在std：：map中搜索时发生堆栈溢出

Question

此代码在运行时由于某种原因导致堆栈溢出异常：

neuralnetwork::CPerceptron::inputEvent(const neuralnetwork::IConnection * origin, double value)
    std::map<std::reference_wrapper<const IConnection>, float64_t, _CPerceptronComparator>::iterator it = m_inputValues.find( std::ref( *origin ) );
    if ( it == m_inputValues.end() )
    {
        throw "Some error";
    }
    ...
}

class _CPerceptronComparator
{
public:
_CPerceptronComparator()
{
}

bool operator()( const std::reference_wrapper<const neuralnetwork::IConnection *> & val1,
                 const std::reference_wrapper<const neuralnetwork::IConnection *> & val2 ) const
{
    return (val1.get()) < (val2.get());
}

bool operator()( const std::reference_wrapper<const neuralnetwork::IConnection> & val1,
                 const std::reference_wrapper<const neuralnetwork::IConnection> & val2 ) const
{
    return &( val1.get() ) < &( val2.get() );
}

bool operator()( const std::reference_wrapper<neuralnetwork::IConnection> & val1,
                 const std::reference_wrapper<neuralnetwork::IConnection> & val2 ) const
{
    return &( val1.get() ) < &( val2.get() );
}
};

我增加了一些代码，也许你能帮上忙。这是我添加输入连接的方式：

 void CPerceptron::addInputConnection( IConnection * inConn )
 {
    m_outConnections.insert( std::ref(*inConn) );

    m_inputValues.insert( std::pair<std::reference_wrapper<IConnection>, float64_t>( std::ref( *inConn ), 0.0f ) );
    m_isInputReady.insert( std::pair<std::reference_wrapper<IConnection>, bool>( std::ref( *inConn ), false ) );
 }

注意：我知道std::make_pair更容易使用，但我替换了它，希望它会引起我的问题。你知道，要看透它返回的类型是不可能的。这个解决方案可能更难读懂，但却是明智之举。

错误：Neural Network.exe中0x002C2EC9处未处理得异常：0xC00000FD：堆栈溢出（参数：0x00000001,0x00102FFC）.

Neural Network.exe!std::_Iterator_base12::_Orphan_me() Line 192 C++
Neural Network.exe!std::_Iterator_base12::_Adopt(const std::_Container_base12 * _Parent) Line 165   C++
Neural Network.exe!std::_Iterator_base12::operator=(const std::_Iterator_base12 & _Right) Line 129  C++
Neural Network.exe!std::_Iterator_base12::_Iterator_base12(const std::_Iterator_base12 & _Right) Line 121   C++
Neural Network.exe!std::_Iterator012<std::bidirectional_iterator_tag,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double>,int,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const *,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const &,std::_Iterator_base12>::_Iterator012<std::bidirectional_iterator_tag,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double>,int,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const *,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const &,std::_Iterator_base12>(const std::_Iterator012<std::bidirectional_iterator_tag,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double>,int,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const *,std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> const &,std::_Iterator_base12> & __that)    C++
Neural Network.exe!std::_Tree_unchecked_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > >,std::_Iterator_base12>::_Tree_unchecked_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > >,std::_Iterator_base12>(const std::_Tree_unchecked_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > >,std::_Iterator_base12> & __that)   C++
Neural Network.exe!std::_Tree_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > >::_Tree_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > >(const std::_Tree_const_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > > & __that)    C++
Neural Network.exe!std::_Tree_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > >::_Tree_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > >(const std::_Tree_iterator<std::_Tree_val<std::_Tree_simple_types<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> > > > & __that)  C++
Neural Network.exe!std::_Tree<std::_Tmap_traits<std::reference_wrapper<neuralnetwork::IConnection const >,double,neuralnetwork::_CPerceptronComparator,std::allocator<std::pair<std::reference_wrapper<neuralnetwork::IConnection const > const ,double> >,0> >::find(const std::reference_wrapper<neuralnetwork::IConnection const > & _Keyval) Line 1553  C++
Neural Network.exe!neuralnetwork::CPerceptron::inputEvent(const neuralnetwork::IConnection * origin, double value) Line 94  C++

Answer 1

问题是由无限循环引起的（实际上是我见过的堆栈溢出的唯一原因）。

void CPerceptron::addInputConnection( IConnection * inConn )
{
    m_outConnections.insert( std::ref(*inConn) );

    m_inputValues.insert( std::pair<std::reference_wrapper<IConnection>, float64_t>( std::ref( *inConn ), 0.0f ) );
    m_isInputReady.insert( std::pair<std::reference_wrapper<IConnection>, bool>( std::ref( *inConn ), false ) );
}

我在m_outConnections中插入了一个名为AddInputConnections的函数，它在图（在神经网络中）中创建了一个圆，因此传播结果会导致无限循环（传播函数不在文章中）。

这是一个很好的例子，说明你很容易错过这么小的东西，但在其他方面却是无用的帖子。IMO删除它。