Using lambda instead of a function object, bad performance - c++

My problem is pretty simple, i want to use lambda's in the same way i may use a functor as a 'comparator', let me explain a little better. I have two big structs, both of them have their own implementation of operator<, and i have also a useless class (this is just the name of the class in the context of this question) which use the two struct, everything looks like this:
struct be_less
{
//A lot of stuff
int val;
be_less(int p_v):val(p_v){}
bool operator<(const be_less& p_other) const
{
return val < p_other.val;
}
};
struct be_more
{
//A lot of stuff
int val;
be_more(int p_v):val(p_v){}
bool operator<(const be_more& p_other) const
{
return val > p_other.val;
}
};
class useless
{
priority_queue<be_less> less_q;
priority_queue<be_more> more_q;
public:
useless(const vector<int>& p_data)
{
for(auto elem:p_data)
{
less_q.emplace(elem);
more_q.emplace(elem);
}
}
};
I whould like to remove the duplication in the two struct's, the simpliest idea is to make the struct a template and provide two functor to do the comparison job:
template<typename Comp>
struct be_all
{
//Lot of stuff, better do not duplicate
int val;
be_all(int p_v):val{p_v}{}
bool operator<(const be_all<Comp>& p_other) const
{
return Comp()(val,p_other.val);
}
};
class comp_less
{
public:
bool operator()(int p_first,
int p_second)
{
return p_first < p_second;
}
};
class comp_more
{
public:
bool operator()(int p_first,
int p_second)
{
return p_first > p_second;
}
};
typedef be_all<comp_less> all_less;
typedef be_all<comp_more> all_more;
class useless
{
priority_queue<all_less> less_q;
priority_queue<all_more> more_q;
public:
useless(const vector<int>& p_data)
{
for(auto elem:p_data)
{
less_q.emplace(elem);
more_q.emplace(elem);
}
}
};
This work pretty well, now for sure i dont have any duplication in the struct code at the price of two additional function object. Please note that i'm very simplifying the implementation of operator<, the hipotetic real code does much more than just comparing two ints.
Then i was thinking about how to do the same thing using lambda (Just as an experiment).The only working solution i was able to implement is:
template<typename Comp>
struct be_all
{
int val;
function<bool(int,int)> Comparator;
be_all(Comp p_comp,int p_v):
Comparator(move(p_comp)),
val{p_v}
{}
bool operator<(const be_all& p_other) const
{
return Comparator(val, p_other.val);
}
};
auto be_less = [](int p_first,
int p_second)
{
return p_first < p_second;
};
auto be_more = [](int p_first,
int p_second)
{
return p_first > p_second;
};
typedef be_all<decltype(be_less)> all_less;
typedef be_all<decltype(be_more)> all_more;
class useless
{
priority_queue<all_less> less_q;
priority_queue<all_more> more_q;
public:
useless(const vector<int>& p_data)
{
for(auto elem:p_data)
{
less_q.emplace(be_less,elem);
more_q.emplace(be_more,elem);
}
}
};
This implementation not only add a new member to the data containing struct, but have also a very poor performance, i prepared a small test in which i create one instance for all the useless class i've show you here, every time i feed the constructor with a vector full of 2 milion integers, the results are the following:
Takes 48ms to execute the constructor of the first useless class
Takes 228ms to create the second useless class (functor)
Takes 557ms to create the third useless class (lambdas)
Clearly the price i pay for the removed duplication is very high, and in the original code the duplication is still there. Please note how bad is the performance of the third implementation, ten times slower that the original one, i believed that the reason of the third implementation being slower than the second was because of the additional parameter in the constructor of be_all... but:
Actually there's also a fourth case, where i still used the lambda but i get rid of the Comparator member and of the additional parameter in be_all, the code is the following:
template<typename Comp>
struct be_all
{
int val;
be_all(int p_v):val{p_v}
{}
bool operator<(const be_all& p_other) const
{
return Comp(val, p_other.val);
}
};
bool be_less = [](int p_first,
int p_second)
{
return p_first < p_second;
};
bool be_more = [](int p_first,
int p_second)
{
return p_first > p_second;
};
typedef be_all<decltype(be_less)> all_less;
typedef be_all<decltype(be_more)> all_more;
class useless
{
priority_queue<all_less> less_q;
priority_queue<all_more> more_q;
public:
useless(const vector<int>& p_data)
{
for(auto elem:p_data)
{
less_q.emplace(elem);
more_q.emplace(elem);
}
}
};
If i remove auto from the lambda and use bool instead the code build even if i use Comp(val, p_other.val) in operator<.
What's very strange to me is that this fourth implementation (lambda without the Comparator member) is even slower than the other, at the end the average performance i was able to register are the following:
48ms
228ms
557ms
698ms
Why the functor are so much faster than lambdas in this scenario? I was expecting lambda's to be at least performing good as the ordinary functor, can someone of you comment please? And is there any technial reason why the fourth implementation is slower than the third?
PS:
The compilator i'm using is g++4.8.2 with -O3. In my test i create for each useless class an instance and using chrono i take account of the required time:
namespace benchmark
{
template<typename T>
long run()
{
auto start=chrono::high_resolution_clock::now();
T t(data::plenty_of_data);
auto stop=chrono::high_resolution_clock::now();
return chrono::duration_cast<chrono::milliseconds>(stop-start).count();
}
}
and:
cout<<"Bad code: "<<benchmark::run<bad_code::useless>()<<"ms\n";
cout<<"Bad code2: "<<benchmark::run<bad_code2::useless>()<<"ms\n";
cout<<"Bad code3: "<<benchmark::run<bad_code3::useless>()<<"ms\n";
cout<<"Bad code4: "<<benchmark::run<bad_code4::useless>()<<"ms\n";
The set of input integers is the same for all, plenty_of_data is a vector full of 2 million intergers.
Thanks for your time

You are not comparing the runtime of a lambda and a functor. Instead, the numbers indicate the difference in using a functor and an std::function. And std::function<R(Args...)>, for example, can store any Callable satisfying the signature R(Args...). It does this through type-erasure. So, the difference you see comes from the overhead of a virtual call in std::function::operator().
For example, the libc++ implementation(3.5) has a base class template<class _Fp, class _Alloc, class _Rp, class ..._ArgTypes> __base with a virtual operator(). std::function stores a __base<...>*. Whenever you create an std::function with a callable F, an object of type template<class F, class _Alloc, class R, class ...Args> class __func is created, which inherits from __base<...> and overrides the virtual operator().

Related

Using std::unique_ptr of a polymorphic class as key in std::unordered_map

My problem comes from a project that I'm supposed to finish. I have to create an std::unordered_map<T, unsigned int> where T is a pointer to a base, polymorphic class. After a while, I figured that it will also be a good practice to use an std::unique_ptr<T> as a key, since my map is meant to own the objects. Let me introduce some backstory:
Consider class hierarchy with polymorphic sell_obj as a base class. book and table inheriting from that class. We now know that we need to create a std::unordered_map<std::unique_ptr<sell_obj*>, unsigned int>. Therefore, erasing a pair from that map will automatically free the memory pointed by key. The whole idea is to have keys pointing to books/tables and value of those keys will represent the amount of that product that our shop contains.
As we are dealing with std::unordered_map, we should specify hashes for all three classes. To simplify things, I specified them in main like this:
namespace std{
template <> struct hash<book>{
size_t operator()(const book& b) const
{
return 1; // simplified
}
};
template <> struct hash<table>{
size_t operator()(const table& b) const
{
return 2; // simplified
}
};
// The standard provides a specilization so that std::hash<unique_ptr<T>> is the same as std::hash<T*>.
template <> struct hash<sell_obj*>{
size_t operator()(const sell_obj *s) const
{
const book *b_p = dynamic_cast<const book*>(s);
if(b_p != nullptr) return std::hash<book>()(*b_p);
else{
const table *t_p = static_cast<const table*>(s);
return std::hash<table>()(*t_p);
}
}
};
}
Now let's look at implementation of the map. We have a class called Shop which looks like this:
#include "sell_obj.h"
#include "book.h"
#include "table.h"
#include <unordered_map>
#include <memory>
class Shop
{
public:
Shop();
void add_sell_obj(sell_obj&);
void remove_sell_obj(sell_obj&);
private:
std::unordered_map<std::unique_ptr<sell_obj>, unsigned int> storeroom;
};
and implementation of two, crucial functions:
void Shop::add_sell_obj(sell_obj& s_o)
{
std::unique_ptr<sell_obj> n_ptr(&s_o);
storeroom[std::move(n_ptr)]++;
}
void Shop::remove_sell_obj(sell_obj& s_o)
{
std::unique_ptr<sell_obj> n_ptr(&s_o);
auto target = storeroom.find(std::move(n_ptr));
if(target != storeroom.end() && target->second > 0) target->second--;
}
in my main I try to run the following code:
int main()
{
book *b1 = new book("foo", "bar", 10);
sell_obj *ptr = b1;
Shop S_H;
S_H.add_sell_obj(*ptr); // works fine I guess
S_H.remove_sell_obj(*ptr); // usually (not always) crashes [SIGSEGV]
return 0;
}
my question is - where does my logic fail? I heard that it's fine to use std::unique_ptr in STL containters since C++11. What's causing the crash? Debugger does not provide any information besides the crash occurance.
If more information about the project will be needed, please point it out. Thank you for reading
There are quite a few problems with logic in the question. First of all:
Consider class hierarchy with polymorphic sell_obj as base class. book and table inheriting from that class. We now know that we need to create a std::unordered_map<std::unique_ptr<sell_obj*>, unsigned int>.
In such cases std::unique_ptr<sell_obj*> is not what we would want. We would want std::unique_ptr<sell_obj>. Without the *. std::unique_ptr is already "a pointer".
As we are dealing with std::unordered_map, we should specify hashes for all three classes. To simplify things, I specified them in main like this: [...]
This is also quite of an undesired approach. This would require changing that part of the code every time we add another subclass in the hierarchy. It would be best to delegate the hashing (and comparing) polymorphically to avoid such problems, exactly as #1201programalarm suggested.
[...] implementation of two, crucial functions:
void Shop::add_sell_obj(sell_obj& s_o)
{
std::unique_ptr<sell_obj> n_ptr(&s_o);
storeroom[std::move(n_ptr)]++;
}
void Shop::remove_sell_obj(sell_obj& s_o)
{
std::unique_ptr<sell_obj> n_ptr(&s_o);
auto target = storeroom.find(std::move(n_ptr));
if(target != storeroom.end() && target->second > 0) target->second--;
}
This is wrong for couple of reasons. First of all, taking an argument by non-const reference suggest modification of the object. Second of all, the creation of n_ptr from a pointer obtained by using & on an argumnet is incredibly risky. It assumes that the object is allocated on the heap and it is unowned. A situation that generally should not take place and is incredibly dangerous. In case where the passed object is on the stack and / or is already managed by some other owner, this is a recipe for a disaster (like a segfault).
What's more, it is more or less guaranteed to end up in a disaster, since both add_sell_obj() and remove_sell_obj() create std::unique_ptrs to potentially the same object. This is exactly the case from the original question's main(). Two std::unique_ptrs pointing to the same object result in double delete.
While it's not necessarily the best approach for this problem if one uses C++ (as compared to Java), there are couple of interesting tools that can be used for this task. The code below assumes C++20.
The class hierarchy
First of all, we need a base class that will be used when referring to all the objects stored in the shop:
struct sell_object { };
And then we need to introduce classes that will represent conrete objects:
class book : public sell_object {
std::string title;
public:
book(std::string title) : title(std::move(title)) { }
};
class table : public sell_object {
int number_of_legs = 0;
public:
table(int number_of_legs) : number_of_legs(number_of_legs) { }
};
For simplicity (but to still have some distinctions) I chose for them to have just one, distinct field (title and number_of_legs).
The storage
The shop class that will represent storage for any sell_object needs to somehow store, well, any sell_object. For that we either need to use pointers or references to the base class. You can't have a container of references, so it's best to use pointers. Smart pointers.
Originally the question suggested the usage of std::unordered_map. Let us stick with it:
class shop {
std::unordered_map<
std::unique_ptr<sell_object>, int,
> storage;
public:
auto add(...) -> void {
...
}
auto remove(...) -> void {
...
}
};
It is worth mentioning that we chose std::unique_ptr as key for our map. That means that the storage is going to copy the passed objects and use the copies it owns to compare with elements we query (add or remove). No more than one equal object will be copied, though.
The fixed version of storage
There is a problem, however. std::unordered_map uses hashing and we need to provide a hash strategy for std::unique_ptr<sell_object>. Well, there already is one and it uses the hash strategy for T*. The problem is that we want to have custom hashing. Those particular std::unique_ptr<sell_object>s should be hashed according to the associated sell_objects.
Because of this, I opt to choose a different approach than the one proposed in the question. Instead of providing a global specialization in the std namespace, I will choose a custom hashing object and a custom comparator:
class shop {
struct sell_object_hash {
auto operator()(std::unique_ptr<sell_object> const& object) const -> std::size_t {
return object->hash();
}
};
struct sell_object_equal {
auto operator()(
std::unique_ptr<sell_object> const& lhs,
std::unique_ptr<sell_object> const& rhs
) const -> bool {
return (*lhs <=> *rhs) == 0;
}
};
std::unordered_map<
std::unique_ptr<sell_object>, int,
sell_object_hash, sell_object_equal
> storage;
public:
auto add(...) -> void {
...
}
auto remove(...) -> void {
...
}
};
Notice a few things. First of all, the type of storage has changed. No longer it is an std::unordered_map<std::unique_ptr<T>, int>, but an std::unordered_map<std::unique_ptr<T>, int, sell_object_hash, sell_object_equal>. This is to indicate that we are using custom hasher (sell_object_hash) and custom comparator (sell_object_equal).
The lines we need to pay extra attention are:
return object->hash();
return (*lhs <=> *rhs) == 0;
Onto them:
return object->hash();
This is a delegation of hashing. Instead of being an observer and trying to have a type that for each and every possible type derived from sell_object implements a different hashing, we require that those objects supply the sufficient hashing themselves. In the original question, the std::hash specialization was the said "observer". It certainly did not scale as a solution.
In order to achieve the aforementioned, we modify the base class to impose the listed requirement:
struct sell_object {
virtual auto hash() const -> std::size_t = 0;
};
Thus we also need to change our book and table classes:
class book : public sell_object {
std::string title;
public:
book(std::string title) : title(std::move(title)) { }
auto hash() const -> std::size_t override {
return std::hash<std::string>()(title);
}
};
class table : public sell_object {
int number_of_legs = 0;
public:
table(int number_of_legs) : number_of_legs(number_of_legs) { }
auto hash() const -> std::size_t override {
return std::hash<int>()(number_of_legs);
}
};
return (*lhs <=> *rhs) == 0;
This is a C++20 feature called the three-way comparison operator, sometimes called the spaceship operator. I opted into using it, since starting with C++20, most types that desire to be comparable will be using this operator. That means we also need our concrete classes to implement it. What's more, we need to be able to call it with base references (sell_object&). Yet another virtual function (operator, actually) needs to be added to the base class:
struct sell_object {
virtual auto hash() const -> std::size_t = 0;
virtual auto operator<=>(sell_object const&) const -> std::partial_ordering = 0;
};
Every subclass of sell_object is going to be required to be comparable with other sell_objects. The main reason is that we need to compare sell_objects in our storage map. For completeness, I used std::partial_ordering, since we require every sell_object to be comparable with every other sell_object. While comparing two books or two tables yields strong ordering (total ordering where two equivalent objects are indistinguishable), we also - by design - need to support comparing a book to a table. This is somewhat meaningless (always returns false). Fortunately, C++20 helps us here with std::partial_ordering::unordered. Those elements are not equal and neither of them is greater or less than the other. Perfect for such scenarios.
Our concrete classes need to change accordingly:
class book : public sell_object {
std::string title;
public:
book(std::string title) : title(std::move(title)) { }
auto hash() const -> std::size_t override {
return std::hash<std::string>()(title);
}
auto operator<=>(book const& other) const {
return title <=> other.title;
};
auto operator<=>(sell_object const& other) const -> std::partial_ordering override {
if (auto book_ptr = dynamic_cast<book const*>(&other)) {
return *this <=> *book_ptr;
} else {
return std::partial_ordering::unordered;
}
}
};
class table : public sell_object {
int number_of_legs = 0;
public:
table(int number_of_legs) : number_of_legs(number_of_legs) { }
auto hash() const -> std::size_t override {
return std::hash<int>()(number_of_legs);
}
auto operator<=>(table const& other) const {
return number_of_legs <=> other.number_of_legs;
};
auto operator<=>(sell_object const& other) const -> std::partial_ordering override {
if (auto table_ptr = dynamic_cast<table const*>(&other)) {
return *this <=> *table_ptr;
} else {
return std::partial_ordering::unordered;
}
}
};
The overriden operator<=>s are required due to the base class' requirements. They are quite simple - if the other object (the one we are comparing this object to) is of the same type, we delegate to the <=> version that uses the concrete type. If not, we have a type mismatch and we report the unordered ordering.
For those of you who are curious why the <=> implementation that compares two, identical types is not = defaulted: it would use the base-class comparison first, which would delegate to the sell_object version. That would dynamic_cast again and delegate to the defaulted implementation. Which would compare the base class and... result in an infinite recursion.
add() and remove() implementation
Everything seems great, so we can move on to adding and removing items to and from our shop. However, we immediately arrive at a hard design decision. What arguments should add() and remove() accept?
std::unique_ptr<sell_object>? That would make their implementation trivial, but it would require the user to construct a potentially useless, dynamically allocated object just to call a function.
sell_object const&? That seems correct, but there are two problems with it: 1) we would still need to construct an std::unique_ptr with a copy of passed argument to find the appropriate element to remove; 2) we wouldn't be able to correctly implement add(), since we need the concrete type to construct an actual std::unique_ptr to put into our map.
Let us go with the second option and fix the first problem. We certainly do not want to construct a useless and expensive object just to look for it in the storage map. Ideally we would like to find a key (std::unique_ptr<sell_object>) that matches the passed object. Fortunately, transparent hashers and comparators come to the rescue.
By supplying additional overloads for hasher and comparator (and providing a public is_transparent alias), we allow for looking for a key that is equivalent, without needing the types to match:
struct sell_object_hash {
auto operator()(std::unique_ptr<sell_object> const& object) const -> std::size_t {
return object->hash();
}
auto operator()(sell_object const& object) const -> std::size_t {
return object.hash();
}
using is_transparent = void;
};
struct sell_object_equal {
auto operator()(
std::unique_ptr<sell_object> const& lhs,
std::unique_ptr<sell_object> const& rhs
) const -> bool {
return (*lhs <=> *rhs) == 0;
}
auto operator()(
sell_object const& lhs,
std::unique_ptr<sell_object> const& rhs
) const -> bool {
return (lhs <=> *rhs) == 0;
}
auto operator()(
std::unique_ptr<sell_object> const& lhs,
sell_object const& rhs
) const -> bool {
return (*lhs <=> rhs) == 0;
}
using is_transparent = void;
};
Thanks to that, we can now implement shop::remove() like so:
auto remove(sell_object const& to_remove) -> void {
if (auto it = storage.find(to_remove); it != storage.end()) {
it->second--;
if (it->second == 0) {
storage.erase(it);
}
}
}
Since our comparator and hasher are transparent, we can find() an element that is equivalent to the argument. If we find it, we decrement the corresponding count. If it reaches 0, we remove the entry completely.
Great, onto the second problem. Let us list the requirements for the shop::add():
we need the concrete type of the object (merely a reference to the base class is not enough, since we need to create matching std::unique_ptr).
we need that type to be derived from sell_object.
We can achieve both with a constrained* template:
template <std::derived_from<sell_object> T>
auto add(T const& to_add) -> void {
if (auto it = storage.find(to_add); it != storage.end()) {
it->second++;
} else {
storage[std::make_unique<T>(to_add)] = 1;
}
}
This is, again, quite simple
*References: {1} {2}
Correct destruction semantics
There is only one more thing that separates us from the correct implementation. It's the fact that if we have a pointer (either smart or not) to a base class that is used to deallocate it, the destructor needs to be virtual.
This leads us to the final version of the sell_object class:
struct sell_object {
virtual auto hash() const -> std::size_t = 0;
virtual auto operator<=>(sell_object const&) const -> std::partial_ordering = 0;
virtual ~sell_object() = default;
};
See full implementation with example and additional printing utilities.

Create library to override operator*() of iterator - risk dangling pointer

I am trying to create my own boost::adaptors::transformed.
Here is the related boost code.
Here is its usage (modified from a SO answer by LogicStuff):-
C funcPointer(B& b){
//"funcPointer" is function convert from "B" to "C"
return instance-of-C
}
MyArray<B> test; //<-- any type, must already have begin() & end()
for(C c : test | boost::adaptor::transformed(funcPointer)) {
//... something ....
}
The result will be the same as :-
for(auto b : test) {
C c = funcPointer(b);
//... something ...
}
My Attempt
I created CollectAdapter that aim to work like boost::adaptor::transformed.
It works OK in most common cases.
Here is the full demo and back up. (same as below code)
The problematic part is CollectAdapter - the core of my library.
I don't know whether I should cache the collection_ by-pointer or by-value.
CollectAdapter encapsulates underlying collection_ (e.g. pointer to std::vector<>) :-
template<class COLLECTION,class ADAPTER>class CollectAdapter{
using CollectAdapterT=CollectAdapter<COLLECTION,ADAPTER>;
COLLECTION* collection_; //<---- #1 problem? should cache by value?
ADAPTER adapter_; //<---- = func1 (or func2)
public: CollectAdapter(COLLECTION& collection,ADAPTER adapter){
collection_=&collection;
adapter_=adapter;
}
public: auto begin(){
return IteratorAdapter<
decltype(std::declval<COLLECTION>().begin()),
decltype(adapter_)>
(collection_->begin(),adapter_);
}
public: auto end(){ ..... }
};
IteratorAdapter (used above) encapsulates underlying iterator, change behavior of operator* :-
template<class ITERATORT,class ADAPTER>class IteratorAdapter : public ITERATORT {
ADAPTER adapter_;
public: IteratorAdapter(ITERATORT underlying,ADAPTER adapter) :
ITERATORT(underlying),
adapter_(adapter)
{ }
public: auto operator*(){
return adapter_(ITERATORT::operator*());
}
};
CollectAdapterWidget (used below) is just a helper class to construct CollectAdapter-instance.
It can be used like:-
int func1(int i){ return i+10; }
int main(){
std::vector<int> test; test.push_back(5);
for(auto b:CollectAdapterWidget::createAdapter(test,func1)){
//^ create "CollectAdapter<std::vector<int>,func1>" instance
//here, b=5+10=15
}
}
Problem
The above code works OK in most cases, except when COLLECTION is a temporary object.
More specifically, dangling pointer potentially occurs when I create adapter of adapter of adapter ....
int func1(int i){ return i+10; }
int func2(int i){ return i+100; }
template<class T> auto utilityAdapter(const T& t){
auto adapter1=CollectAdapterWidget::createAdapter(t,func1);
auto adapter12=CollectAdapterWidget::createAdapter(adapter1,func2);
//"adapter12.collection_" point to "adapter1"
return adapter12;
//end of scope, "adapter1" is deleted
//"adapter12.collection_" will be dangling pointer
}
int main(){
std::vector<int> test;
test.push_back(5);
for(auto b:utilityAdapter(test)){
std::cout<< b<<std::endl; //should 5+10+100 = 115
}
}
This will cause run time error. Here is the dangling-pointer demo.
In the real usage, if the interface is more awesome, e.g. use | operator, the bug will be even harder to be detected :-
//inside "utilityAdapter(t)"
return t|func1; //OK!
return t|func1|func2; //dangling pointer
Question
How to improve my library to fix this error while keeping performance & robustness & maintainablilty near the same level?
In other words, how to cache data or pointer of COLLECTION (that can be adapter or real data-structure) elegantly?
Alternatively, if it is easier to answer by coding from scratch (than modifying my code), go for it. :)
My workarounds
The current code caches by pointer.
The main idea of workarounds is to cache by value instead.
Workaround 1 (always "by value")
Let adapter cache the value of COLLECTION.
Here is the main change:-
COLLECTION collection_; //<------ #1
//changed from .... COLLECTION* collection_;
Disadvantage:-
Whole data-structure (e.g. std::vector) will be value-copied - waste resource.
(when use for std::vector directly)
Workaround 2 (two versions of library, best?)
I will create 2 versions of the library - AdapterValue and AdapterPointer.
I have to create related classes (Widget,AdapterIterator,etc.) as well.
AdapterValue - by value. (designed for utilityAdapter())
AdapterPointer - by pointer. (designed for std::vector)
Disadvantage:-
Duplicate code a lot = low maintainability
Users (coders) have to be very conscious about which one to pick = low robustness
Workaround 3 (detect type)
I may use template specialization that do this :-
If( COLLECTION is an "CollectAdapter" ){ by value }
Else{ by pointer }
Disadvantage:-
Not cooperate well between many adapter classes.
They have to recognize each other : recognized = should cache by value.
Sorry for very long post.
I personally would go with template specialisation – however, not specialise the original template, but a nested class instead:
template<typename Collection, typename Adapter>
class CollectAdapter
{
template<typename C>
class ObjectKeeper // find some better name yourself...
{
C* object;
public:
C* operator*() { return object; };
C* operator->() { return object; };
};
template<typename C, typename A>
class ObjectKeeper <CollectAdapter<C, A>>
{
CollectAdapter<C, A> object;
public:
CollectAdapter<C, A>* operator*() { return &object; };
CollectAdapter<C, A>* operator->() { return &object; };
};
ObjectKeeper<Collection> keeper;
// now use *keeper or keeper-> wherever needed
};
The outer class then covers both cases by just always using pointers while the nested class hides the differences away.
Sure, incomplete (you yet need to add appropriate constructors, for instance, both to outer and inner class), but it should give you the idea...
You might even allow the user to select if she/he wants to copy:
template<typename Collection, typename Adapter, bool IsAlwaysCopy = false>
class CollectAdapter
{
template<typename C, bool IsCopy>
class ObjectWrapper // find some better name yourself...
{
C* object;
public:
C* operator*() { return object; };
C* operator->() { return object; };
};
template<typename C>
class ObjectWrapper<C, true>
{
C object;
public:
C* operator*() { return &object; };
C* operator->() { return &object; };
};
// avoiding code duplication...
template<typename C, bool IsCopy>
class ObjectKeeper : public ObjectWrapper<C, IsCopy>
{ };
template<typename C, typename A, bool IsCopy>
class ObjectKeeper <CollectAdapter<C, A>, IsCopy>
: public ObjectWrapper<CollectAdapter<C, A>, true>
{ };
ObjectKeeper<Collection> keeper;
};
In my indexed_view I store the value of the collection if it is an rvalue, and store a reference if it is an lvalue. You could do the same here: overload your operator| for both rvalues and lvalues.
template<typename Collection,typename Filter>
auto operator|(Collection&& collection,Filter filter){
return create_adapter_for_rvalue_collection(collection,filter);
}
template<typename Collection,typename Filter>
auto operator|(Collection const& collection,Filter filter){
return create_adapter_for_const_lvalue_collection(collection,filter);
}
template<typename Collection,typename Filter>
auto operator|(Collection & collection,Filter filter){
return create_adapter_for_non_const_lvalue_collection(collection,filter);
}

How to implement a lambda function for a sort algorithm involving object members, indirection, and casting?

I'm working on some code and I have a section where I do a one off sort function. To implement it I decided it was easiest to overload the operator< function. What I would prefer to do is move the implementation of the sort closer to the actual call by using some sort of boost::bind, boost::phoenix, lambda or some other type of implementation. Unfortunately I don't have access to new C++11 functionality. Below is some example code.
// In a header
struct foo
{
char * a;
char * c_str() { return a; }
}
// In a header
struct bar
{
foo * X;
bar(foo * _X) : X(_X) {}
bool operator < (const bar& rhs) const
{
return std::string(X->c_str()) < std::string(rhs.X->c_str());
}
};
struct bars : public std::vector<bar> { ... some stuff };
// Some other header
bars Bs;
// A cpp file
... other stuff happens that fills the Xs vector with objects
...::Function()
{
// Current use and it works fine
std::sort(Bs.begin(), Bs.end())
// Would like something that accomplishes this:
// std::sort(Bs.begin(), Bs.end(),
// std::string(lhs.X->c_str()) < std::string(rhs.X->c_str()))
// A non-working example of what I'm trying to do
// std::sort(Xs.begin(), Xs.end(),
// std::string((bind(bar::X->c_str(), _1)) <
// std::string((bind(bar::X->c_str(), _2)) )
}
I get lost when trying to figure out how to access the member pointers, member function and then cast the result all within a boost::bind function.
Thank you for your help.
I'm sure you can twist your way out of this using ample helpings of
Boost Phoenix bind and lambda
Boost Bind protect
However, I've learned to avoid these situations. Edit In fact, see below for one such contraption. I find this very very error prone and hard to reason about.
What you're seeing is, in essence, a violation of the Law Of Demeter. If you "just" wrote the code (not in a lambda), already it would be handling too many tasks.
So the first thing I'd do is rethink the class design.
The second thing I'd do is /extract/ different responsibilities from your comparator. Notice, that the comparator does three things:
access the c_str() of the X in lhs
access the c_str() of the X in rhs
compare the two
The first two steps are clear candidates for extraction. Let's write the generic comparer that remains first:
template <typename F>
struct compare_by_impl {
compare_by_impl(F f = F{}) : _f(std::move(f)) {}
template <typename T, typename U>
bool operator()(T const& a, U const& b) const {
return _f(a) < _f(b);
}
private:
F _f;
};
As always, it's nice to have factory function that will deduce the accessor type (in case you can get away with just using Phoenix there, it will save you specifying the (arcane) typenames involved in the expression templates):
template <typename Accessor>
compare_by_impl<Accessor> comparer_by(Accessor&& f) {
return compare_by_impl<Accessor>(std::forward<Accessor>(f));
}
Now you could already move the implementation with your sort call:
void Function()
{
struct accessX_c_str {
std::string operator()(bar const& b) const {
return b.X->c_str();
}
};
std::sort(Bs.begin(), Bs.end(), comparer_by(accessX_c_str()));
}
I'd personally leave it there.
Here's some more twisted contraptions:
// to avoid `comparer_by`
std::sort(Bs.begin(), Bs.end(), phx::bind(accessX_c_str(), arg1) < phx::bind(accessX_c_str(), arg2));
// to avoid any helper types (!?!?!? untested!)
std::sort(Bs.begin(), Bs.end(),
phx::construct<std::string>(phx::bind(&foo::c_str, phx::lambda [ phx::bind(&bar::X, arg1) ](arg1)))
< phx::construct<std::string>(phx::bind(&foo::c_str, phx::lambda [ phx::bind(&bar::X, arg1) ](arg2)))
);

C++ Push Multiple Types onto Vector

Note: I know similar questions to this have been asked on SO before, but I did not find them helpful or very clear.
Second note: For the scope of this project/assignment, I'm trying to avoid third party libraries, such as Boost.
I am trying to see if there is a way I can have a single vector hold multiple types, in each of its indices. For example, say I have the following code sample:
vector<something magical to hold various types> vec;
int x = 3;
string hi = "Hello World";
MyStruct s = {3, "Hi", 4.01};
vec.push_back(x);
vec.push_back(hi);
vec.push_back(s);
I've heard vector<void*> could work, but then it gets tricky with memory allocation and then there is always the possibility that certain portions in nearby memory could be unintentionally overridden if a value inserted into a certain index is larger than expected.
In my actual application, I know what possible types may be inserted into a vector, but these types do not all derive from the same super class, and there is no guarantee that all of these types will be pushed onto the vector or in what order.
Is there a way that I can safely accomplish the objective I demonstrated in my code sample?
Thank you for your time.
The objects hold by the std::vector<T> need to be of a homogenous type. If you need to put objects of different type into one vector you need somehow erase their type and make them all look similar. You could use the moral equivalent of boost::any or boost::variant<...>. The idea of boost::any is to encapsulate a type hierarchy, storing a pointer to the base but pointing to a templatized derived. A very rough and incomplete outline looks something like this:
#include <algorithm>
#include <iostream>
class any
{
private:
struct base {
virtual ~base() {}
virtual base* clone() const = 0;
};
template <typename T>
struct data: base {
data(T const& value): value_(value) {}
base* clone() const { return new data<T>(*this); }
T value_;
};
base* ptr_;
public:
template <typename T> any(T const& value): ptr_(new data<T>(value)) {}
any(any const& other): ptr_(other.ptr_->clone()) {}
any& operator= (any const& other) {
any(other).swap(*this);
return *this;
}
~any() { delete this->ptr_; }
void swap(any& other) { std::swap(this->ptr_, other.ptr_); }
template <typename T>
T& get() {
return dynamic_cast<data<T>&>(*this->ptr_).value_;
}
};
int main()
{
any a0(17);
any a1(3.14);
try { a0.get<double>(); } catch (...) {}
a0 = a1;
std::cout << a0.get<double>() << "\n";
}
As suggested you can use various forms of unions, variants, etc. Depending on what you want to do with your stored objects, external polymorphism could do exactly what you want, if you can define all necessary operations in a base class interface.
Here's an example if all we want to do is print the objects to the console:
#include <iostream>
#include <string>
#include <vector>
#include <memory>
class any_type
{
public:
virtual ~any_type() {}
virtual void print() = 0;
};
template <class T>
class concrete_type : public any_type
{
public:
concrete_type(const T& value) : value_(value)
{}
virtual void print()
{
std::cout << value_ << '\n';
}
private:
T value_;
};
int main()
{
std::vector<std::unique_ptr<any_type>> v(2);
v[0].reset(new concrete_type<int>(99));
v[1].reset(new concrete_type<std::string>("Bottles of Beer"));
for(size_t x = 0; x < 2; ++x)
{
v[x]->print();
}
return 0;
}
In order to do that, you'll definitely need a wrapper class to somehow conceal the type information of your objects from the vector.
It's probably also good to have this class throw an exception when you try to get Type-A back when you have previously stored a Type-B into it.
Here is part of the Holder class from one of my projects. You can probably start from here.
Note: due to the use of unrestricted unions, this only works in C++11. More information about this can be found here: What are Unrestricted Unions proposed in C++11?
class Holder {
public:
enum Type {
BOOL,
INT,
STRING,
// Other types you want to store into vector.
};
template<typename T>
Holder (Type type, T val);
~Holder () {
// You want to properly destroy
// union members below that have non-trivial constructors
}
operator bool () const {
if (type_ != BOOL) {
throw SomeException();
}
return impl_.bool_;
}
// Do the same for other operators
// Or maybe use templates?
private:
union Impl {
bool bool_;
int int_;
string string_;
Impl() { new(&string_) string; }
} impl_;
Type type_;
// Other stuff.
};

Calling different implementation of function based on SSE features

I am designing a series of Vector classes in C++ that support SSE(SIMD). The operators have been overloaded for convenience. Example of class:
class vector2 {
public:
//...code
friend const vector2 operator+ (const vector2 & lhs, const vector2 & rhs);
//...code
protected:
float x, y;
};
So far the method checks to see if the CPU has a SSE(SIMD) feature, using a class I created called PROCESSOR, which does this check when the program is executed at run-time. Example of method:
const vector2 operator+ (const vector2 & lhs, const vector2 & rhs) {
vector2 temp;
if(PROCESSOR.SSE) {
_asm { //... The "SSE WAY"
}
} else {
// The "NORMAL WAY"
}
return temp;
}
So as you can see if SSE is available it will run the "SSE" way otherwise it will run "normal" way. However, it is very in-efficient having to check if SSE is available every time this operation is called. Is there a way to implement two versions of a method and call only the appropriate method? Since my PROCESSOR class only does the SSE check once, is there a way of setting my vector class can do the same?
To help you avoid code duplication you can create two vector classes, one for SSE and one for non-SSE. Then you can template your calling algorithms.
class vector_base { float x,y; } ;
class vector_sse : public vector_base { vector_sse operator+(...){...} };
class vector_nonsse : public vector_base { vector_nonsse operator+(...){...} };
template< typename VECTOR >
void do_somthing() {
for( /*lots*/) {
VECTOR v = ...;
VECTOR w = ...;
foo(v+w);
}
}
int main() {
if(PROCESSOR.SSE) { do_something<vector_sse>(); }
else { do_something<vector_nonsse>(); }
}
If you're likely to use other classes than vector (like matrix etc) in an SSE manner you might do better by tagging your types instead .. in which case the code looks like this:
class vector_base { float x,y; } ;
struct SSE_tag;
struct NONSSE_tag;
template<typename T>
class vector;
template<>
class vector<SSE_tag> : public vector_base { vector_sse operator+(...){...} };
template<>
class vector<NONSSE_tag> : public vector_base { vector_nonsse operator+(...){...} };
template< typename TAG >
void do_somthing() {
for( /*lots*/) {
vector<TAG> v = ...;
vector<TAG> w = ...;
matrix<TAG> m = ...;
foo(v+(m*w));
}
}
int main() {
if(PROCESSOR.SSE) { do_something<SSE_tag>(); }
else { do_something<NONSSE_tag>(); }
}
Split the function into two parts, one for SSE and one not. Create a function pointer and initialize it with the appropriate version of the function. You can make an inline function that calls the pointer if that makes your code look cleaner.
Unfortunately you'll still pay the price of an indirection for the function call. Whether this is faster than testing a boolean flag can only be determined by benchmarking.
The best way to deal with this problem is to make sure the amount of data being processed with each call is enough to make the overhead insignificant.