I went ahead and installed the new .whl that @smth put out, (changing to cu80 since I have cuda 8.0), and the install seemed to go well. I can train a net, but I am wondering if I need to do anything else to make sure that it uses my GPUs? When I do nvidia-smi I do not see any activity… how can I force it to train using my GPUs? thanks.
EDIT:
I use net.cuda() and this seems to work. However when I try to run my script I get this error:

Traceback (most recent call last):
File “test.py”, line 266, in 
yEst = net.forward_prop(currentBatchData)
File “test.py”, line 126, in forward_prop
x = F.max_pool2d(F.relu(self.conv1(x)), (2,2))
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/modules/module.py”, line 210, in call
result = self.forward(*input, **kwargs)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/modules/conv.py”, line 235, in forward
self.padding, self.dilation, self.groups)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/functional.py”, line 37, in conv2d
return f(input, weight, bias) if bias is not None else f(input, weight)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/_functions/conv.py”, line 33, in forward
output = self._update_output(input, weight, bias)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/_functions/conv.py”, line 88, in _update_output
return self._thnn(‘update_output’, input, weight, bias)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/_functions/conv.py”, line 147, in _thnn
return impl[fn_name](self, self._bufs[0], input, weight, *args)
File “/data/venv/pytorch/local/lib/python2.7/site-packages/torch/nn/_functions/conv.py”, line 219, in call_update_output
bias, *args)
TypeError: FloatSpatialConvolutionMM_updateOutput received an invalid combination of arguments - got (int, torch.FloatTensor, torch.FloatTensor, torch.cuda.FloatTensor, torch.cuda.FloatTensor, torch.FloatTensor, torch.FloatTensor, long, long, int, int, int, int), but expected (int state, torch.FloatTensor input, torch.FloatTensor output, torch.FloatTensor weight, [torch.FloatTensor bias or None], torch.FloatTensor finput, torch.FloatTensor fgradInput, int kW, int kH, int dW, int dH, int padW, int padH)

(If I do not try to run net.cuda() my script works find on the CPU).