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Python2 crashes if tensorboard_logger is imported before torch #25

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@kukuruza

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@kukuruza

Thanks for the great package, it really brings much value for me. But I've recently come across a python crash.

*** Error in `python': malloc(): memory corruption: 0x000000007842e4c0 ***
Aborted (core dumped)

Steps to reproduce. Running the script below causes the crash on the last line (forward pass of the network).

from tensorboard_logger import configure

import torch
from torch.autograd import Variable

mymodel = torch.nn.Sequential(torch.nn.Conv2d(3, 10, kernel_size=3, bias=True))
imgs = Variable(torch.zeros((1,3,64,64), dtype=torch.float32)).cuda()
mymodel.cuda()
mymodel(imgs)

I also found that switching the order of the imports solves the problem. The following works fine.

import torch
from torch.autograd import Variable

from tensorboard_logger import configure

mymodel = torch.nn.Sequential(torch.nn.Conv2d(3, 10, kernel_size=3, bias=True))
imgs = Variable(torch.zeros((1,3,64,64), dtype=torch.float32)).cuda()
mymodel.cuda()
mymodel(imgs)

If I am not using .cuda() in the code, any order works fine.

System:

Ubuntu 14.04.5 LTS
Cuda  8.0, V8.0.61

Packages:

python                    2.7.15               h33da82c_4    conda-forge
pytorch                   0.4.1                py27__9.0.176_7.1.2_2
tensorboard-logger        0.1.0

I installed them with

conda install pytorch torchvision -c pytorch
pip install tensorboard_logger

I assume the order of imports was tested before, so my only guess is that conda and pip don't work well together and load different versions of some package.

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