Dear sir,
I am a new guy,had issue with GPU training for cifar10_tutorial. CPU training code is fine!
My environment:
pytorch                   0.2.0           py27hc03bea1_4cu80  [cuda80]  soumith
torchvision               0.1.9            py27hdb88a65_1    soumith
code:
in 30: outputs = net.cuda(Variable(images))
I get:
RuntimeError                              Traceback (most recent call last)
 in ()
----> 1 outputs = net.cuda(Variable(images))
/home/john/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.pyc in cuda(self, device_id)
145                 copied to that device
146         “”"
–> 147         return self._apply(lambda t: t.cuda(device_id))
148
149     def cpu(self):
/home/john/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.pyc in _apply(self, fn)
116     def _apply(self, fn):
117         for module in self.children():
–> 118             module._apply(fn)
119
120         for param in self._parameters.values():
/home/john/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.pyc in _apply(self, fn)
122                 # Variables stored in modules are graph leaves, and we don’t
123                 # want to create copy nodes, so we have to unpack the data.
–> 124                 param.data = fn(param.data)
125                 if param._grad is not None:
126                     param._grad.data = fn(param._grad.data)
/home/john/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.pyc in (t)
145                 copied to that device
146         “”"
–> 147         return self._apply(lambda t: t.cuda(device_id))
148
149     def cpu(self):
/home/john/anaconda2/lib/python2.7/site-packages/torch/_utils.pyc in _cuda(self, device, async)
51         if device is None:
52             device = torch.cuda.current_device()
—> 53         if self.get_device() == device:
54             return self
55     else:
/home/john/anaconda2/lib/python2.7/site-packages/torch/autograd/variable.pyc in bool(self)
121             return False
122         raise RuntimeError(“bool value of Variable objects containing non-empty " +
–> 123                            torch.typename(self.data) + " is ambiguous”)
124
125     nonzero = bool
RuntimeError: bool value of Variable objects containing non-empty torch.ByteTensor is ambiguous
Do anybody try the tutorial? Is this a known bug? How could I fix it?
Thanks
John