isaacai

This library is a work in progress to become a deep learning library for my own use.

The code in this library is heavily inspired by the miniai library developed as part of the part 2 course. I am writing the Deep Learning portions myself, but other parts of the library are taken directly from that library (ie memory cleaning functions, plotting helper functions, etc.). This is very much a work in progress at the very early/beginning stages. It’s not ready for practical use (yet!).

Install

Cone the repo and do an editable install. You will almost certainly need to modify the library as you use it given the early stages it is in.

pip install -e .[dev]

How to use

Minimal Example

Dataloaders

• Pytorch Datasets

Data Augmentation

Use Existing Augmentations

• Item vs Batch Aug
• CPU vs GPU Aug

Add New Augmentation

• Item vs Batch Aug
• CPU vs GPU Aug
• Random Erasing, torchvision, albumentations

Models

• Pytorch Model
• Timm Model
• HuggingFace Model
• Resnet

Metrics

• Create New Metric

Loss Functions

• Use Existing Loss Function
• Create Loss Function

Model Evaluations

• Plot Loss