Transformer from Scratch in TF Part 2: Encoder

This post provides a detailed, step-by-step explanation of the Transformer Encoder Block using TensorFlow, focusing on the Multi-Head Attention mechanism. It covers the creation of Queries, Keys, and Values, the Scaled Dot-Product Attention mechanism, and the addition of residual connections and Layer Normalization. The final component, the Feed-Forward Network (FFN), is also detailed. Code examples in TensorFlow are provided throughout to illustrate key concepts.