Everytime I use cuda() to remove Variable from CPU to GPU in pytorch,it takes about 5 to 10 minitues
I just do this:

t = Variable(torch.randn(5))
t =t.cuda()
print(t)


but it takes 5 to 10 minitues,everytime.
I used cuda samples to test bandwidth, it's fine.
Then I used pdb to find which takes the most time.
I find in /anaconda3/lib/python3.6/site-packages/torch/cuda/__init__:

def _lazy_new(cls, *args, **kwargs):
    _lazy_init()
    # We need this method only for lazy init, so we can remove it
    del _CudaBase.__new__
    return super(_CudaBase, cls).__new__(cls, *args, **kwargs)


it takes about 5 minitues in the return
I don't know how to solve my problem by these imformation.
My environment is: Ubuntu 16.04 + CUDA 9.1

There’s a cuda version mismatch between the cuda my pytorch was compiled with the cuda I'm running.I divided the official installation commond

conda install pytorch torchvision cuda90 -c pytorch

into two section：

conda install -c soumith magma-cuda90
conda install pytorch torchvision -c soumith

The second commond installed pytorch-0.2.0 by default,which mathchs CUDA8.0. After I update my pytorch to 0.3.0,this commond only takes one second.
