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49 changes: 16 additions & 33 deletions
49
src/plugins/intel_cpu/src/nodes/executors/acl/acl_mvn.hpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,51 +1,34 @@ | ||
| // Copyright (C) 2023 Intel Corporation | ||
| // Copyright (C) 2018-2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
|
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| #pragma once | ||
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| #include "acl_utils.hpp" | ||
| #include "nodes/executors/mvn.hpp" | ||
| #include "arm_compute/runtime/NEON/NEFunctions.h" | ||
| #include "utils/debug_capabilities.h" | ||
| #include "acl_common_executor.hpp" | ||
| #include "nodes/executors/mvn_config.hpp" | ||
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| namespace ov { | ||
| namespace intel_cpu { | ||
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| class AclMVNExecutor : public MVNExecutor { | ||
| class ACLMVNExecutor : public ACLCommonExecutor { | ||
| public: | ||
| AclMVNExecutor(const ExecutorContext::CPtr context); | ||
| ACLMVNExecutor(const MVNAttrs& attrs, | ||
| const PostOps& postOps, | ||
| const MemoryArgs& memory, | ||
| const ExecutorContext::CPtr context) : aclMVNAtrrs(attrs) {} | ||
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| bool init(const MVNAttrs& mvnAttrs, | ||
| const std::vector<MemoryDescPtr>& srcDescs, | ||
| const std::vector<MemoryDescPtr>& dstDescs, | ||
| const dnnl::primitive_attr &attr) override; | ||
| void exec(const std::vector<MemoryCPtr>& src, | ||
| const std::vector<MemoryPtr>& dst, | ||
| const void *post_ops_data_) override; | ||
| static bool supports(const MVNConfig& config); | ||
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| impl_desc_type getImplType() const override { | ||
| return implType; | ||
| } | ||
| void updateTensorsShapes(ACLShapes& aclMemoryShapes) override; | ||
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| private: | ||
| impl_desc_type implType = impl_desc_type::acl; | ||
| arm_compute::Status validateTensorsInfo(const ACLInfos & aclMemoryInfos) override; | ||
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| arm_compute::Tensor srcTensor; | ||
| arm_compute::Tensor dstTensor; | ||
| std::unique_ptr<arm_compute::NEMeanStdDevNormalizationLayer> mvn = nullptr; | ||
| }; | ||
| ACLFunction configureFunction(const ACLTensors & aclMemoryTensors) override; | ||
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| class AclMVNExecutorBuilder : public MVNExecutorBuilder { | ||
| public: | ||
| bool isSupported(const MVNAttrs& mvnAttrs, | ||
| const std::vector<MemoryDescPtr>& srcDescs, | ||
| const std::vector<MemoryDescPtr>& dstDescs) const override; | ||
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| MVNExecutorPtr makeExecutor(const ExecutorContext::CPtr context) const override { | ||
| return std::make_shared<AclMVNExecutor>(context); | ||
| } | ||
| private: | ||
| MVNAttrs aclMVNAtrrs; | ||
| }; | ||
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| using ACLMVNExecutorPtr = std::shared_ptr<ACLMVNExecutor>; | ||
| } // namespace intel_cpu | ||
| } // namespace ov | ||
| } // namespace ov |
120 changes: 120 additions & 0 deletions
120
src/plugins/intel_cpu/src/nodes/executors/common/ref_mvn.cpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,120 @@ | ||
| // Copyright (C) 2023 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #include "ref_mvn.hpp" | ||
| #include "openvino/core/parallel.hpp" | ||
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| void ov::intel_cpu::CommonMVNExecutor::execute(const ov::intel_cpu::MemoryArgs &memory) { | ||
| mvn_ref(reinterpret_cast<uint8_t *>(memory.at(ARG_SRC_0)->getData()), | ||
| reinterpret_cast<uint8_t *>(memory.at(ARG_DST)->getData()), refMVNAttrs.shape5D); | ||
| } | ||
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| bool ov::intel_cpu::CommonMVNExecutor::update(const ov::intel_cpu::MemoryArgs &memory) { | ||
| return true; | ||
| } | ||
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| bool ov::intel_cpu::CommonMVNExecutor::supports(const ov::intel_cpu::MVNConfig& config) { | ||
| return true; | ||
| } | ||
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| void ov::intel_cpu::CommonMVNExecutor::mvn_ref(const uint8_t* src_data, uint8_t* dst_data, const VectorDims& shape5d) { | ||
| const float *src_data_ptr = reinterpret_cast<const float *>(src_data); | ||
| float *dst_data_ptr = reinterpret_cast<float *>(dst_data); | ||
| const size_t N = shape5d[0]; | ||
| const size_t C = shape5d[1]; | ||
| const size_t D = shape5d[2]; | ||
| const size_t H = shape5d[3]; | ||
| const size_t W = shape5d[4]; | ||
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| size_t C1 = H * W; | ||
| size_t C2 = C1 * D; | ||
| size_t C3 = C2 * C; | ||
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| parallel_for(N, [&](int b) { | ||
| size_t cb = b * C3; | ||
| if (refMVNAttrs.execAcrossChannels_) { | ||
| // Parallel sum for each channel for mean | ||
| float C3inv = 1.f / static_cast<float>(C3); | ||
| float mean_temp = 0.0f; | ||
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| mean_temp = parallel_sum(C, mean_temp, [&](size_t c)->float { | ||
| float mean_internal = 0.0f; | ||
| size_t cc = cb + c * C2; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| mean_internal += src_data_ptr[cc + sp]; | ||
| } | ||
| return mean_internal; | ||
| }); | ||
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| float mean = mean_temp * C3inv; | ||
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| if (refMVNAttrs.normalizeVariance_) { | ||
| // parallel sum for each channel for variance | ||
| float variance_temp = 0.0f; | ||
| variance_temp = parallel_sum(C, variance_temp, [&](size_t c)->float { | ||
| float variance_internal = 0.0f; | ||
| size_t cc = cb + c * C2; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| variance_internal += (src_data_ptr[cc + sp] - mean) * (src_data_ptr[cc + sp] - mean); | ||
| } | ||
| return variance_internal; | ||
| }); | ||
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| float variance = 1.f; | ||
| if (refMVNAttrs.epsMode_ == INSIDE_SQRT) | ||
| variance = 1.f / sqrtf(variance_temp * C3inv + refMVNAttrs.epsValue_); | ||
| else if (refMVNAttrs.epsMode_ == OUTSIDE_SQRT) | ||
| variance = 1.f / (sqrtf(variance_temp * C3inv) + refMVNAttrs.epsValue_); | ||
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| parallel_for(C, [&](int c) { | ||
| size_t cc = cb + c * C2; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| dst_data_ptr[cc + sp] = (src_data_ptr[cc + sp] - mean) * variance; | ||
| } | ||
| }); | ||
| } else { | ||
| parallel_for(C, [&](int c) { | ||
| size_t cc = cb + c * C2; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| dst_data_ptr[cc + sp] = src_data_ptr[cc + sp] - mean; | ||
| } | ||
| }); | ||
| } | ||
| } else { // per channel | ||
| float C2inv = 1.f / static_cast<float>(C2); | ||
| parallel_for(C, [&](size_t c) { | ||
| // mean for this channel | ||
| float mean = 0.f; | ||
| size_t cc = cb + c * C2; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| mean += src_data_ptr[cc + sp]; | ||
| } | ||
| mean *= C2inv; | ||
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| if (refMVNAttrs.normalizeVariance_) { | ||
| // variance for this channel | ||
| float variance = 0.f; | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| variance += (src_data_ptr[cc + sp] - mean) * (src_data_ptr[cc + sp] - mean); | ||
| } | ||
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| if (refMVNAttrs.epsMode_ == INSIDE_SQRT) | ||
| variance = 1.f / sqrtf(variance * C2inv + refMVNAttrs.epsValue_); | ||
| else if (refMVNAttrs.epsMode_ == OUTSIDE_SQRT) | ||
| variance = 1.f / (sqrtf(variance * C2inv) + refMVNAttrs.epsValue_); | ||
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| // mvn for this channel | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| dst_data_ptr[cc + sp] = (src_data_ptr[cc + sp] - mean) * variance; | ||
| } | ||
| } else { | ||
| // mvn for this channel | ||
| for (size_t sp = 0lu; sp < C2; sp++) { | ||
| dst_data_ptr[cc + sp] = src_data_ptr[cc + sp] - mean; | ||
| } | ||
| } | ||
| }); | ||
| } | ||
| }); | ||
| } |
37 changes: 37 additions & 0 deletions
37
src/plugins/intel_cpu/src/nodes/executors/common/ref_mvn.hpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| // Copyright (C) 2018-2022 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
| #pragma once | ||
|
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| #include <memory> | ||
| #include "cpu_memory.h" | ||
| #include "nodes/executors/mvn_config.hpp" | ||
|
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| namespace ov { | ||
| namespace intel_cpu { | ||
|
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| class CommonMVNExecutor : public Executor { | ||
| public: | ||
| CommonMVNExecutor(const MVNAttrs& attrs, | ||
| const PostOps& postOps, | ||
| const MemoryArgs& memory, | ||
| const ExecutorContext::CPtr context) : refMVNAttrs(attrs) {} | ||
|
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| void execute(const MemoryArgs& memory) override; | ||
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| impl_desc_type implType() const override { | ||
| return impl_desc_type::ref; | ||
| } | ||
|
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| // offloads execution data preparation from the exec call | ||
| bool update(const MemoryArgs& memory) override; | ||
|
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| static bool supports(const MVNConfig& config); | ||
|
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| private: | ||
| const MVNAttrs& refMVNAttrs; | ||
| void mvn_ref(const uint8_t *in_ptr_, uint8_t *out_ptr_, const VectorDims& shape5d); | ||
| }; | ||
|
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| } // namespace intel_cpu | ||
| } // namespace ov |
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