Install

pip install autonvtx

Usage

Write your model as usual and autonvtx(model) to your model:

import torch
import autonvtx

class Model(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.layer1 = torch.nn.Linear(5, 5)
        self.layer2 = torch.nn.Linear(5, 5)
    def forward(self, x):
        x = self.layer1(x)
        x = self.layer2(x)
        return x

m = Model().cuda()
autonvtx(m)
input_ = torch.randn(1024, 5, device='cuda')

torch.cuda.profiler.start()
for _ in range(10):
    output = m(input_)
torch.cuda.profiler.stop()

The screenshot for this would be:

Screenshot 1

It also works with existing models:

import torch
import torchvision
import autonvtx

m = torchvision.models.resnet50()
autonvtx(m)
input_ = torch.randn(10, 3, 224, 224)

torch.cuda.profiler.start()
for _ in range(10):
    output = m(input_)
torch.cuda.profiler.stop()

The screenshot for this would be:

Screenshot 2

Metadata

Release files for autonvtx 0.1

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

Source distribution (sdist)

Source distribution for autonvtx 0.1
File	Size	Uploaded	Provenance	Actions
autonvtx-0.1.linux-x86_64.tar.gz	2.0 kB	Dec 17, 2019	Without provenance	Details for autonvtx-0.1.linux-x86_64.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for autonvtx 0.1
File	Interpreter	ABI	Platform	Actions Reset
autonvtx-0.1-py3-none-any.whl 2.7 kB Dec 17, 2019 Without provenance	Python 3	none	any	Details for autonvtx-0.1-py3-none-any.whl

Total release size: 4.8 kB

Release files / autonvtx-0.1.linux-x86_64.tar.gz

Download URL	autonvtx-0.1.linux-x86_64.tar.gz
Size	2.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`25ae971a23af60f75a3eaea056434c4b7c5733124a1b2f7c6704a8dd12547e9d`
BLAKE2b-256 checksum How to use checksums	`5db4b176868ee80b2c47c9e4f58ffa26b764d33d74755ffebb55f237c987e23a`
Upload date	Dec 17, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.3`

Release files / autonvtx-0.1-py3-none-any.whl

Download URL	autonvtx-0.1-py3-none-any.whl
Size	2.7 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`b88ec5737e9858df34cf6fcf35a5ec5d361f613c2a79e0de96ec2d3b25409ed9`
BLAKE2b-256 checksum How to use checksums	`515bb0d2236d97612c08961b9ea20d6068dd2d58f7f1beba8698b85446ff8bee`
Upload date	Dec 17, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.3`

Security for autonvtx 0.1

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1 This release

Dec 17, 2019 2 release files No provenance

autonvtx 0.1