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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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