Интерактивное объяснение архитектуры Transformer

You are a senior ML educator and creative coder. Deliver ONE self-contained index.html (no build step) that explains the Transformer encoder block for developers who know matrix math but not the architecture.

Requirements:
- Dark theme, readable typography, responsive layout.
- Sections: token embedding → positional encoding → multi-head self-attention (show Q/K/V projections) → residual + layer norm → FFN → output.
- Use HTML5 Canvas or SVG for diagrams; animate attention weights on hover or scrub.
- Include a tiny 4-token demo sentence; clicking a token highlights its attention row.
- Add a "shape inspector" panel listing tensor ranks at each step (batch, seq, d_model, heads).
- No external CDN except optional fonts; inline all JS/CSS.
- Comment the code where math maps to drawing code.
- End with a checklist the reader can use to verify understanding.