The value is 0, then I try this code,still get an error.
TypeError                                 Traceback (most recent call last)
<ipython-input-418-2de402a52488> in <module>()
----> 1 robust_loss_pytorch.adaptive.AdaptiveLossFunction( num_dims = 4, float_dtype=torch.cuda.FloatTensor, device=0)

~/anaconda3/envs/torch36/lib/python3.6/site-packages/robust_loss_pytorch/adaptive.py in __init__(self, num_dims, float_dtype, device, alpha_lo, alpha_hi, alpha_init, scale_lo, scale_init)
    154               latent_alpha_init.clone().detach().to(
    155                   dtype=self.float_dtype,
--> 156                   device=self.device)[np.newaxis, np.newaxis].repeat(
    157                       1, self.num_dims),
    158               requires_grad=True))

TypeError: to() received an invalid combination of arguments - got (device=int, dtype=torch.tensortype, ), but expected one of:
 * (torch.device device, torch.dtype dtype, bool non_blocking, bool copy, *, torch.memory_format memory_format)
 * (torch.dtype dtype, bool non_blocking, bool copy, *, torch.memory_format memory_format)
 * (Tensor tensor, bool non_blocking, bool copy, *, torch.memory_format memory_format)