agoge


Nameagoge JSON
Version 0.1.3 PyPI version JSON
download
home_pagehttps://github.com/nintorac/agoge
SummaryMachine Learning infra
upload_time2020-07-06 07:12:14
maintainer
docs_urlNone
authorNintorac
requires_python
licenseMIT
keywords pytorch machine learning
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Agoge

An opinionated ML development environment

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


## Libraries

### Pytorch

[Pytorch](https://pytorch.org/) is a Python first machine learning library 

### Ray

[Ray](https://ray-project.github.io/) 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](https://www.wandb.com/) 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](https://pytorch.org/docs/stable/data.html#map-style-datasets)


# 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
            

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