使用 shared_ptr 在类及其成员对象之间共享变量是一个很好的解决方案吗？

Question

I did this for share the learning_rate between all my neurons :

class neural_network {
public:
  neural_network(float learning_rate = 0.005f)
      : learning_rate(new float(learning_rate)){};
  shared_ptr<float> learning_rate;

private:
  vector<neuron> neurons;
};

class neuron {
public:
  neuron(const float learning_rate) {
    this->learningRate = make_shared<float>(learningRate);
  };

private:
  const shared_ptr<const float> learning_rate;
};

Is this a good solution to have same learning_rate on all my neurons?

Answer 1

shared_ptr is reasonably expensive, I don't see the need for it here, only the network needs to "own" the learning rate. Don't be afraid to use raw pointers where appropriate, just avoid new and delete :

class neuron {
public:
    neuron(const float& learning_rate)
        : learning_rate(&learning_rate){};

private:
    const float* learning_rate;
};

class neural_network {
public:
    neural_network(float learning_rate = 0.005f)
        : learning_rate(learning_rate){};
    float learning_rate;

    void make_neuron()
    {
        neurons.push_back(neuron(learning_rate));
    }

private:
    vector<neuron> neurons;
};

Answer 2

shared_ptr is to share ownership, not to "share an instance".

There is a well defined relation between lifetime of some instance X and its members. In the easiest case the members will be alive till they are destroyed in X s destructor. Members typically do not stay alive beyond the lifetime of X . Hence, there is no need for shared ownership. You could use raw pointers to emphasize that the neurons do not participate in the ownership of learning_rate .

class neural_network
{
public:
    neural_network(float learning_rate = 0.005f)
        : learning_rate(learnin_rate) {};
    float learning_rate;
private:
    vector<neuron> neurons;
}

class neuron
{
public:
    neuron(const float* learning_rate) : learning_rate(learning_rate){}
private:
    const float* learning_rate;
}

PS: Not sure, but I think I would apply a rather different design. Make learning_rate a (non-const non-pointer) member of neurons . Then if the neural_network changes the learning_rate it would call the neurons set_learning_rate method to update their learning rate. In this way neuron s have a chance to react when the learning rate changes.

Answer 3

For a single float , I really think all this is overkill. If your learning rate could grow more complex, that's one thing, but in the code given here? I suggest just going with a float member in neural_network , and a const neural_network* owner; in neuron set during construction.

Then you slap a public getLearningRate() on neural_network and you're done. And you might have all sorts of network-wide state to track, so the individual neurons can get a lot of utility out of that one pointer. Examples might be logs, a serialization stream, or maybe a dirty flag.

Bonus: No dynamic allocations, which is always a nice efficiency gain when you can get it. No pointer-related cache misses, no new ing or delete ing.

Furthermore, I'd think your call to make_shared() in neuron 's constructor will create a new shared pointer, pointing to a new instance of that same float value. This results in changes to the root learning_rate not affecting the existing neuron instances at all. (and a lot of extra, unwanted memory allocation)