torch-batteries 0.5.1

A lightweight Python package that supplies batteries-included abstractions for PyTorch workflows

torch-batteries

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A lightweight Python package that supplies batteries-included abstractions for:

• Data loading pipelines
• Model training loops
• Evaluation workflows
• Metrics computation
• Experiment tracking (Weights & Biases)

Designed to reduce boilerplate and standardize experiment code.

Installation

pip install torch-batteries

Optional Dependencies

For experiment tracking with Weights & Biases:

pip install torch-batteries[wandb]

Examples

Explore practical examples demonstrating torch-batteries features:

Example	Description	Notebook	Colab
Function Fitting with MLP	Train a neural network to approximate a polynomial function using the event-driven training approach	function_fitting.ipynb
Image Classification with CNN	Train a Convolutional Neural Network (CNN) for image classification	image_classification.ipynb
Learning Rate Sweep with Early Stopping	Conduct a learning rate sweep on MNIST classification with aggressive early stopping and log results to Weights & Biases	lr_sweep_early_stopping.ipynb