[Doc] [Serve] Add docs for custom resources with Serve

doc/source/serve/scaling-and-resource-allocation.md

@@ -123,6 +123,17 @@ def func_2(*args):
 
 In this example, each replica of each deployment will be allocated 0.5 GPUs.  The same can be done to multiplex over CPUs, using `"num_cpus"`.
 
+### Custom Resources
+
+You can also specify [custom resources](custom-resources) in `ray_actor_options`, for example to ensure that a deployment is scheduled on a specific node.
+For example, if you have a deployment that requires 2 units of the `"custom_resource"` resource, you can specify it like this:
+
+```python
+@serve.deployment(ray_actor_options={"resources": {"custom_resource": 2}})
+def func(*args):
+    return do_something_with_my_custom_resource()
+```
+
 (serve-omp-num-threads)=
 
 ## Configuring Parallelism with OMP_NUM_THREADS

python/ray/serve/api.py

@@ -317,7 +317,9 @@ def deployment(
             a '/' unless they're the root (just '/'), which acts as a
             catch-all.
         ray_actor_options: Options to be passed to the Ray actor
-            constructor such as resource requirements.
+            constructor such as resource requirements. Valid options are
+            `accellerator_type`, `memory`, `num_cpus`, `num_gpus`,
+            `object_store_memory`, `resources`, and `runtime_env`.
         user_config (Optional[Any]): Config to pass to the
             reconfigure method of the deployment. This can be updated
             dynamically without changing the version of the deployment and

python/ray/serve/config.py

@@ -390,7 +390,8 @@ def _validate_ray_actor_options(self) -> None:
                 f'Got invalid type "{type(self.ray_actor_options)}" for '
                 "ray_actor_options. Expected a dictionary."
             )
-
+        # Please keep this in sync with the docstring for the ray_actor_options
+        # kwarg in api.py.
         allowed_ray_actor_options = {
             # Resource options
             "accelerator_type",