Fix bugs that Mixup does not work when device is cpu
diff --git a/timm/data/mixup.py b/timm/data/mixup.py
index 38477548a0..7e382c5233 100644
--- a/timm/data/mixup.py
+++ b/timm/data/mixup.py
@@ -214,7 +214,7 @@ def __call__(self, x, target):
             lam = self._mix_pair(x)
         else:
             lam = self._mix_batch(x)
-        target = mixup_target(target, self.num_classes, lam, self.label_smoothing)
+        target = mixup_target(target, self.num_classes, lam, self.label_smoothing, x.device)
         return x, target
 
 

`timm.data.Mixup` class does not work when device is cpu.

```python
from timm.data.mixup import Mixup

mixup_args = {
    'mixup_alpha': 1.,
    'cutmix_alpha': 0.,
    'cutmix_minmax': None,
    'prob': 1.0,
    'switch_prob': 0.,
    'mode': 'batch',
    'label_smoothing': 0,
    'num_classes': 4
}

mixup_fn = Mixup(**mixup_args)
x, labels = next(iter(loader))
x, labels = mixup_fn(x, labels)
```

```
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-22-ac462bac9f44> in <module>()
     21 loader = torch.utils.data.DataLoader(train_dataset, batch_size=16, shuffle=True)
     22 x, labels = next(iter(loader))
---> 23 x, labels = mixup_fn(x, labels)
     24 
     25 

2 frames
/usr/local/lib/python3.7/dist-packages/timm/data/mixup.py in __call__(self, x, target)
    215         else:
    216             lam = self._mix_batch(x)
--> 217         target = mixup_target(target, self.num_classes, lam, self.label_smoothing)
    218         return x, target
    219 

/usr/local/lib/python3.7/dist-packages/timm/data/mixup.py in mixup_target(target, num_classes, lam, smoothing, device)
     23     off_value = smoothing / num_classes
     24     on_value = 1. - smoothing + off_value
---> 25     y1 = one_hot(target, num_classes, on_value=on_value, off_value=off_value, device=device)
     26     y2 = one_hot(target.flip(0), num_classes, on_value=on_value, off_value=off_value, device=device)
     27     return y1 * lam + y2 * (1. - lam)

/usr/local/lib/python3.7/dist-packages/timm/data/mixup.py in one_hot(x, num_classes, on_value, off_value, device)
     17 def one_hot(x, num_classes, on_value=1., off_value=0., device='cuda'):
     18     x = x.long().view(-1, 1)
---> 19     return torch.full((x.size()[0], num_classes), off_value, device=device).scatter_(1, x, on_value)
     20 
     21 

RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking arugment for argument index in method wrapper_scatter__value)
```

So, I fixed `timm.data.Mixup` class. 