Library for faster pinned CPU <-> GPU transfer in Pytorch

PyTorch tutorial notebooks for beginners.

Evaluation of multiple graph neural network models—GCN, GAT, GraphSAGE, MPNN and DGI—for node classification on graph-structured data. Preprocessing includes feature normalization and adjacency-matrix regularization, and an ensemble of model predictions boosts performance. The best ensemble achieves 83.47% test accuracy.

Optimizing PyTorch Model Training by Wrapping Memory Mapped Tensors on Nvidia GPUs with TensorDict.

Optimizing PyTorch Model Training by Wrapping Memory Mapped Tensors on an Nvidia GPU with TensorDict.

PyTorch is a popular open-source machine learning library that provides tools for building and training neural networks. One of the key features of PyTorch is its ability to automatically compute gradients for tensor operations, which is essential for efficient training of neural networks.

NeuralForge: Complete Transformer architecture from scratch using only PyTorch tensors. Learn how Transformers really work with clean, production-ready code.