Skip to main content

Provides a helper to detect the best Pytorch device (env override, CUDA, MPS, XPU, or CPU) and to clear CUDA caches.

Project description

Pytorch Device Detection

Small utility to select a torch device at runtime and to clear CUDA caches.

Summary

Provides two functions:

  • get_device(strings=False, verbose=False): returns the best available device (torch.device by default, or a string when strings=True). Probes in this order: TORCH_DEVICE/DEVICE environment variables, CUDA, MPS, XPU (torch.xpu or intel_extension_for_pytorch.xpu), then CPU. When verbose=True the function emits debug-level messages through the logger.

  • clear_torch(): calls torch.cuda.empty_cache().

Install

uv add devicer

If you want XPU:

uv add devicer[xpu]

Usage

from devicer import get_device

device = get_device()
print(device)

Environment variables:

  • Set TORCH_DEVICE or DEVICE to force a device, for example cuda, cuda:0, mps, cpu, or xpu:
export TORCH_DEVICE=cuda
python myscript.py

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

devicer-0.1.1.tar.gz (2.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

devicer-0.1.1-py3-none-any.whl (3.5 kB view details)

Uploaded Python 3

File details

Details for the file devicer-0.1.1.tar.gz.

File metadata

  • Download URL: devicer-0.1.1.tar.gz
  • Upload date:
  • Size: 2.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.8

File hashes

Hashes for devicer-0.1.1.tar.gz
Algorithm Hash digest
SHA256 1568bfcab9bf687452bf4dea1c7beed52d9d926a533a6248b1dd92d2a9dc156f
MD5 6eb62f9a0992aba0ba8552addfc3bb38
BLAKE2b-256 8c7a72244570a812e200dff1904c0cace93a0465a5fd720e6faa76937c1423a3

See more details on using hashes here.

File details

Details for the file devicer-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: devicer-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 3.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.8

File hashes

Hashes for devicer-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 fac7b4e55510a165184fce6315b03f05cfa094131da43e77fe22114bd92498f4
MD5 726bcfc44fecde757c6cdbda303a1972
BLAKE2b-256 01a44c3f53f6837494df02b2e496d96dde4973f49a88771cd2753df78f7e888c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page