Hi, I’m doing some calculations using numba cuda and was wondering if I could just wrap the cuda array with a
FloatTensor and
Variable instead of copying it to the
host using numba and back to
device with pytorch.
Let’s say I do:
from numba import cuda import numpy as np x = cuda.device_array((3, 9, 11), dtype=np.float32)
How can I wrap this array with pytorch?
I am able to get the ctypes pointer of the array with
x.device_ctypes_pointer but I don’t know how to proceed from there to pass it to a
torch.cuda.FloatTensor
As far as I can tell, this code here does the opposite: