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https://issues.apache.org/jira/browse/ARROW-2920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Rok Mihevc updated ARROW-2920:
------------------------------
External issue URL: https://github.com/apache/arrow/issues/19287
> [Python] Segfault with pytorch 0.4
> ----------------------------------
>
> Key: ARROW-2920
> URL: https://issues.apache.org/jira/browse/ARROW-2920
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: Philipp Moritz
> Assignee: Philipp Moritz
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.10.0
>
> Time Spent: 1.5h
> Remaining Estimate: 0h
>
> See also [https://github.com/ray-project/ray/issues/2447]
> How to reproduce:
> * Start the Ubuntu Deep Learning AMI (version 12.0) on EC2
> * Create a new env with {{conda create -y -n breaking-env python=3.5}}
> * Install pytorch with {{source activate breaking-env && conda install
> pytorch torchvision cuda91 -c pytorch}}
> * Compile and install manylinux1 pyarrow wheels from latest arrow master as
> described here:
> https://github.com/apache/arrow/blob/2876a3fdd1fb9ef6918b7214d6e8d1e3017b42ad/python/manylinux1/README.md
> * In the breaking-env just created, run the following:
>
> {code:java}
> Python 3.5.5 |Anaconda, Inc.| (default, May 13 2018, 21:12:35)
> [GCC 7.2.0] on linux
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import pyarrow
> >>> import torch
> >>> torch.nn.Conv2d(64, 2, kernel_size=3, stride=1, padding=1,
> >>> bias=False).cuda()
> Segmentation fault (core dumped){code}
>
> Backtrace:
> {code:java}
> >>> torch.nn.Conv2d(64, 2, kernel_size=3, stride=1, padding=1,
> >>> bias=False).cuda()
> Program received signal SIGSEGV, Segmentation fault.
> 0x0000000000000000 in ?? ()
> (gdb) bt
> #0 0x0000000000000000 in ?? ()
> #1 0x00007ffff7bc8a99 in __pthread_once_slow (once_control=0x7fffdb791e50
> <at::globalContext()::globalContext_+400>, init_routine=0x7fffe46aafe1
> <std::__once_proxy()>)
> at pthread_once.c:116
> #2 0x00007fffda95c302 in at::Type::toBackend(at::Backend) const () from
> /home/ubuntu/anaconda3/envs/breaking-env2/lib/python3.5/site-packages/torch/lib/libcaffe2.so
> #3 0x00007fffdc59b231 in torch::autograd::VariableType::toBackend
> (this=<optimized out>, b=<optimized out>) at
> torch/csrc/autograd/generated/VariableType.cpp:145
> #4 0x00007fffdc8dbe8a in torch::autograd::THPVariable_cuda
> (self=0x7ffff6dbff78, args=0x7ffff6daf828, kwargs=0x0) at
> torch/csrc/autograd/generated/python_variable_methods.cpp:333
> #5 0x000055555569f4e8 in PyCFunction_Call ()
> #6 0x00005555556f67cc in PyEval_EvalFrameEx ()
> #7 0x00005555556fbe08 in PyEval_EvalFrameEx ()
> #8 0x00005555556f6e90 in PyEval_EvalFrameEx ()
> #9 0x00005555556fbe08 in PyEval_EvalFrameEx ()
> #10 0x000055555570103d in PyEval_EvalCodeEx ()
> #11 0x0000555555701f5c in PyEval_EvalCode ()
> #12 0x000055555575e454 in run_mod ()
> #13 0x000055555562ab5e in PyRun_InteractiveOneObject ()
> #14 0x000055555562ad01 in PyRun_InteractiveLoopFlags ()
> #15 0x000055555562ad62 in PyRun_AnyFileExFlags.cold.2784 ()
> #16 0x000055555562b080 in Py_Main.cold.2785 ()
> #17 0x000055555562b871 in main (){code}
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