解决方法：
def conv_2(batch, channel=256):
mydevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu') ### aimin li, added
for x in batch:
x.to(mydevice)
weights = torch.ones(channel, in_channel, 2, 2).to(mydevice)
b = torch.ones(channel).to(mydevice)
out = F.conv2d(input=x, weight=weights, bias=b, stride=1, padding=1)
