[Chore] Factor out logic for requesting initial memory (#30868)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/v1/worker/gpu_worker.py

@@ -56,6 +56,8 @@ from vllm.v1.worker.utils import is_residual_scattered_for_sp
 from vllm.v1.worker.worker_base import WorkerBase
 from vllm.v1.worker.workspace import init_workspace_manager
 
+from .utils import request_memory
+
 logger = init_logger(__name__)
 
 if TYPE_CHECKING:
@@ -237,22 +239,8 @@ class Worker(WorkerBase):
             torch.cuda.empty_cache()
 
             # take current memory snapshot
-            self.init_snapshot = MemorySnapshot()
-            self.requested_memory = (
-                self.init_snapshot.total_memory
-                * self.cache_config.gpu_memory_utilization
-            )
-            if self.init_snapshot.free_memory < self.requested_memory:
-                GiB = lambda b: round(b / GiB_bytes, 2)
-                raise ValueError(
-                    f"Free memory on device "
-                    f"({GiB(self.init_snapshot.free_memory)}/"
-                    f"{GiB(self.init_snapshot.total_memory)} GiB) on startup "
-                    f"is less than desired GPU memory utilization "
-                    f"({self.cache_config.gpu_memory_utilization}, "
-                    f"{GiB(self.requested_memory)} GiB). Decrease GPU memory "
-                    f"utilization or reduce GPU memory used by other processes."
-                )
+            self.init_snapshot = init_snapshot = MemorySnapshot(device=self.device)
+            self.requested_memory = request_memory(init_snapshot, self.cache_config)
         else:
             raise RuntimeError(f"Not support device type: {self.device_config.device}")