implicitlab

The neural implicit lab is a helper library built on top of pytorch for training implicit neural representations (INR) of geometrical objects. The goal of the library is to make the computation of an INR the ressemble a config file as much as possible and abstract away the data sampling, the training loop and the model definition, while remaining highly customizable.

The library is under construction. Expect heavy changes.

The documentation can be found here: https://GCoiffier.github.io/neural_implicit_lab/

Conventions

All input geometries are centered around zero and scaled down so that they fit inside [-1, 1]^n
By default, datasets of points are sampler inside the [-1.5, 1.5]^n domain

TODO list

Rely on meshio for faster geometry loading
Implement SAL and SALD
Setup the query module
Find a better name for the lib :)

Metadata

Release files for implicitlab 0.2

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Source distribution (sdist)

Source distribution for implicitlab 0.2
File	Size	Uploaded
implicitlab-0.2.tar.gz	41.8 kB	Aug 14, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for implicitlab 0.2
File	Interpreter	ABI	Platform	Reset
implicitlab-0.2-py3-none-any.whl 53.9 kB Aug 14, 2026	Python 3	none	any	Details

Total release size: 95.7 kB

Release files / implicitlab-0.2.tar.gz

Download URL	implicitlab-0.2.tar.gz
Size	41.8 kB
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SHA-256 checksum How to use checksums	`57ad4d6cce9f0178468b39c133b6721b9279ce02c0f239996d91f53f49162c9d`
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Uploaded via	`twine/7.0.0 CPython/3.13.14`

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Publishing platform: GitHub Actions
Publishing repository: github.com/GCoiffier/neural_implicit_lab
Publishing commit: github.com/GCoiffier/neural_implicit_lab/tree/8a21966a59258c1ac13c877a56d5964cb074f769

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Publishing configuration: github.com/GCoiffier/neural_implicit_lab/blob/8a21966a59258c1ac13c877a56d5964cb074f769/.github/workflows/python-publish.yml
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Subject: implicitlab-0.2.tar.gz
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Release files / implicitlab-0.2-py3-none-any.whl

Download URL	implicitlab-0.2-py3-none-any.whl
Size	53.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`91ec8230a4906d183e8b2baddf708259721f7451779b6cdd7b157be29ab1e308`
BLAKE2b-256 checksum How to use checksums	`8a0a2c86005fc554626763a89fafce6227457c12c6b56d1bfc148a5244f9f23c`
Upload date	Aug 14, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/GCoiffier/neural_implicit_lab
Publishing commit: github.com/GCoiffier/neural_implicit_lab/tree/8a21966a59258c1ac13c877a56d5964cb074f769

Workflow

Publishing configuration: github.com/GCoiffier/neural_implicit_lab/blob/8a21966a59258c1ac13c877a56d5964cb074f769/.github/workflows/python-publish.yml
Publishing logs: github.com/GCoiffier/neural_implicit_lab/actions/runs/31813540932/attempts/1

Artifact

Subject: implicitlab-0.2-py3-none-any.whl
SHA-256 checksum: 91ec8230a4906d183e8b2baddf708259721f7451779b6cdd7b157be29ab1e308 Verifying attestations