"Efficient Distributed Training with Determined AI"
0"Efficient Distributed Training with Determined AI" - This code showcases how the Determined AI platform can distribute the training process across multiple GPUs, allowing for faster and more efficient training of deep neural networks on large datasets such as CIFAR-10.
The code demonstrates how to use Determined AI to train a deep neural network on the CIFAR-10 dataset using distributed training. This project uses the CIFAR-10 dataset, a common benchmark dataset for image classification. The model architecture is a convolutional neural network that consists of two convolutional layers, max-pooling layers, and two fully connected layers. The data loader function preprocesses the data and creates TensorFlow Datasets for training and validation. The training function uses the Determined AI library to distribute the training across multiple GPUs using the TensorFlow backend.