Library designed for enhancing productivity for AI developers

Introduction

This is a comprehensive library designed to facilitate various machine learning projects using PyTorch. It provides essential functionalities such as custom layers, dataset handling, and utility functions for model training and visualization.

Features

• Custom layers for pixel normalization and upsampling/downsampling.
• Convenient data transformation and augmentation functions.
• Custom dataset class for handling image datasets.
• Utility functions for model initialization, visualization, and more.

Installation

This tool requires Python. Use this command to install the library:

pip install polip

Required Libraries for Visualization

Make sure to install the following required libraries:

pip install matplotlib os torch PIL numpy torchvision

Usage

Custom Layers

The library includes custom layers like PixelNormLayer, UpSample, and DownSample. Here's an example of how to use them:

from polip.cb import PixelNormLayer, UpSample, DownSample

Custom Image Dataset

You can use the CustomImageDataset class to handle image datasets:

from polip import CustomImageDataset, get_rgb_transform