Use NCCL instead of ray for control-plane communication to remove serialization overhead (#2221)

docs/source/models/adding_model.rst

@@ -58,11 +58,10 @@ Next, you need to rewrite the :code:`forward` methods of your model by following
     +    positions: torch.Tensor,
     +    kv_caches: List[KVCache],
     +    input_metadata: InputMetadata,
-    +    cache_events: Optional[List[torch.cuda.Event]],
-    +) -> SamplerOutput:
+    +) -> Optional[SamplerOutput]:
 
-3. Update the code by considering that :code:`input_ids` and :code:`positions` are now flattened tensors.
-4. Replace the attention operation with either :code:`PagedAttention`, :code:`PagedAttentionWithRoPE`, or :code:`PagedAttentionWithALiBi` depending on the model's architecture.
+1. Update the code by considering that :code:`input_ids` and :code:`positions` are now flattened tensors.
+2. Replace the attention operation with either :code:`PagedAttention`, :code:`PagedAttentionWithRoPE`, or :code:`PagedAttentionWithALiBi` depending on the model's architecture.
 
 .. note::
     Currently, vLLM supports the basic multi-head attention mechanism and its variant with rotary positional embeddings.