Your question is Attention Mechanisms in Transformers. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain how the attention mechanism works in transformers.
Discuss query, key, and value projections, scaled dot-product attention, softmax weighting, multi-head attention, masking, positional information, and the role of attention within a transformer block. Include a concise PyTorch implementation and explain how you would validate its correctness. Address computational complexity and the difference between self-attention and cross-attention.