Comments (8)
Hey @pfebrer,
That is a reasonable solution. Could you try it and check if it solves your issues?
from mace.
It indeed solved the problem, my checkpoint files size has been reduced from 680 MB to 26 MB :) I could also restart the training without problems.
But maybe in some case it is useful to store them precomputed?
from mace.
I now noticed that this change breaks compatibility with loading models.
E.g.: if you load a model that stored the U matrices in a version of mace that has them set to persistent=False
this will result in an error. And the same happens in the opposite case.
from mace.
I now noticed that this change breaks compatibility with loading models.
E.g.: if you load a model that stored the U matrices in a version of mace that has them set to
persistent=False
this will result in an error. And the same happens in the opposite case.
This could maybe be fixed with non-strict loading. The torch load function has a keyword strict=False
, but it might be better to just break the backwards compatibility or explicitly remove the U matrices from old checkpoints.
from mace.
@ilyes319 do you think you can make them persistent=False
? To load an old model on the new implementation it would just be a matter of "cleaning" the checkpoint file, i.e. removing the matrices from it.
from mace.
I wonder how this interacts with torchscript though and libtorch. I guess the safest would be to make an argument and keep the default to true. Would this alright?
from mace.
Yes, if it can be configured from an argument of the SymmetricContraction
module (not just Contraction
) I think it would be fine for us 👍
from mace.
Could we add this? :) (a persistent_U_matrices
or something similar argument to SymmetricContraction
that defaults to True
)
I can submit a PR.
from mace.
Related Issues (20)
- Restart of the training using --restart_latest doesn't properly work - resolved -
- Deployment of the MACE Model Without Using ASE HOT 5
- Error while using multihead interface HOT 2
- Segmentation fault during LAMMPS-MACE-CPU run HOT 1
- Problems with parallelization on CPU (Using LAMMPS) HOT 1
- Improve plotting script
- Automatically add parameters to optimizer
- Change stress to virials internally
- ASE documentation update? HOT 4
- Move to ruff for linting and formating? HOT 3
- Tripeptides Data for MACE-OFF Model
- Bug on loading finetuning model HOT 2
- Remove `e3nn` version pin HOT 2
- models created from multihead fine tuning don't work in lammps HOT 6
- universal loss (at least in multi-head-interface branch) does not support per-config weight
- cannot turn off multihead finetuning in multi-head-interface branch HOT 17
- Colab Tutorial Link Does not work HOT 2
- help message for `--pair_repulsion` is wrong HOT 1
- How to use multi-GPUs training with PBS system HOT 20
- [feature suggest] active learning in lammps
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from mace.