c++ - Why can't I add default-argument to my lambda function parameters (or is there an alternative way to do it)? - Sta

admin管理员组

文章数量:1405323

So I have a method with simple lambda functions I use to update my weights and I want to try different functions but I also want to have default parameter for the decay:

void ema_update(int i, const NetImpl& mdl, void (&updwp)(torch::Tensor& w, const torch::Tensor& w1, double decay = 0.999)  = [](torch::Tensor& w, const torch::Tensor& w1, double decay) {
    w.set_data(w.data().detach() * decay + w1.detach() * (1. - decay));
    }, void (&updw)(torch::Tensor& w, const torch::Tensor& w1, double decay = 0.999) = [](torch::Tensor& w, const torch::Tensor& w1, double decay) {
        w = w.detach() * decay;
        w += w1.detach() * (1. - decay);
        }) {
    updw(layers[i]vtr1->weight, mdl.layers[i]vtr1->weight);
    updw(layers[i]vtr2->weight, mdl.layers[i]vtr2->weight);
    updw(layers[i]vtr3->weight, mdl.layers[i]vtr3->weight);
    updw(layers[i].lin1->weight, mdl.layers[i].lin1->weight);
    updw(layers[i].lin2->weight, mdl.layers[i].lin2->weight);
    updw(layers[i].lin3->weight, mdl.layers[i].lin3->weight);

    updw(layers[i]v1->weight, mdl.layers[i]v1->weight);
    updw(layers[i]v2->weight, mdl.layers[i]v2->weight);
    updw(layers[i]v3->weight, mdl.layers[i]v3->weight);
    updw(layers[i]v4->weight, mdl.layers[i]v4->weight);
    updw(layers[i].rnnresh, mdl.layers[i].rnnresh);
    if (layers[i].mha->in_proj_weight.defined())
        updw(layers[i].mha->in_proj_weight, mdl.layers[i].mha->in_proj_weight);
    if (layers[i].mha->k_proj_weight.defined())
        updw(layers[i].mha->k_proj_weight, mdl.layers[i].mha->k_proj_weight);
    if (layers[i].mha->q_proj_weight.defined())
        updw(layers[i].mha->q_proj_weight, mdl.layers[i].mha->q_proj_weight);
    if (layers[i].mha->v_proj_weight.defined())
        updw(layers[i].mha->v_proj_weight, mdl.layers[i].mha->v_proj_weight);
    for (size_t pi = 0; pi < layers[i].trans->decoder.ptr()->parameters().size(); ++pi)
        updwp(layers[i].trans->decoder.ptr()->parameters()[pi], mdl.layers[i].trans->decoder.ptr()->parameters()[pi].data());//torch::nn::init::xavier_uniform_(p).cuda();
    for (size_t pi = 0; pi < layers[i].trans->encoder.ptr()->parameters().size(); ++pi)
        updwp(layers[i].trans->encoder.ptr()->parameters()[pi], mdl.layers[i].trans->encoder.ptr()->parameters()[pi].data());
    for (size_t pi = 0; pi < layers[i].rnn1->all_weights().size(); ++pi)
        updwp(layers[i].rnn1->all_weights()[pi], mdl.layers[i].rnn1->all_weights()[pi].data());
}

Here I specify all the layers I need to update and the small lambdas are default parameters - however I can't set default parameters on the function pointer prototypes for the decay.

MSVC says:

error C2383: 'updwp': default-arguments are not allowed on this symbol

It doesn't matter if I use reference or pointer to the function.

I'm open to alternative suggestions to make both lambdas and decay default parameters.

Also it was originally:

void ema_update(int i, const NetImpl& mdl, double decay = 0.999, void (&updwp)(torch::Tensor& w, const torch::Tensor& w1)  = [](torch::Tensor& w, const torch::Tensor& w1) {
    w.set_data(w.data().detach() * decay + w1.detach() * (1. - decay));
    }, void (&updw)(torch::Tensor& w, const torch::Tensor& w1) = [](torch::Tensor& w, const torch::Tensor& w1) {
        w = w.detach() * decay;
        w += w1.detach() * (1. - decay);
        }) 

But that doesn't work either.

Self contained example:

void f(void (*pf)(int &a, double b=0.77) = [] (int &a, double b){
     a *= b;
}) {
    int a = 9;
    pf(a);
}

void f1(double b=0.77, void (*pf)(int &a) = [] (int &a){
    a *= b;
}) {
    int a = 9;
    pf(a);
}

I also tried std functions:

#include <functional>



void f3(double b=0.77, std::function<void (double b, int &a)> fa = [] (double b, int &a){
     a *= b;
}) {
    int a = 9;
    std::function f = std::bind(fa, b);
    f(a);
}

So I have a method with simple lambda functions I use to update my weights and I want to try different functions but I also want to have default parameter for the decay:

void ema_update(int i, const NetImpl& mdl, void (&updwp)(torch::Tensor& w, const torch::Tensor& w1, double decay = 0.999)  = [](torch::Tensor& w, const torch::Tensor& w1, double decay) {
    w.set_data(w.data().detach() * decay + w1.detach() * (1. - decay));
    }, void (&updw)(torch::Tensor& w, const torch::Tensor& w1, double decay = 0.999) = [](torch::Tensor& w, const torch::Tensor& w1, double decay) {
        w = w.detach() * decay;
        w += w1.detach() * (1. - decay);
        }) {
    updw(layers[i].cnvtr1->weight, mdl.layers[i].cnvtr1->weight);
    updw(layers[i].cnvtr2->weight, mdl.layers[i].cnvtr2->weight);
    updw(layers[i].cnvtr3->weight, mdl.layers[i].cnvtr3->weight);
    updw(layers[i].lin1->weight, mdl.layers[i].lin1->weight);
    updw(layers[i].lin2->weight, mdl.layers[i].lin2->weight);
    updw(layers[i].lin3->weight, mdl.layers[i].lin3->weight);

    updw(layers[i].cnv1->weight, mdl.layers[i].cnv1->weight);
    updw(layers[i].cnv2->weight, mdl.layers[i].cnv2->weight);
    updw(layers[i].cnv3->weight, mdl.layers[i].cnv3->weight);
    updw(layers[i].cnv4->weight, mdl.layers[i].cnv4->weight);
    updw(layers[i].rnnresh, mdl.layers[i].rnnresh);
    if (layers[i].mha->in_proj_weight.defined())
        updw(layers[i].mha->in_proj_weight, mdl.layers[i].mha->in_proj_weight);
    if (layers[i].mha->k_proj_weight.defined())
        updw(layers[i].mha->k_proj_weight, mdl.layers[i].mha->k_proj_weight);
    if (layers[i].mha->q_proj_weight.defined())
        updw(layers[i].mha->q_proj_weight, mdl.layers[i].mha->q_proj_weight);
    if (layers[i].mha->v_proj_weight.defined())
        updw(layers[i].mha->v_proj_weight, mdl.layers[i].mha->v_proj_weight);
    for (size_t pi = 0; pi < layers[i].trans->decoder.ptr()->parameters().size(); ++pi)
        updwp(layers[i].trans->decoder.ptr()->parameters()[pi], mdl.layers[i].trans->decoder.ptr()->parameters()[pi].data());//torch::nn::init::xavier_uniform_(p).cuda();
    for (size_t pi = 0; pi < layers[i].trans->encoder.ptr()->parameters().size(); ++pi)
        updwp(layers[i].trans->encoder.ptr()->parameters()[pi], mdl.layers[i].trans->encoder.ptr()->parameters()[pi].data());
    for (size_t pi = 0; pi < layers[i].rnn1->all_weights().size(); ++pi)
        updwp(layers[i].rnn1->all_weights()[pi], mdl.layers[i].rnn1->all_weights()[pi].data());
}

Here I specify all the layers I need to update and the small lambdas are default parameters - however I can't set default parameters on the function pointer prototypes for the decay.

MSVC says:

error C2383: 'updwp': default-arguments are not allowed on this symbol

It doesn't matter if I use reference or pointer to the function.

I'm open to alternative suggestions to make both lambdas and decay default parameters.

Also it was originally:

void ema_update(int i, const NetImpl& mdl, double decay = 0.999, void (&updwp)(torch::Tensor& w, const torch::Tensor& w1)  = [](torch::Tensor& w, const torch::Tensor& w1) {
    w.set_data(w.data().detach() * decay + w1.detach() * (1. - decay));
    }, void (&updw)(torch::Tensor& w, const torch::Tensor& w1) = [](torch::Tensor& w, const torch::Tensor& w1) {
        w = w.detach() * decay;
        w += w1.detach() * (1. - decay);
        }) 

But that doesn't work either.

Self contained example:

void f(void (*pf)(int &a, double b=0.77) = [] (int &a, double b){
     a *= b;
}) {
    int a = 9;
    pf(a);
}

void f1(double b=0.77, void (*pf)(int &a) = [] (int &a){
    a *= b;
}) {
    int a = 9;
    pf(a);
}

https://wandbox./permlink/XmZtzsxmcwgUIbJy

I also tried std functions:

#include <functional>



void f3(double b=0.77, std::function<void (double b, int &a)> fa = [] (double b, int &a){
     a *= b;
}) {
    int a = 9;
    std::function f = std::bind(fa, b);
    f(a);
}

https://wandbox./permlink/Jvv3Dw2gSemkyaxt

• c++
• visual-c++
• methods
• lambda
• default-parameters

Share Improve this question Follow edited Mar 8 at 11:27 AnArrayOfFunctions asked Mar 8 at 11:08 AnArrayOfFunctionsAnArrayOfFunctions 3,78533 gold badges3535 silver badges7575 bronze badges 6

• 2 You can in C++20, but please don't, it's ridiculously unreadable. Use a free function if you must. – Passer By Commented Mar 8 at 11:38
• 1 Do you ever plan on calling the lambda with and without default parameters? Anyway better to make a struct with all the parameters in it and pass an instance of that. Would make the code a lot more readable too – Pepijn Kramer Commented Mar 8 at 11:40
• 1 Wait, ignore my previous comment. You mean you want the function pointer parameter to have default arguments? That's never intended, but you can wrap it like auto wrapped = [pf, b](int& a) { return pf(a, b); }; – Passer By Commented Mar 8 at 11:44
• @PasserBy Yes. Yeah that's the solution I've found - I was overcomplicating it :). – AnArrayOfFunctions Commented Mar 8 at 11:46
• @PepijnKramer No - I only call with the default parameter passed/or omitted by the caller. – AnArrayOfFunctions Commented Mar 8 at 11:53

 |  Show 1 more comment

1 Answer 1

Sorted by: Reset to default 0

I've found a solution - which is the simplest (maybe not the most elegant):

I need to pass by reference because in the original code a is not simple integer but an object with getter and setter I use inside the lambda.

#include <functional>

void f4(double b=0.77, std::function<void (double b, int &a)> fa= [] (double b, int &a){
     a *= b;
}) {
    int a = 9;
    auto f = [fa, b] (int &a) {fa(b, a);};
    f(a);
}

https://wandbox./permlink/uKwqe1reWwwEJAGC

本文标签：