Comments (18)
In GitLab by @RandomDefaultUser on Jan 27, 2021, 11:56
I've notices the NaN errors as well. This seems to come from the correlation calculation when some values of the jacobian are very small. Might be helpful to introduce some offset there, moving all values away a bit from zero.
Also the size of the correlation matrix scales square with the batch size (unsurprisingly), so expect seriously degraded performance with larger batch sizes - For the example data Batch sizes >>1000 quickly meant that actually training the network was faster than calculating the surrogate metric.
By Nils-Hoffmann on 2021-01-27T11:56:55 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Jan 26, 2021, 15:49
https://arxiv.org/abs/2006.04647: This is the paper Nils' implementation is based upon.
By Fiedler, Lenz (FWU) - 146409 on 2021-01-26T15:49:34 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:18
Asignees: Parvez, Nils
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:18:12 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Jan 26, 2021, 16:18
Some notes for the merge:
- there's a spurious NaN error that sometimes occurs when running Nils' implementation after applying the validation loss fix. Investigate that
- Parvez' implementation needs to install the oapackage and for that needs SWIG, add that to the requirements.
By Fiedler, Lenz (FWU) - 146409 on 2021-01-27T11:56:55 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Jan 28, 2021, 10:21
Yes I have also tracked it down to the correlation calculation and small values. It would definitely be interesting to test some sort of offset there, because values close to zero will be kind of common I think.
The batch size dependence is very interesting! That is sort of inverse to regular hyperparameter optimization on GPUs for which larger batch sizes are generally very beneficial.
By Fiedler, Lenz (FWU) - 146409 on 2021-01-28T10:21:57 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Feb 3, 2021, 18:06
I refactored the @Nils-Hoffmann and @Zevrap-81 code a bit do be more consistent in use with the rest of the code. I am doing a final test on hemera and should that be successful I am closing this issue and addin new, more fine grained issues for the other things we want to investigate/fix in the context of Hyperparameter optimization.
By Fiedler, Lenz (FWU) - 146409 on 2021-02-03T18:19:44 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Feb 3, 2021, 18:19
Sounds great! The investigation of both "NAS without training" and "orthogonal arrays" on a real-world dataset will be very interesting.
By Cangi, Dr. Attila (FWU) - 139621 on 2021-02-03T18:19:44 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Feb 4, 2021, 11:41
Final tests were successful, I am running the first bigger test for the NAS without training and will create an application issue for further hyperparameter calculations.
By Fiedler, Lenz (FWU) - 146409 on 2021-02-04T11:41:45 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 09:31
changed the description
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T09:31:13 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 09:50
changed the description
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T09:50:21 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 11:32
changed the description
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T11:32:09 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 11:51
assigned to @Nils-Hoffmann
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T11:51:35 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:14
assigned to @Nils-Hoffmann and unassigned @Zevrap-81
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:14:51 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:14
assigned to @Nils-Hoffmann and unassigned @fiedle09
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:14:32 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:13
assigned to @Zevrap-81 and unassigned @Nils-Hoffmann
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:13:37 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:14
assigned to @Nils-Hoffmann and unassigned @Zevrap-81
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:14:06 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:14
assigned to @fiedle09 and unassigned @Nils-Hoffmann
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:14:26 (imported from GitLab)
from mala.
In GitLab by @RandomDefaultUser on Dec 21, 2020, 12:14
assigned to @Zevrap-81 and unassigned @Nils-Hoffmann
By Fiedler, Lenz (FWU) - 146409 on 2020-12-21T12:14:42 (imported from GitLab)
from mala.
Related Issues (20)
- Update MALA logos
- Zero validation data loss during hyperparameter optimization HOT 1
- GPU Graphs fail when used with batch size that is not divisor of data set size
- Optuna v3.x.x no longer compatible with zombie trial cleaning HOT 2
- Adopt a code formatting standard HOT 4
- SNAP data overwritten for simultaneous pre-processing in same directory HOT 1
- Unused imports HOT 2
- Code duplications in `predictor.py` HOT 1
- Issue creating an arbitrary number of snapshots HOT 1
- Avoid CI runs when PR is still in "draft" mode HOT 2
- Optuna resume workflow overhaul
- Remove old container images from package registry HOT 1
- Use tempfile to handle LAMMPS and QE temporary files
- Align Python versions througout MALA
- New containers are added to the registry, which should not actually be different
- Clean up cache entires after successfull merge of PR HOT 2
- Remove potentially obsolete step in CI CPU test workflow HOT 1
- Make OpenPMD consistent HOT 1
- Improve CI with regards to data repo updates HOT 3
- Delete caches after pushes tp `develop`, `master` etc.
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 mala.