Agoge
An opinionated ML development environment
Train pytorch models, hyperparameter tune them with single loc change.
Libraries
Pytorch
Pytorch is a Python first machine learning library
Ray
Ray Provides easy experiment scaling + hyper parameter optimisation
Weights and Biases
Agoge uses WandB to monitor model training. It's super easy to setup, just go to the wandb website and sign up for an account. Then follow the instructions to set up
Static Components
These components should not need to be customised for model specific use cases
Train Worker
Setups all the required components to train a model
Inference Worker
Setups all the required components for inference. Also attempts to download model weights if they are not found locally.
Data Handler
Loads the dataset and handles the dataset split
User Provided Components
These components need to be inherited by project specific classes
Model
Provides some convenience functions around loading models. This class will hold all model specific code and is used by the train worker and inference workers
Solver
Override the solve method with the code required to train your model
Dataset
Any dataset that is compatiable with the Pytorch map style dataset model
Disclaimer
This code is subject to change. I will try not to break anything but can't promise. File an issue if an update breaks your code
Metadata
Release files for agoge 0.1.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| agoge-0.1.3.tar.gz | 7.2 kB | Without provenance | Details for agoge-0.1.3.tar.gz |
Release files / agoge-0.1.3.tar.gz
| Download URL | agoge-0.1.3.tar.gz |
|---|---|
| Size | 7.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ef4be176961e687bd523ae415c1e9ef1f2752130856f31d7c78a5a239d922a5a
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912b97fed5b1e33924bd82286e01c14535d0c3f6c83877df92e66e7c102f036f
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.0.post20200616 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.6.10
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Security for agoge 0.1.3
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