mirror of https://github.com/alibaba/MNN.git
74 lines
2.4 KiB
C++
74 lines
2.4 KiB
C++
//
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// CPULayerNorm.cpp
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// MNN
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//
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// Created by MNN on 2020/07/15.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <cmath>
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#include "backend/cpu/CPUDynamicQuant.hpp"
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#include "backend/cpu/CPUBackend.hpp"
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#include "backend/cpu/compute/CommonOptFunction.h"
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#include "backend/cpu/compute/Int8FunctionsOpt.h"
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#include "core/Execution.hpp"
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#include "core/Concurrency.h"
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#include "core/OpCommonUtils.hpp"
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#include "MNN_generated.h"
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namespace MNN {
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CPUDynamicQuant::CPUDynamicQuant(const MNN::Op* op, Backend* backend) : Execution(backend) {
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}
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ErrorCode CPUDynamicQuant::onResize(const std::vector<Tensor*> &inputs,
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const std::vector<Tensor*> &outputs) {
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return NO_ERROR;
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}
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ErrorCode CPUDynamicQuant::onExecute(const std::vector<Tensor*> &inputs,
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const std::vector<Tensor*> &outputs) {
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auto core = static_cast<CPUBackend*>(backend())->functions();
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auto int8core = static_cast<CPUBackend*>(backend())->int8Functions();
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float *inputPtr = inputs[0]->host<float>();
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int8_t *outputPtr = outputs[0]->host<int8_t>();
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int size = static_cast<CPUBackend*>(backend())->getTensorSize(inputs[0]);
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float quantScale = 0.f, dequantScale = 0.f, zeroPoint = 0.f;
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float maxVal = 0.f, minVal = 0.f;
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core->MNNCountMaxMinValue(inputPtr, &minVal, &maxVal, size);
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// Compute scale and zero
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float range = maxVal - minVal;
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MNN_ASSERT(range != 0);
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quantScale = 255.0f / range;
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dequantScale = range / 255.0f;
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zeroPoint = std::min(255.f, std::max(roundf(-(minVal * 255.f) / range), 0.f)) - 128.0f;
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int pack = core->pack;
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std::vector<float> qsVec(pack, quantScale);
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int sizeDiv = UP_DIV(size, pack);
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int8core->MNNFloat2Int8(inputPtr, outputPtr, sizeDiv, &quantScale, -128, 127, &zeroPoint, 0);
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float* scale = outputs[1]->host<float>();
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float* zeros = outputs[2]->host<float>();
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*scale = dequantScale;
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*zeros = zeroPoint;
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return NO_ERROR;
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}
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CPUDynamicQuant::~CPUDynamicQuant() {
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}
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class CPUDynamicQuantCreator : public CPUBackend::Creator {
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public:
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Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs, const MNN::Op* op, Backend* backend) const override {
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return new CPUDynamicQuant(op, backend);
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}
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};
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REGISTER_CPU_OP_CREATOR(CPUDynamicQuantCreator, OpType_DynamicQuant);
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} // namespace MNN
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