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debug CompileModelCacheTestBase
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@riverlijunjie
riverlijunjie committed Sep 26, 2023
1 parent b4dea53 commit 2481b4a
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Showing 6 changed files with 35 additions and 25 deletions.
2 changes: 1 addition & 1 deletion src/plugins/intel_cpu/src/dnnl_extension_utils.cpp
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Expand Up @@ -65,7 +65,7 @@ memory::data_type DnnlExtensionUtils::IEPrecisionToDataType(const InferenceEngin
case InferenceEngine::Precision::UNSPECIFIED:
return memory::data_type::undef;
default: {
return memory::data_type::undef;
OPENVINO_THROW("The plugin does not support ", prec.name());
}
}
}
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41 changes: 24 additions & 17 deletions src/plugins/intel_cpu/src/graph.cpp
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Expand Up @@ -201,6 +201,7 @@ void Graph::Replicate(const std::shared_ptr<const ov::Model> &model) {
});
};

#if 0
auto find_input_port_prec = [&](const std::string& name) -> ov::element::Type_t {
for (auto& it : model->inputs()) {
auto port_name = get_port_name(it, is_legacy_api);
Expand All @@ -213,11 +214,11 @@ void Graph::Replicate(const std::shared_ptr<const ov::Model> &model) {
OPENVINO_THROW("Cannot find input port with name: ", name);
};
// change precision for input/output nodes to avoid extra data conversion when set input/output blobs
// for (auto &input : inputNodesMap) {
// auto prec = InferenceEngine::details::convertPrecision(find_input_port_prec(input.first));
// const auto precToSet = normalizeToSupportedPrecision(prec);
// input.second->setOriginalOutputPrecisionAtPort(0, precToSet);
//}
for (auto& input : inputNodesMap) {
auto prec = InferenceEngine::details::convertPrecision(find_input_port_prec(input.first));
const auto precToSet = normalizeToSupportedPrecision(prec);
input.second->setOriginalOutputPrecisionAtPort(0, precToSet);
}

auto find_output_port_prec = [&](const std::string& name) -> ov::element::Type_t {
for (auto& it : model->outputs()) {
Expand All @@ -230,11 +231,12 @@ void Graph::Replicate(const std::shared_ptr<const ov::Model> &model) {
}
OPENVINO_THROW("Cannot find output port with name: ", name);
};
// for (auto &output : outputNodesMap) {
// auto prec = InferenceEngine::details::convertPrecision(find_output_port_prec(output.first));
// const auto precToSet = normalizeToSupportedPrecision(prec);
// output.second->setOriginalInputPrecisionAtPort(0, precToSet);
//}
for (auto &output : outputNodesMap) {
auto prec = InferenceEngine::details::convertPrecision(find_output_port_prec(output.first));
const auto precToSet = normalizeToSupportedPrecision(prec);
output.second->setOriginalInputPrecisionAtPort(0, precToSet);
}
#endif
// enforce must be performed after inputs and outputs info are taken into account
EnforceInferencePrecision();
// also we need to change input/output precisions for consumers/producers to avoid inserting reorder
Expand Down Expand Up @@ -446,11 +448,16 @@ void Graph::CreatePrimitivesAndExecConstants() const {
}

static bool isReorderAvailable(const MemoryDescPtr& parentDesc, const MemoryDescPtr& childDesc, const dnnl::engine& eng) {
auto definedParentDesc = parentDesc->isDefined() ? parentDesc : MemoryDescUtils::makeDummyDesc(*parentDesc);
memory::desc srcMemDesc = MemoryDescUtils::convertToDnnlMemoryDesc(definedParentDesc)->getDnnlDesc();

auto definedChildDesc = childDesc->isDefined() ? childDesc : MemoryDescUtils::makeDummyDesc(*childDesc);
memory::desc dstMemDesc = MemoryDescUtils::convertToDnnlMemoryDesc(definedChildDesc)->getDnnlDesc();
memory::desc srcMemDesc, dstMemDesc;
try {
auto definedParentDesc = parentDesc->isDefined() ? parentDesc : MemoryDescUtils::makeDummyDesc(*parentDesc);
memory::desc srcMemDesc = MemoryDescUtils::convertToDnnlMemoryDesc(definedParentDesc)->getDnnlDesc();

auto definedChildDesc = childDesc->isDefined() ? childDesc : MemoryDescUtils::makeDummyDesc(*childDesc);
memory::desc dstMemDesc = MemoryDescUtils::convertToDnnlMemoryDesc(definedChildDesc)->getDnnlDesc();
} catch (ov::Exception&) {
return false;
}

dnnl::primitive_attr attr;

Expand Down Expand Up @@ -503,7 +510,7 @@ void Graph::InitEdges() {
numberOfEdges--;
};

#if 0
#if 1
{
static std::mutex _lock;
std::lock_guard<std::mutex> guard(_lock);
Expand Down Expand Up @@ -591,7 +598,7 @@ void Graph::InitEdges() {
updateEdge(i);
}
}
#if 0
#if 1
{
static std::mutex _lock;
std::lock_guard<std::mutex> guard(_lock);
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4 changes: 2 additions & 2 deletions src/plugins/intel_cpu/src/node.cpp
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Expand Up @@ -1242,7 +1242,7 @@ std::vector<InferenceEngine::Precision> Node::getInputPrecisions() const {
for (size_t i = 0; i < getParentEdges().size(); i++) {
auto parentEdge = getParentEdgeAt(i);
if (parentEdge && parentEdge->getStatus() == Edge::Status::Validated) {
inputPrecisions.emplace_back(DnnlExtensionUtils::DataTypeToIEPrecision((parentEdge->getMemoryPtr()->getDataType())));
inputPrecisions.emplace_back(parentEdge->getMemoryPtr()->getDesc().getPrecision());
}
}
return inputPrecisions;
Expand All @@ -1253,7 +1253,7 @@ std::vector<InferenceEngine::Precision> Node::getOutputPrecisions() const {
for (size_t i = 0; i < getChildEdges().size(); i++) {
auto childEdge = getChildEdgeAt(i);
if (childEdge && childEdge->getStatus() == Edge::Status::Validated) {
outputPrecisions.emplace_back(DnnlExtensionUtils::DataTypeToIEPrecision((childEdge->getMemoryPtr()->getDataType())));
outputPrecisions.emplace_back(childEdge->getMemoryPtr()->getDesc().getPrecision());
}
}
return outputPrecisions;
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8 changes: 4 additions & 4 deletions src/plugins/intel_cpu/src/nodes/input.cpp
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Expand Up @@ -482,17 +482,17 @@ void Input::initSupportedPdDefault() {

if (getType() == Type::Input || getType() == Type::MemoryInput) {
auto precision = getOriginalOutputPrecisionAtPort(0);
if (precision == Precision::U16 || isMeanImage) {
precision = Precision::FP32;
}
// if (precision == Precision::U16 || isMeanImage) {
// precision = Precision::FP32;
//}

outPortConfs.push_back({LayoutType::ncsp, precision});
if (!getParentEdges().empty()) {
inPortConfs.push_back({LayoutType::ncsp, precision, true});
}
} else if (getType() == Type::Output) {
auto precision = getOriginalInputPrecisionAtPort(0);
if (precision == Precision::U16) precision = Precision::FP32;
// if (precision == Precision::U16) precision = Precision::FP32;

inPortConfs.push_back({LayoutType::ncsp, precision});
}
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2 changes: 1 addition & 1 deletion src/plugins/intel_cpu/src/utils/cpu_utils.hpp
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Expand Up @@ -91,7 +91,7 @@ inline bool isEmptyTensorDesc(const InferenceEngine::TensorDesc &td) {
return std::any_of(dims.begin(), dims.end(), [](size_t dim) { return dim == 0; } );
}

#if 0
#if 1
/**
* @brief Return precision to which given precision must be converted to be supported in plug-in
* @param precision
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3 changes: 3 additions & 0 deletions src/plugins/intel_cpu/tests/functional/shared_tests_instances/skip_tests_config.cpp
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Expand Up @@ -217,6 +217,9 @@ std::vector<std::string> disabledTestPatterns() {
R"(.*smoke_TopK/TopKLayerTest.Inference.*_k=21_.*_sort=value_modelType=f16_trgDev=CPU.*)",
// Issue: 121228
R"(smoke_TestsDFT_(1|2|3|4)d/DFTLayerTest.Inference.*bf16.*)",
// Issue: 121363
R"(.*smoke_Constant/ConstantLayerTest.*_dataPRC=(u4|u16|u32|i4|i16|f64).*)",
R"(.*smoke_Constant_with_negative_values/ConstantLayerTest.*_dataPRC=(u4|u16|u32|i4|i16|f64).*)",
};
#if defined(__APPLE__) && defined(OPENVINO_ARCH_ARM64)
// Issue: 120950
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