CourseTransformers: From Attention to Trained, Served and Interpreted Models · Module 3: The Transformer Block · part 22 of 111
Part 22 · Module 3: The Transformer Block

Lesson 2: The residual stream, where every layer adds its part

26 min read·13 Oct 2026
Module 3 · Lesson 2 · About 45 minutes · Needs: Module 3, Lesson 1 (ModelConfig, FeedForward); Module 2, Lessons 4 and 5 (masks, GroupedQueryAttention)

The situation

Sol 406 at Aurora Station. Kofi Mensah reads shared block 17: x = x + self.attn(self.norm1(x)). "Why add? If every layer only adds, which one did the work? Show me what breaks without the plus sign."

This lesson assembles the block for tinyformer/model.py, measures what each part writes, and removes the plus sign. The running example is lines 3 and 4 of Ana Dubois's log for sol 286 (Lesson 1's log): 101 characters ending "Ana noted that pressure held steady."

The rest of this course is yours to keep

This course is bought on its own, once, and stays readable afterwards, including the parts added to it later.