdge->getParent();
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auto parent_spd = parentPtr->getSelectedPrimitiveDescriptor();
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auto parentDesc = parent_spd->getConfig().outConfs[0].getMemDesc();
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size_t supportedPDIdx = 0;
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if (check_special_shape(parentDesc->getShape()) && parentDesc->hasLayoutType(LayoutType::ncsp) &&
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memDescInSupportedPD(parentDesc, i, supportedPDIdx)) {
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num_sshape_ncsp++;
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}
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if ((!check_special_shape(parentDesc->getShape())) && parentDesc->hasLayoutType(LayoutType::nspc) &&
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memDescInSupportedPD(parentDesc, i, supportedPDIdx)) {
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num_nonsshape_nspc++;
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selectedPDIdx = supportedPDIdx;
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}
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}
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bool foundOptimalPD = num_sshape_ncsp == 2 && num_nonsshape_nspc == 1;
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if (foundOptimalPD) {
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selectPrimitiveDescriptorByIndex(selectedPDIdx);
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return;
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}
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}
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// fallback
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selectPreferPrimitiveDescriptor(getImplPriority(), true);
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}
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@ -0,0 +1,124 @@
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// Copyright (C) 2024 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "openvino/opsets/opset8.hpp"
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#include "ov_models/builders.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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namespace ov {
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namespace test {
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/*
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input1(f32_abcd_{1,64,32,32}) input2(f32_abcd_{1,128,1,1})
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| |
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Reorder(f32_acdb_{1,64,32,32}) const |
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| / |
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| / |
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Convolution(f32_acdb_{1,1,30,30}) Range_1520 VariadicSplit(f32_abcd_{1,64,1,1}, f32_abcd_{1,64,1,1})
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| / \ /
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| / \ /
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| / \ /
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| / \ /
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MVN(f32_acdb_{1,1,30,30}) Reorder1(f32_acdb_{1,64,1,1}) Reorder2(f32_acdb_{1,64,1,1})
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\ / /
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\ / /
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\ / /
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\ / /
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Subgraph(f32_acdb_{1,64,30,30})
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Convolution(f32_acdb_{1,1,28,28})
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Result
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The Subgraph node have 3 inputs: they don't have same layout.
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Expected: Reorder is inserted after VariadicSplit[0] and VariadicSplit[1], not inserted after MVN.
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Because VariadicSplit's output layout is [1,64,1,1], it' reorder almost have calculation.
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*/
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class SubgraphSelectPD : virtual public SubgraphBaseStaticTest {
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protected:
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void SetUp() override {
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targetDevice = ov::test::utils::DEVICE_CPU;
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abs_threshold = 2e-2;
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auto type = element::f32;
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constexpr int const1 = 32;
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auto input1 = std::make_shared<ov::opset8::Parameter>(type, Shape{1, const1 / 2, 8, 8});
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input1->set_friendly_name("input1");
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auto input2 = std::make_shared<ov::opset8::Parameter>(type, Shape{1, const1, 1, 1});
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input2->set_friendly_name("input2");
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auto variadicSplit = std::make_shared<ov::op::v1::VariadicSplit>(
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input2,
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ov::opset8::Constant::create(element::i64, Shape{1}, {1}),
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ov::opset8::Constant::create(element::i64, Shape{2}, {const1 / 2, const1 / 2}));
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variadicSplit->set_friendly_name("variadicSplit");
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auto add1 = std::make_shared<ov::opset8::Add>(variadicSplit->output(0),
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ov::opset8::Constant::create(type, Shape{1}, {0}));
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add1->set_friendly_name("add1");
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auto shapeof = std::make_shared<ov::opset8::ShapeOf>(input1);
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auto rankof = std::make_shared<ov::opset8::ShapeOf>(shapeof);
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auto squeeze =
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std::make_shared<ov::opset8::Squeeze>(rankof, ov::opset8::Constant::create(element::i64, Shape{1}, {0}));
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auto range = std::make_shared<ov::opset8::Range>(ov::opset8::Constant::create(element::i64, Shape{}, {2}),
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squeeze,
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ov::opset8::Constant::create(element::i64, Shape{}, {1}),
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ov::element::i64);
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auto create_conv = [&](const std::shared_ptr<ov::Node>& input_node) {
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auto conv = std::make_shared<ov::opset8::Convolution>(
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input_node,
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ngraph::builder::makeConstant(type,
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Shape{const1 / 2u, const1 / 2u, 3, 3},
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std::vector<float>{},
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true,
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0.1f,
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0.9f),
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Strides{1, 1},
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CoordinateDiff{1, 1},
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CoordinateDiff{1, 1},
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Strides{1, 1});
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conv->get_rt_info() =
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CPUTestUtils::CPUTestsBase::makeCPUInfo({CPUTestUtils::nhwc}, {CPUTestUtils::nhwc}, {});
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return conv;
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};
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auto create_relu = [&](const std::shared_ptr<ov::Node>& input_node) {
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return std::make_shared<ov::opset8::PRelu>(input_node,
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ov::opset8::Constant::create(element::f32, Shape{1}, {1}));
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};
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auto conv1 = create_conv(input1);
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auto mvn =
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std::make_shared<ov::opset8::MVN>(create_relu(conv1), range, false, 0.1, op::MVNEpsMode::INSIDE_SQRT);
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auto mul = std::make_shared<ov::opset8::Multiply>(create_relu(add1), mvn);
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auto add2 = std::make_shared<ov::opset8::Add>(variadicSplit->output(1), mul);
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auto conv2 = create_conv(create_relu(add2));
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conv2->set_friendly_name("conv2");
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function = std::make_shared<ov::Model>(conv2, ParameterVector{input1, input2});
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}
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void TearDown() override {
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auto runtime_function = compiledModel.get_runtime_model();
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int nodes_found = 0;
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for (const auto& n : runtime_function->get_ordered_ops()) {
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auto layer_type = n->get_rt_info().at(ov::exec_model_info::LAYER_TYPE).as<std::string>();
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if (layer_type == "Subgraph") {
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nodes_found++;
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auto output_layout = n->get_rt_info().at(ov::exec_model_info::OUTPUT_LAYOUTS).as<std::string>();
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// The optimal choose should be: 'nhwc'.
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ASSERT_EQ(output_layout, "acdb");
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}
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}
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ASSERT_GT(nodes_found, 0);
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}
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};
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TEST_F(SubgraphSelectPD, smoke_CompareWithRefs) {
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run();
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}
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} // namespace test
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} // namespace ov
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