Chapter 4 of 6 · Huawei HCIA-AI H13-311
AI Development Framework
What AI frameworks do, tensors, graphs, autograd, PyTorch and the development process.
- 2topics
- 10 minfast track
- 20%of the exam
Topics in this chapter
Take them in order, or jump to the one you need.
- 1AI Frameworks and Development BasicsLearn what an AI framework provides, PyTorch, TensorFlow and MindSpore, tensors, static and dynamic graphs, autograd and GPU or…5 min
- 2PyTorch and AI Application DevelopmentLearn PyTorch nn.Module, losses, optimizers, DataLoader, the training loop, evaluation and saving, and the AI application…5 min
About this chapter
What this chapter covers
AI Development Framework is 20% of the Huawei HCIA-AI H13-311 exam. It covers what an AI framework does and which frameworks are mainstream, the core ideas every framework shares (tensors, computational graphs, automatic differentiation and hardware acceleration), PyTorch as the framework used in the V4.0 course, and the steps for developing an AI application.
Questions are single-answer, multiple-answer without a stated count, true/false and typed fill-in-the-blank, often "Which of the following statements is true?". This exam has no exhibit figures and no drag and drop, so every question is plain text.
It has 4 outline topics, and two pages cover them.
How the topics fit together
A framework hides the hard parts of deep learning: storing data as tensors, recording the computation as a graph, computing gradients automatically and running it all on GPUs or NPUs. PyTorch is one concrete framework, and the development process shows how you use it from data to a deployed model.
The first page explains the ideas shared by PyTorch, TensorFlow and MindSpore. The second page turns them into real PyTorch code and the workflow around it.
Know the difference between dynamic and static computational graphs. PyTorch builds the graph as the code runs (define by run), which makes debugging easy; a static graph is built first and then executed, which gives more room for optimization.
How to use these pages
Each topic page has the same shape, so you can skim for what you need.
- What it is: the idea in plain words.
- How it works: the mechanism, with tables and examples.
- What to remember for the exam: the facts to memorize.
- Common mistakes: the classic traps.
- Check yourself: three questions to test your understanding.
For every PyTorch call you meet, say which step of training it belongs to. The exam often asks about the order of zero_grad(), backward() and step().
Ready for more practice?
The full Huawei HCIA-AI H13-311 question bank has 600 questions, with timed practice exams and an explanation for every answer.
This study guide is independent and is not affiliated with, endorsed by, or sponsored by Huawei. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.