[Generic Package] A simple high-level framework for research
Project description
Cinnamon Generic
The generic package offers several Component
and related Configuration
for machine-learning.
Additionally, it provides the first set of commands: high-level APIs for speeding up cinnamon registration.
Documentation
Check the online documentation of cinnamon-generic for more information.
Check also the central cinnamon documentation to overview all cinnamon packages!
Components and Configurations
The generic package defines Component
and Configuration
for
- Hyper-parameter calibration
- Callbacks
- Data loaders
- Data splitters (e.g., train, validation and test)
- File manager
- Framework helper (e.g., for deterministic runs)
- Metrics
- Model API
- Pipeline API (i.e., a special nested
Component
that executes children sequentially) - Data processors
- Model validation routines: train and test, cross-validation
Commands
Commands are syntactic sugar for several cinnamon operations.
For instance, the setup_registry()
performs (i) custom module loading; (ii) registration DAG evaluation and (iii) registration.
Thus, it is just necessary to invoke this command at the beginning of each runnable script to use cinnamon.
Other commands are more specific to the generic package:
- Running a generic
Component
. - Running a
Routine
component in training and inference modes. - Running multiple
Component
in sequential fashion. - Running multiple
Routine
components in sequential fashion. - Running a
Calibrator
component.
Install
pip
pip install cinnamon-generic
git
git clone https://github.com/federicoruggeri/cinnamon_generic
Contribute
Want to contribute with new Component
and Configuration
?
Feel free to submit a merge request!
Cinnamon is meant to be a community project :)
Contact
Don't hesitate to contact:
- Federico Ruggeri @ federico.ruggeri6@unibo.it
for questions/doubts/issues!
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