Implement "Attention is all you need"

A comprehensive tutorial on implementing the Transformer architecture from the groundbreaking "Attention is All You Need" paper using PyTorch. Covers the complete implementation including multi-head attention mechanisms, encoder-decoder structure, positional encoding, and feed-forward networks. Explains key components like self-attention with the Q, K, V formula, masked attention for decoders, and the training process using teacher forcing. Demonstrates how the architecture works for sequence-to-sequence tasks like machine translation, with detailed explanations of both training and inference phases.