mirror of https://github.com/alibaba/MNN.git
84 lines
2.8 KiB
C++
84 lines
2.8 KiB
C++
//
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// CPURandomUniform.cpp
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// MNN
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//
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// Created by MNN on 2020/8/14.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <random>
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#include "backend/cpu/CPURandomUniform.hpp"
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#include "core/Macro.h"
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#include "backend/cpu/CPUBackend.hpp"
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namespace MNN {
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ErrorCode CPURandomUniform::onResize(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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return NO_ERROR;
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}
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ErrorCode CPURandomUniform::onExecute(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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MNN_ASSERT(outputs.size() == 1);
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auto output = outputs[0];
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int size = output->elementSize();
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auto parameter = mOp->main_as_RandomUniform();
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auto outputPtr = output->host<float>();
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std::uniform_real_distribution<float> distribution(parameter->low(),parameter->high());
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int seed = parameter->seed();
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int seed1 = parameter->seed2();
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if (seed || seed1) {
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std::mt19937 generator(seed || seed1);
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for (int i = 0; i < size; i++) {
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outputPtr[i] = distribution(generator);
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}
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} else {
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std::default_random_engine generator;
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for (int i = 0; i < size; i++) {
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outputPtr[i] = distribution(generator);
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}
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}
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return NO_ERROR;
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}
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ErrorCode CPURandomNormal::onResize(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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return NO_ERROR;
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}
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ErrorCode CPURandomNormal::onExecute(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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MNN_ASSERT(outputs.size() == 1);
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auto output = outputs[0];
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int size = output->elementSize();
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auto parameter = mOp->main_as_RandomUniform();
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auto outputPtr = output->host<float>();
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// RandomUniform and RandomNormal use same param table. low -> mean, high -> scale
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std::normal_distribution<float> distribution(parameter->low(),parameter->high());
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int seed = parameter->seed();
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int seed1 = parameter->seed2();
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if (seed || seed1) {
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std::mt19937 generator(seed || seed1);
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for (int i = 0; i < size; i++) {
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outputPtr[i] = distribution(generator);
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}
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} else {
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std::default_random_engine generator;
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for (int i = 0; i < size; i++) {
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outputPtr[i] = distribution(generator);
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}
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}
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return NO_ERROR;
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}
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class CPURandomCreator : public CPUBackend::Creator {
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public:
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virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
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const MNN::Op *op, Backend *backend) const override {
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if (op->type() == OpType_RandomUniform) {
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return new CPURandomUniform(backend, op);
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} else {
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return new CPURandomNormal(backend, op);
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}
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}
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};
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REGISTER_CPU_OP_CREATOR(CPURandomCreator, OpType_RandomUniform);
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REGISTER_CPU_OP_CREATOR(CPURandomCreator, OpType_RandomNormal);
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} // namespace MNN
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