ML-Mnemonist is an open-source lightweight framework for simple ML operations and it pairs up easily with free online cloud services that do not support session backup and recovery because the framework implements these in the hardware level. To that end, some of the tutorials here are purposefully created to work with Google Colab. <p align=”center”> <img src=”/figures/logo.png”/> </p>
Check out more information on the GitHub <a href=”https://github.com/HamidrezaKmK/ML-Mnemonist”>repository</a>.
Change Log
0.1.0 (20.11.2022)
Tutorial 2 is finalized
Code for hyper experiment runners is refactored
Now we are able to adjoint single experiments with hyper experiment runners
Each experiment will create outputs under the hyper experiment directory
The hyper experiment directory will output all the experiment output scores in a json.
0.0.15 (19.7.2022)
Internal functionalities of Experiment Runner changed
Creating new experiments with the same name overwrites the previous experiment with the same name rather than creating new ones
The caching scheme for meta parameters had a bug which is fixed
The Tutorial is finalized
0.0.14 (19.7.2022)
Add exception handler to hyper experiments for conflicting configs
0.0.13 (01.7.2022)
Bug removal in configurations of the factory
Bug removal in readme
0.0.12 (01.7.2022)
Biggest update yet!
Introduce HyperExperiments!
When retrieving using factory, the pipelines will also be handled
Caching system updated, META_DATA cache added
0.0.11 (01.7.2022)
Grid search can now continue on the runner’s last interrupt
0.0.10 (01.7.2022)
With preprocess added to gridsearch
merge_cfg added to ExperimentRunner
0.0.9 (01.7.2022)
Grid search bug removal
Implement two types of grid search: one using a palette config and another using a directory containing all the config files
Retrieve added to ExperimentRunnerFactory
Updated naming scheme for experiments such that each experiment has a description file and their name contains the date of today
0.0.8 (01.7.2022)
Bug removal in validation tools
0.0.7 (01.7.2022)
Add expand_cfg for hyperparameter tuning
Add gridsearch for hyperparameter tuning
Change cache token scheme
0.0.6 (29.6.2022)
Bug removal in CACHE.RESET() where directories are included in the logs
Runner pipeline cloning option added
preprocess does keep the pipeline by default
0.0.5 (24.6.2022)
Add reload_cfg before each call of runner.run
Add reload_cfg before each call of runner.preprocess
Add runner.export_logs() method to get a zip file from all logfiles in the experiment directory
0.0.4 (23.6.2022)
Add more logs for verbose runners
Add CACHE.LOGS_DIR to save logs such as tensorboard
Add maximum cache limit that can be manipulated using mlm.MAX_CACHE_SIZE
0.0.3 (23.6.2022)
README updated
full support without configurations
secret_root added to factory and reveal_true_path
0.0.2 (23.6.2022)
Bug removal of some initial problems with the setup
0.0.1 (23.6.2022)
First release
1 maintainer
Metadata
1 maintainer
Release files for mlmnemonist 0.1.0
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