- New CudaGraphContext class: warmup -> capture -> replay lifecycle
- One graph per batch_size key, all inputs at fixed workspace addresses
- Added position_ids buffer to InferenceWorkspace (required for graph capture)
- Graph only activates when CUDA backend is the current backend
- Default off (opt-in) due to slight numerical divergence in graph replay
- Sampling stays outside the graph (torch.multinomial uses mutable RNG)
- Resolved circular import: KVCache -> TYPE_CHECKING in attention_backend.py
