[Doc] Update help text for --distributed-executor-backend (#10231)

Signed-off-by: Russell Bryant <[email protected]>

vllm/config.py

@@ -951,9 +951,12 @@ class ParallelConfig:
             https://docs.ray.io/en/latest/ray-observability/user-guides/profiling.html#profiling-nsight-profiler.
         placement_group: ray distributed model workers placement group.
         distributed_executor_backend: Backend to use for distributed model
-            workers, either "ray" or "mp" (multiprocessing). If either
-            pipeline_parallel_size or tensor_parallel_size is greater than 1,
-            will default to "ray" if Ray is installed or "mp" otherwise.
+            workers, either "ray" or "mp" (multiprocessing). If the product
+            of pipeline_parallel_size and tensor_parallel_size is less than
+            or equal to the number of GPUs available, "mp" will be used to
+            keep processing on a single host. Otherwise, this will default
+            to "ray" if Ray is installed and fail otherwise. Note that tpu
+            and hpu only support Ray for distributed inference.
     """
 
     def __init__(

vllm/engine/arg_utils.py

@@ -369,9 +369,14 @@ def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
             '--distributed-executor-backend',
             choices=['ray', 'mp'],
             default=EngineArgs.distributed_executor_backend,
-            help='Backend to use for distributed serving. When more than 1 GPU '
-            'is used, will be automatically set to "ray" if installed '
-            'or "mp" (multiprocessing) otherwise.')
+            help='Backend to use for distributed model '
+            'workers, either "ray" or "mp" (multiprocessing). If the product '
+            'of pipeline_parallel_size and tensor_parallel_size is less than '
+            'or equal to the number of GPUs available, "mp" will be used to '
+            'keep processing on a single host. Otherwise, this will default '
+            'to "ray" if Ray is installed and fail otherwise. Note that tpu '
+            'and hpu only support Ray for distributed inference.')
+
         parser.add_argument(
             '--worker-use-ray',
             action='store_true',