clab / clab/dynet

double free or corruption (fasttop)

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moderate bug
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C++
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Description

I translated the RNNG code (https://github.com/clab/rnng) into dynet 2.0.3 (rnng code was written in dynet's old version: cnn), just changing Parameter to Parameters... and similar stuff.

It trains perfectly fine and it decodes also perfectly fine, providing a F1 score that replicates what we had in the paper. Everything seems to work fine but when I decode I get the following error, after finishing and obtaining the output:

Test output in /tmp/parser_test_eval.25868.txt
F1score: 89.1
*** Error in `./nt-parser': double free or corruption (fasttop): 0x0000000001a46220 ***
======= Backtrace: =========
/lib64/libc.so.6(+0x7c619)[0x2b853d97e619]
/lib64/libstdc++.so.6(_ZNSsD1Ev+0x43)[0x2b853d19fe43]
/lib64/libc.so.6(__cxa_finalize+0x9a)[0x2b853d93adda]
/opt/share/boost-1.57.0/lib/libboost_program_options.so.1.57.0(+0x2a716)[0x2b8535793716]

This is the discriminative parser.

I tried with 2 different boost versions 1.57.0 and 1.59.0, same issue with all of them. In RNNG we used boost for stream processing and I still do in this local RNNG version. This means that I changed the code to use the newest Dynet saving/loading parameters routines that get rid of boost, but not for the rest of boost operations used in the RNNG code.

Is this a Dynet issue? or should I look somewhere else?
any ideas?

Thank you,
Miguel

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Research direction

Start by reproducing the failure in ./nt-parser after decoding and review the reported backtrace, especially the Boost stream-processing code used by the translated RNNG integration. Compare the parameter saving/loading changes with the remaining Boost operations; done means identifying whether the corruption is in DyNet or the local RNNG code and documenting a minimal reproducible case.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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