Skip to main content

A pytorch perf decorator

Project description

PyTorch Perf

import torch
from torchperf import perf, info

info.show()

N = 100
x = torch.rand(N, N, device="cuda")
results = []
repeats = 100

@perf(o=results, n=repeats)
def mul(x, y):
    return x * y

z = mul(x, x)
print(results[:5])
print("avg:", sum(results)/len(results))


@perf(n=repeats)
def mul(x, y):
    return x * y

z = mul(x, x)

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

pytorch-perf-0.0.1.dev0.tar.gz (3.8 kB view details)

Uploaded Source

Built Distribution

pytorch_perf-0.0.1.dev0-py3-none-any.whl (3.9 kB view details)

Uploaded Python 3

File details

Details for the file pytorch-perf-0.0.1.dev0.tar.gz.

File metadata

  • Download URL: pytorch-perf-0.0.1.dev0.tar.gz
  • Upload date:
  • Size: 3.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for pytorch-perf-0.0.1.dev0.tar.gz
Algorithm Hash digest
SHA256 5857f53c85bc3319fe7dd07cb64a27d1ac28d70b79bbbae2a336042c18e16ccc
MD5 9fc29991ec5b5f0e23b84da71ba3531b
BLAKE2b-256 ba89852c0e0ff6fdef52488a9a97ce05921159651601a16e4e5b3fa94b8d73e9

See more details on using hashes here.

File details

Details for the file pytorch_perf-0.0.1.dev0-py3-none-any.whl.

File metadata

File hashes

Hashes for pytorch_perf-0.0.1.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 ef2cad0360f13b7e3f6071d582f4afcc853e6864bf337604bccfc66772eecb39
MD5 795617bf54c91682e5d1ac29693dedf3
BLAKE2b-256 92c6174541e43480bd34c9d5bb1cfefc5fb8b377eb8c6b87eaee61ea6afd45eb

See more details on using hashes here.

Supported by

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