Demo note. This note demonstrates what the SciDraft Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct. A project that produces a paper has to keep three kinds of thing apart that are easy to mix: the installed source, the outputs of individual runs, and the material the paper is written from. Once several sweeps and a performance benchmark live in the same repository, the folder structure is what decides whether a figure can be traced back to the run that produced it. ...
Project Layout
Layout of a Small Numeric Experiment (starter folder structure)
Demo note. This note demonstrates what the SciDraft Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct. The smallest useful project around a piece of neural-network mathematics holds one idea per file and keeps the generated numbers out of the code. Nothing in it is conventional yet: a starter folder is decided by what you want to compare next, not by what a template says. ...
Layout of a Trainable Model (intermediate folder structure)
Demo note. This note demonstrates what the SciDraft Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct. Once a model trains, the folder structure has a second job: it has to separate what changes per run from what changes per idea. Configurations and checkpoints belong to a run; attention code, data preparation and the training loop belong to the project, and the split is what lets a result be reproduced from a config file plus a commit rather than from memory. ...