torch compatibility layer
Project description
pip install torchcompat
Features
Provide a super set implementation of pytorch device interface to enable code to run seamlessly between different accelerators.
Identify uniquely devices
import torchcompat.core as accelerator
# on cuda accelerator == torch.cuda
# on rocm accelerator == torch.cuda
# on xpu accelerator == torch.xpu
# on gaudi accelerator == ...
assert accelerator.is_available() == true
assert accelerator.device_name in ('xpu', 'cuda', "hpu") # rocm is seen as cuda by pytorch
assert accelerator.device_string(0) == "cuda:0" or "xpu:0" or "hpu:0"
assert accelerator.fetch_device(0) == torch.device("cuda:0")
accelerator.set_enable_tf32(true) # toggle the right flags for each backend
Example
example here
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
torchcompat-1.1.2.tar.gz
(6.1 kB
view hashes)
Built Distribution
Close
Hashes for torchcompat-1.1.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7ef1b571034b7e0182650d3d433e3e4fbc1df77d5ab4b047112de9e3c5fc84c |
|
MD5 | 892dd9ff3a055850006edcb96c48c508 |
|
BLAKE2b-256 | a9eda03fc071c6c55f64cfeb0a0f7a3d2cce9422ce963ff6209ebdfab824f115 |