Graph Neural Network Library for PyTorch. Contribute to pyg-team/pytorch_geometric development by creating an account on GitHub.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

We can now optimize the model in a training loop, similar to the standard PyTorch training procedure. importtorch. nn. functionalasFdata=dataset [0] optimizer=torch. optim.

PyTorch recreates the graph on the fly at each iteration step. In contrast, TensorFlow by default creates a single data flow graph, optimizes the graph code for performance, and then trains the model.

Dr. James McCaffrey of Microsoft Research continues his examination of creating a PyTorch neural network binary classifier through six steps, here addressing step No. 4: training the network.

PyTorch Lightning supports training by using multiple GPUs which helps AI researchers and ML Engineers extensively. Sharding of data across multiple GPUs help to accelerate the training process.