# omni-learn
This repo contains a framework for various machine learning and simulation projects.
## Installation
Run pip install . while in this dir to install package.
### Environment Variables
It is strongly encouraged to set a few environment variables when using this library:
OMNILEARN_SAVE_DIR=”$HOME/trained_nets” - set this to an absolute path to a directory you have write access to, this is where scripts will save output (by default).
OMNILEARN_DATA_DIR=”$HOME/local_data” - set this to an absolute path to a directory with some datasets (best to also have write access to allow automatic downloading of some datasets).
## Execution
For an example of how to use this library, see the mnist/ dir.
An example execution from inside the mnist/ dir (requires the environment variables above to be set):
python project.py model –name test-mnist
1 maintainer
Metadata
1 maintainer
Release files for omnilearn 0.5.14
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| omnilearn-0.5.14.tar.gz | 130.1 kB | Details |
Release files / omnilearn-0.5.14.tar.gz
| Download URL | omnilearn-0.5.14.tar.gz |
|---|---|
| Size | 130.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
55bf876eb9138d1bdea5f7dc4d243e77f60e69dbf15c56be4aa361827f10292f
|
|
BLAKE2b-256 checksum How to use checksums |
97692f4a26feb0896267c399482b4c5b9213998285989d8e5acefce48c8719a5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.6.13
|
