We have to.dtype_layout, to.device, to.dtype, to.other. I use gdb to trace and find that it calls to.dtype_layout instead of to.device.
import torch
a = torch.Tensor([1,2,3]).to("cuda")
We have to.dtype_layout, to.device, to.dtype, to.other. I use gdb to trace and find that it calls to.dtype_layout instead of to.device.
import torch
a = torch.Tensor([1,2,3]).to("cuda")
The to()
method check for all input options. What kind of issue are you seeing?
If I want to call to.dtype
instead of to.dtype_layout
, how to code?
If you want to change the dtype
, you can directly pass the wanted dtype
to the to()
call:
x = x.to(torch.float32)
x = x.to(torch.long)
or call the “dtype method” on the tensor:
x = x.float()
x = x.long()
Sorry, I’m wrong. When I use tensor.to(torch.long)
it will call to.dtype. But When I call tensor.to("cuda")
it will call to.dtype_layout instead of to.device.