Challenge: Distributed Training with JAX and Flax
Explore the process of distributed training with JAX and Flax by loading a small image dataset, creating parallelized training functions using pmap, and applying models across multiple devices. Understand training and evaluation phases focused on accuracy metrics to manage image classification with cars and bikes.
We will perform distributed training using JAX and Flax in this challenge. We have imported all the necessary libraries for you.
Challenge 1: Load the dataset
In the /usr/local/notebooks directory, we have a dataset in a zipped folder, cars_and_bikes.zip, containing images from two classes: cars and bikes. There are ...