hi, I met a issue:
# env
cuda-8.0-cudnn-7
python 2.7/3.5
torch-2.0
here:
a = Variable(torch.randn(2,5).cuda(), requires_grad=True)
y = torch.nn.BatchNorm1d(5)(a)
## info
----> 1 y = torch.nn.BatchNorm1d(5)(a)
~/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.pyc in __call__(self, *input, **kwargs)
222 for hook in self._forward_pre_hooks.values():
223 hook(self, input)
--> 224 result = self.forward(*input, **kwargs)
225 for hook in self._forward_hooks.values():
226 hook_result = hook(self, input, result)
~/anaconda2/lib/python2.7/site-packages/torch/nn/modules/batchnorm.pyc in forward(self, input)
35 return F.batch_norm(
36 input, self.running_mean, self.running_var, self.weight, self.bias,
---> 37 self.training, self.momentum, self.eps)
38
39 def __repr__(self):
~/anaconda2/lib/python2.7/site-packages/torch/nn/functional.pyc in batch_norm(input, running_mean, running_var, weight, bias, training, momentum, eps)
637 training=False, momentum=0.1, eps=1e-5):
638 f = torch._C._functions.BatchNorm(running_mean, running_var, training, momentum, eps, torch.backends.cudnn.enabled)
--> 639 return f(input, weight, bias)
640
641
RuntimeError: std::bad_cast
But works well on cpu.
anyone met this?