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Machine Learning infra

Project description


An opinionated ML development environment

Train pytorch models, hyperparameter tune them with single loc change.



Pytorch is a Python first machine learning library


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


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


Override the solve method with the code required to train your model


Any dataset that is compatiable with the Pytorch map style dataset model


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

Project details

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agoge-0.1.3.tar.gz (7.2 kB view hashes)

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