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[CPU] Enable CPU plugin cache for DepthToSpace. (#9492)

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* Enable CPU plugin RT cache for DepthToSpace.

* Applied review comments.

* Applied review comments.

* Apply reivew comments.
This commit is contained in:
Luwei Zhou 2022-01-12 16:43:24 +08:00 committed by GitHub
parent 4546df5091
commit 84bf5fa178
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 69 additions and 31 deletions
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47
src/plugins/intel_cpu/src/nodes/mkldnn_depth_to_space_node.cpp
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@ -4,14 +4,16 @@
#include "mkldnn_depth_to_space_node.h"
#include <cpu/x64/jit_generator.hpp>
#include <mkldnn_extension_utils.h>
#include "common/blocked_desc_creator.h"
#include <utils/general_utils.h>
#include <ngraph/opsets/opset1.hpp>
#include <string>
#include <cmath>
#include <common/primitive_hashing_utils.hpp>
#include <cpu/x64/jit_generator.hpp>
#include <ngraph/opsets/opset1.hpp>
#include <string>
#include "common/blocked_desc_creator.h"
#define THROW_ERROR IE_THROW() << "DepthToSpace layer with name '" << getName() << "' "
@ -19,6 +21,31 @@ using namespace MKLDNNPlugin;
using namespace InferenceEngine;
using namespace mkldnn::impl;
size_t MKLDNNDepthToSpaceNode::DepthToSpaceAttrs::hash() const {
using namespace dnnl::impl;
using namespace dnnl::impl::primitive_hashing;
size_t seed = 0;
seed = hash_combine(seed, layoutType);
seed = hash_combine(seed, mode);
seed = hash_combine(seed, blockSize);
seed = hash_combine(seed, blockStep);
seed = hash_combine(seed, dataSize);
seed = hash_combine(seed, nSpatialDims);
seed = get_vector_hash(seed, srcBlockedDims);
return seed;
}
bool MKLDNNDepthToSpaceNode::DepthToSpaceAttrs::operator==(const DepthToSpaceAttrs& rhs) const {
bool result = layoutType == rhs.layoutType && mode == rhs.mode &&
blockSize == rhs.blockSize && blockStep == rhs.blockStep &&
dataSize == rhs.dataSize && nSpatialDims == rhs.nSpatialDims &&
srcBlockedDims == rhs.srcBlockedDims;
return result;
}
bool MKLDNNDepthToSpaceNode::isSupportedOperation(const std::shared_ptr<const ngraph::Node>& op, std::string& errorMessage) noexcept {
try {
auto depthToSpace = ov::as_type_ptr<const ngraph::opset1::DepthToSpace>(op);
@ -157,7 +184,17 @@ void MKLDNNDepthToSpaceNode::createPrimitive() {
void MKLDNNDepthToSpaceNode::prepareParams() {
attrs.srcBlockedDims = getParentEdgeAt(0)->getMemoryPtr()->GetDescWithType<BlockedMemoryDesc>()->getBlockDims();
execPtr = std::make_shared<DepthToSpaceExecutor>(attrs);
auto builder = [](const DepthToSpaceAttrs& key) -> std::shared_ptr<DepthToSpaceExecutor> {
return std::make_shared<DepthToSpaceExecutor>(key);
};
auto cache = getRuntimeCache();
auto result = cache->getOrCreate(attrs, builder);
if (!result.first) {
IE_THROW() << "DepthToSpaceExecutor was not found for node " << getName() << ".";
}
execPtr = result.first;
}
MKLDNNDepthToSpaceNode::DepthToSpaceExecutor::DepthToSpaceExecutor(const DepthToSpaceAttrs& attrs) {

19
src/plugins/intel_cpu/src/nodes/mkldnn_depth_to_space_node.h
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@ -24,15 +24,7 @@ public:
void prepareParams() override;
protected:
void executeDynamicImpl(mkldnn::stream strm) override;
private:
enum Mode {
BLOCKS_FIRST = 0,
DEPTH_FIRST = 1
};
enum Mode { BLOCKS_FIRST = 0, DEPTH_FIRST = 1 };
struct DepthToSpaceAttrs {
LayoutType layoutType;
Mode mode;
@ -41,8 +33,15 @@ private:
size_t dataSize = 1lu;
size_t nSpatialDims = 0lu;
VectorDims srcBlockedDims;
} attrs;
size_t hash() const;
bool operator==(const DepthToSpaceAttrs& rhs) const;
};
protected:
void executeDynamicImpl(mkldnn::stream strm) override;
private:
DepthToSpaceAttrs attrs;
struct DepthToSpaceExecutor {
DepthToSpaceExecutor(const DepthToSpaceAttrs& attrs);
void exec(MKLDNNMemoryPtr& srcMemPtr, MKLDNNMemoryPtr& dstMemPtr, const int MB);

18
src/tests/functional/plugin/cpu/single_layer_tests/depth_to_space.cpp
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@ -209,35 +209,37 @@ INSTANTIATE_TEST_SUITE_P(smoke_CPUDepthToSpaceStaticBS3_5D, DepthToSpaceLayerCPU
} // namespace static_shapes
/* *========================* *==================* *========================* */
/* *========================* Dynamic Shapes Tests *========================* */
namespace dynamic_shapes {
const std::vector<InputShape> inputShapes4D = {
{{-1, -1, -1, -1}, // dynamic
{{2, 36, 1, 1}, {1, 36, 3, 1}, {1, 72, 1, 4}}}, // target
{{2, 36, 1, 1}, {1, 36, 3, 1}, {2, 36, 1, 1}, {1, 36, 3, 1}}}, // target
{{-1, 576, -1, -1}, // dynamic
{{1, 576, 1, 1}, {1, 576, 2, 2}, {3, 576, 4, 1}}}, // target
{{1, 576, 1, 1}, {1, 576, 2, 2}, {3, 576, 4, 1}, {1, 576, 1, 1}}}, // target
{{{1, 5}, {36, 72}, {1, 16}, {1, 16}}, // dynamic
{{3, 36, 4, 4}, {1, 36, 16, 12}, {3, 72, 8, 8}}}, // target
{{3, 36, 4, 4}, {1, 36, 16, 12}, {3, 72, 8, 8}, {1, 36, 16, 12}}}, // target
};
const std::vector<InputShape> inputShapes5D = {
{{-1, -1, -1, -1, -1}, // dynamic
{{2, 216, 1, 1, 1}, {1, 216, 3, 1, 2}, {1, 432, 2, 3, 1}}}, // target
{{2, 216, 1, 1, 1},
{1, 216, 3, 1, 2},
{1, 432, 2, 3, 1},
{2, 216, 1, 1, 1}}}, // target
{{{1, 3}, {216, 432}, {1, 4}, {1, 4}, {1, 4}}, // dynamic
{{3, 216, 2, 2, 2}, {1, 432, 1, 1, 1}}}, // target
{{3, 216, 2, 2, 2}, {1, 432, 1, 1, 1}, {3, 216, 2, 2, 2}}}, // target
};
const std::vector<InputShape> inputShapesBlocked5D = {
{{-1, 256, -1, -1, -1}, // dynamic
{{1, 256, 1, 1, 1}, {1, 256, 2, 1, 4}, {3, 256, 4, 1, 2}}}, // target
{{1, 256, 1, 1, 1}, {1, 256, 2, 1, 4}, {3, 256, 4, 1, 2}, {1, 256, 1, 1, 1}}}, // target
{{{1, 3}, 256, {1, 3}, {1, 3}, {1, 3}}, // dynamic
{{1, 256, 1, 1, 1}, {1, 256, 2, 1, 3}, {3, 256, 3, 1, 2}}}, // target
{{1, 256, 1, 1, 1}, {1, 256, 2, 1, 3}, {3, 256, 3, 1, 2}, {1, 256, 2, 1, 3}}}, // target
};
INSTANTIATE_TEST_SUITE_P(smoke_CPUDepthToSpaceDynamic4D, DepthToSpaceLayerCPUTest,