Skip to main content

nnprof

Introduction

nnprof is a profile tool for pytorch neural networks.

Features

  • multi profile mode: nnprof support 4 profile mode: Layer level, Operation level, Mixed level, Layer Tree level. Please check below for detail usage.
  • time and memory profile: nnprof support both time and memory profile now. But since memory profile is first supported in pytorch 1.6, please use torch version >= 1.6 for memory profile.
  • support sorted by given key and show profile percent: user could print table with percentage and sorted profile info using a given key, which is really helpful for optimiziing neural network.

Requirements

  • Python >= 3.6
  • PyTorch
  • Numpy

Get Started

install nnprof

  • pip install:
pip install nnprof
  • from source:
python -m pip install 'git+https://github.com/FateScript/nnprof.git'

# or install after clone this repo
git clone https://github.com/FateScript/nnprof.git
pip install -e nnprof

use nnprf

from nnprof import profile, ProfileMode
import torch
import torchvision

model = torchvision.models.alexnet(pretrained=False)
x = torch.rand([1, 3, 224, 224])

# mode could be anyone in LAYER, OP, MIXED, LAYER_TREE
mode = ProfileMode.LAYER

with profile(model, mode=mode) as prof:
    y = model(x)

print(prof.table(average=False, sorted_by="cpu_time"))
# table could be sorted by presented header.

Part of presented table looks like table below, Note that they are sorted by cpu_time.

╒══════════════════════╤═══════════════════╤═══════════════════╤════════╕
│ name                 │ self_cpu_time     │ cpu_time          │   hits │
╞══════════════════════╪═══════════════════╪═══════════════════╪════════╡
│ AlexNet.features.0   │ 19.114ms (34.77%) │ 76.383ms (45.65%) │      1 │
├──────────────────────┼───────────────────┼───────────────────┼────────┤
│ AlexNet.features.3   │ 5.148ms (9.37%)   │ 20.576ms (12.30%) │      1 │
├──────────────────────┼───────────────────┼───────────────────┼────────┤
│ AlexNet.features.8   │ 4.839ms (8.80%)   │ 19.336ms (11.56%) │      1 │
├──────────────────────┼───────────────────┼───────────────────┼────────┤
│ AlexNet.features.6   │ 4.162ms (7.57%)   │ 16.632ms (9.94%)  │      1 │
├──────────────────────┼───────────────────┼───────────────────┼────────┤
│ AlexNet.features.10  │ 2.705ms (4.92%)   │ 10.713ms (6.40%)  │      1 │
├──────────────────────┼───────────────────┼───────────────────┼────────┤

You are welcomed to try diffierent profile mode and more table format.

Contribution

Any issues and pull requests are welcomed.

Acknowledgement

Some thoughts of nnprof are inspired by torchprof and torch.autograd.profile . Many thanks to the authors.

Metadata

Release files for nnprof 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nnprof 0.1.1
File Size Uploaded
nnprof-0.1.1.tar.gz 7.2 kB Details

Release files / nnprof-0.1.1.tar.gz

Download URL nnprof-0.1.1.tar.gz
Size 7.2 kB
Tags Source
SHA-256 checksum
How to use checksums
dca701810c075ca01cd553d4ccff6a9cea62a1c7d9371933ec4ccaf1ed3eb85b
BLAKE2b-256 checksum
How to use checksums
9db3a978d2b1185c6d26decb62d13d04903f23e6c25adecfd5b20ff78e96fd17
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.3.0 pkginfo/1.6.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.8

Release history Release notifications | RSS feed

This release

0.1.1 This release

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page