public inbox for gcc-prs@sourceware.org
help / color / mirror / Atom feed
* c++/4051: template instantiation problem with ostream_iterator and pair of buil
@ 2001-08-17 14:46 ola
  0 siblings, 0 replies; only message in thread
From: ola @ 2001-08-17 14:46 UTC (permalink / raw)
  To: gcc-gnats

>Number:         4051
>Category:       c++
>Synopsis:       template instantiation problem with ostream_iterator and pair of buil
>Confidential:   no
>Severity:       non-critical
>Priority:       medium
>Responsible:    unassigned
>State:          open
>Class:          rejects-legal
>Submitter-Id:   net
>Arrival-Date:   Fri Aug 17 14:46:00 PDT 2001
>Closed-Date:
>Last-Modified:
>Originator:     Owen Astrachan
>Release:        3.0
>Organization:
>Environment:
System: SunOS goby 5.8 Generic_108528-09 sun4u sparc SUNW,Ultra-5_10
Architecture: sun4
host: sparc-sun-solaris2.8
build: sparc-sun-solaris2.8
target: sparc-sun-solaris2.8
configured with: ./configure --prefix=/usr/pkg/gcc-3.0
>Description:
There's a problem with template instantiation using ostream_iterator
and pair, where pair<a,b> has either a or b as a built-in type.
If both a and b are user-defined (e.g., class Foo and class Bar)
types with corresponding overloaded operator <<, the the program
below compiles as it should. However, when either b or a is a built-int
type, or a standard C++ type, e.g., vector<int> then an error like the
one below results.

gcc output belowcd /home/home4/ola/108/code/
/usr/pkg/gcc-3.0/bin/g++ -Wall -v -save-temps bug.cpp
Reading specs from /usr/pkg/gcc-3.0/lib/gcc-lib/sparc-sun-solaris2.8/3.0/specs
Configured with: ./configure --prefix=/usr/pkg/gcc-3.0
Thread model: posix
gcc version 3.0
 /usr/pkg/gcc-3.0/lib/gcc-lib/sparc-sun-solaris2.8/3.0/cpp0 -lang-c++ -D__GNUG__=3 -D__GXX_DEPRECATED -D__EXCEPTIONS -D__GXX_ABI_VERSION=100 -v -D__GNUC__=3 -D__GNUC_MINOR__=0 -D__GNUC_PATCHLEVEL__=0 -Dsparc -Dsun -Dunix -D__svr4__ -D__SVR4 -D__sparc__ -D__sun__ -D__unix__ -D__svr4__ -D__SVR4 -D__sparc -D__sun -D__unix -Asystem=unix -Asystem=svr4 -D__NO_INLINE__ -D__STDC_HOSTED__=1 -Wall -D_XOPEN_SOURCE=500 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -D__EXTENSIONS__ -D__GCC_NEW_VARARGS__ -Acpu=sparc -Amachine=sparc bug.cpp bug.ii
GNU CPP version 3.0 (cpplib) (sparc)
ignoring nonexistent directory "/usr/pkg/gcc-3.0/sparc-sun-solaris2.8/include"
#include "..." search starts here:
#include <...> search starts here:
 /usr/pkg/gcc-3.0/include/g++-v3
 /usr/pkg/gcc-3.0/include/g++-v3/sparc-sun-solaris2.8
 /usr/pkg/gcc-3.0/include/g++-v3/backward
 /usr/pkg/gcc-3.0/include
 /usr/pkg/gcc-3.0/lib/gcc-lib/sparc-sun-solaris2.8/3.0/include
 /usr/include
End of search list.
 /usr/pkg/gcc-3.0/lib/gcc-lib/sparc-sun-solaris2.8/3.0/cc1plus -fpreprocessed bug.ii -quiet -dumpbase bug.cpp -Wall -version -o bug.s
GNU CPP version 3.0 (cpplib) (sparc)
GNU C++ version 3.0 (sparc-sun-solaris2.8)
        compiled by GNU C version 2.95.2 19991024 (release).
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_iterator.h: In member function 
   `std::ostream_iterator<_Tp, char, std::char_traits<char> >& 
   std::ostream_iterator<_Tp, _CharT, _Traits>::operator=(const _Tp&) [with _Tp 
   = std::pair<int, int>, _CharT = char, _Traits = std::char_traits<char>]':
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:153:   instantiated from `_OutputIter std::__copy(_RandomAccessIter, _RandomAccessIter, _OutputIter, std::random_access_iterator_tag, _Distance*) [with _RandomAccessIter = std::pair<int, int>*, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >, _Distance = ptrdiff_t]'
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:173:   instantiated from `_OutputIter std::__copy_aux2(_InputIter, _InputIter, _OutputIter, _Bool<false>) [with _InputIter = std::pair<int, int>*, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >]'
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:208:   instantiated from `_OutputIter std::__copy_aux(_InputIter, _InputIter, _OutputIter, _Tp*) [with _InputIter = std::pair<int, int>*, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >, _Tp = std::pair<int, int>]'
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:223:   instantiated from `_OutputIter std::__copy_ni2(_InputIter, _InputIter, _OutputIter, _Bool<false>) [with _InputIter = std::pair<int, int>*, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >]'
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:231:   instantiated from `_OutputIter std::__copy_ni1(_InputIter, _InputIter, _OutputIter, _Bool<true>) [with _InputIter = std::__normal_iterator<std::pair<int, int>*, std::vector<std::pair<int, int>, std::allocator<std::pair<int, int> > > >, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >]'
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_algobase.h:252:   instantiated from `_OutputIter std::copy(_InputIter, _InputIter, _OutputIter) [with _InputIter = std::__normal_iterator<std::pair<int, int>*, std::vector<std::pair<int, int>, std::allocator<std::pair<int, int> > > >, _OutputIter = std::ostream_iterator<std::pair<int, int>, char, std::char_traits<char> >]'
bug.cpp:16:   instantiated from here
/usr/pkg/gcc-3.0/include/g++-v3/bits/stl_iterator.h:397: no match for 
   `std::basic_ostream<char, std::char_traits<char> >& << const std::pair<int, 
   int>&' operator
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:50: candidates are: 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(std::basic_ostream<_CharT, 
   _Traits>&(*)(std::basic_ostream<_CharT, _Traits>&)) [with _CharT = char, 
   _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:72:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(std::basic_ios<_CharT, 
   _Traits>&(*)(std::basic_ios<_CharT, _Traits>&)) [with _CharT = char, _Traits 
   = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:94:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(std::ios_base&(*)(std::ios_base&)) [with _CharT = char, 
   _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:140:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(long int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:177:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(long unsigned int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:115:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(bool) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:99:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(short int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:110:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(short unsigned int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:114:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:125:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(unsigned int) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:267:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(double) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:140:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(float) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:292:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(long double) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:317:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(const void*) [with _CharT = char, _Traits = 
   std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:342:                 
   std::basic_ostream<_CharT, _Traits>& std::basic_ostream<_CharT, 
   _Traits>::operator<<(std::basic_streambuf<_CharT, _Traits>*) [with _CharT = 
   char, _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:215:                 
   std::basic_ostream<_CharT, _Traits>& 
   std::operator<<(std::basic_ostream<_CharT, _Traits>&, char) [with _CharT = 
   char, _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:575:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, char) [with _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:226:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, signed char) [with _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:231:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, unsigned char) [with _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:643:                 
   std::basic_ostream<_CharT, _Traits>& 
   std::operator<<(std::basic_ostream<_CharT, _Traits>&, const char*) [with 
   _CharT = char, _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/ostream.tcc:689:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, const char*) [with _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:250:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, const signed char*) [with _Traits = std::char_traits<char>]
/usr/pkg/gcc-3.0/include/g++-v3/bits/std_ostream.h:255:                 
   std::basic_ostream<char, _Traits>& std::operator<<(std::basic_ostream<char, 
   _Traits>&, const unsigned char*) [with _Traits = std::char_traits<char>]

Compilation exited abnormally with code 1 at Fri Aug 17 17:09:35





>How-To-Repeat:
#include <vector>
#include <iostream>
using namespace std;

ostream& operator << (ostream& out, const pair<int, int> & p)
{
    out << p.first << " " << p.second;
    return out;
}

int main()
{
    vector<pair<int, int> > vpi;
    
    copy(vpi.begin(), vpi.end(),
         ostream_iterator<pair<int,int> >(cout,"\n"));

    return 0;
}
>Fix:
Use userdefined class Foo<x,y> instead of pair<x,y>
>Release-Note:
>Audit-Trail:
>Unformatted:
----gnatsweb-attachment----
Content-Type: application/x-gzip-compressed; name="bug.ii.gz"
Content-Transfer-Encoding: base64
Content-Disposition: attachment; filename="bug.ii.gz"
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^ permalink raw reply	[flat|nested] only message in thread

only message in thread, other threads:[~2001-08-17 14:46 UTC | newest]

Thread overview: (only message) (download: mbox.gz / follow: Atom feed)
-- links below jump to the message on this page --
2001-08-17 14:46 c++/4051: template instantiation problem with ostream_iterator and pair of buil ola

This is a public inbox, see mirroring instructions
for how to clone and mirror all data and code used for this inbox;
as well as URLs for read-only IMAP folder(s) and NNTP newsgroup(s).