Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/x-raylaser/torchassistant
A deep learning framework and automation tool built on top of PyTorch
https://github.com/x-raylaser/torchassistant
artificial-neural-networks automation deep-learning machine-learning neural-networks pytorch pytorch-tool utilities
Last synced: 1 day ago
JSON representation
A deep learning framework and automation tool built on top of PyTorch
- Host: GitHub
- URL: https://github.com/x-raylaser/torchassistant
- Owner: X-rayLaser
- License: mit
- Created: 2022-06-03T05:16:50.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-01-12T11:56:59.000Z (almost 2 years ago)
- Last Synced: 2024-12-15T22:37:05.816Z (7 days ago)
- Topics: artificial-neural-networks, automation, deep-learning, machine-learning, neural-networks, pytorch, pytorch-tool, utilities
- Language: Python
- Homepage:
- Size: 464 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Introduction
**TorchAssistant** is a deep learning framework built on top of **PyTorch**.
It provides a set of tools to automate the training and evaluation of models.
It also reduces the amount of trivial code one usually needs to write.
Just create a specification file configuring the training session and let
the framework do everything else for you.
Main features:
- scripts for training, evaluation, and inference
- automatically calculating metrics
- automatically saving training session
- resuming the interrupted training session
- automatically saving metrics history to CSV files
- nicely formatted information about the training session: epoch, iteration, loss, metrics, etc.
- highly flexible and customizable
- support for building complex training pipelines
# Status: Early development stage
This project is in the early stage of development.
Features and functionality provided here are subject to change.
Furthermore, the code is not yet extensively tested and may contain bugs.
# Prerequisites
This project has dependencies that require separate installation:
- PyTorch (version >= 1.10.1, < 2.0)
- Torchvision (version >= 0.11.2, < 0.12)
- TorchMetrics (version >= 0.7.2 < 0.8)
When possible, try to follow the recommended version range specified in parentheses.
You can install PyTorch and Torchvision together from
[here](https://pytorch.org/get-started/locally/).
And you can install TorchMetrics from
[here](https://torchmetrics.readthedocs.io/en/stable/pages/quickstart.html).
# Installation
```
pip install torchassistant
```
# Examples
The examples directory contains projects that demonstrate how to use
TorchAssistant to train different kinds of neural networks.
# Documentation
You can find all the documentation for the project
[here](https://github.com/X-rayLaser/TorchAssistant/wiki).
# License
This project has an MIT license.