Explanation: Why Transformers Use LayerNorm Instead of BatchNorm? (Necessity of Engineering Without Equations)
Published:Dec 17, 2025 01:59
•1 min read
•Zenn DL
Analysis
The article addresses a common interview question in Deep Learning: why Transformers use Layer Normalization (LN) instead of Batch Normalization (BatchNorm). The author, an AI researcher, expresses a dislike for this question in interviews, suggesting it often leads to rote memorization rather than genuine understanding. The article's focus is on providing an explanation from a practical, engineering perspective, avoiding complex mathematical formulas. This approach aims to offer a more intuitive and accessible understanding of the topic, suitable for a wider audience.
Key Takeaways
- •The article aims to explain the choice of LayerNorm in Transformers from an engineering perspective.
- •It avoids complex mathematical formulas, focusing on practical considerations.
- •The author dislikes the question in interviews, suggesting it often leads to memorization.
Reference
“The article starts with the classic interview question: "Why do Transformers use LayerNorm (LN)?"”