refactor: move planner arg validation to planner_core for better cohesion

Signed-off-by: Daiyaan <darfeen@nvidia.com>

Author: daiyaanarfeen

components/src/dynamo/planner/planner_sla.py

@@ -18,10 +18,7 @@
 
 from pydantic import BaseModel
 
-from dynamo.planner.utils.planner_argparse import (
-    create_sla_planner_parser,
-    validate_planner_args,
-)
+from dynamo.planner.utils.planner_argparse import create_sla_planner_parser
 from dynamo.planner.utils.planner_core import start_sla_planner
 from dynamo.runtime import DistributedRuntime, dynamo_worker
 
@@ -38,19 +35,12 @@ class RequestType(BaseModel):
 
 @dynamo_worker()
 async def init_planner(runtime: DistributedRuntime, args):
-    # Validate args
-    validate_planner_args(args)
-
-    component = runtime.namespace(args.namespace).component("Planner")
-
-    # Planner always runs its observation/prediction/decision loop
-    # In local mode: executes scaling directly via KubernetesConnector
-    # In delegating mode: sends scale requests to GlobalPlanner
     await asyncio.sleep(INIT_PLANNER_START_DELAY)
 
     await start_sla_planner(runtime, args)
 
-    # Serve dummy generate endpoint
+    component = runtime.namespace(args.namespace).component("Planner")
+
     async def generate(request: RequestType):
         """Dummy endpoint to satisfy that each component has an endpoint"""
         yield "mock endpoint"