Distributed training code

In this section, we will learn how to write code to perform distributed training using the PyTorch framework for vision-based deep learning algorithms. We will be using Python code to create the model and then train it with a compute cluster. All the code is available in this book’s GitHub repository for learning and execution purposes.

Creating a training job Python file to process

Follow these steps to create a dataset while leveraging the user interface:

1. Go to https://ml.azure.com and select your workspace.
2. Go to Compute and click Start to start the compute instance.
3. Wait for the compute instance to start; then, click Jupyter to start coding.
4. If you don’t have a compute cluster, please follow the instructions in the previous chapters to create a new one. A compute instance with a CPU is good for development; we will use GPU-based content for model training.
5. If you don’t have enough quotas for your GPU,...