[ROCm][CI] Fix cuda graph mem profile issue

vllm/v1/worker/gpu_model_runner.py

@@ -120,6 +120,7 @@
 from vllm.utils.torch_utils import (
     PIN_MEMORY,
     async_tensor_h2d,
+    current_stream,
     get_dtype_size,
     is_quantized_kv_cache,
     kv_cache_dtype_str_to_dtype,
@@ -6608,17 +6609,19 @@ def profile_cudagraph_memory(self) -> int:
         per_graph_estimate = {}
         encoder_memory_estimate = 0
 
-        # On ROCm, capture these throwaway profiling graphs on the current stream
-        # instead of the fresh side stream graph_capture() allocates by default.
-        # torch's allocator pools free blocks per stream, so a side-stream forward
-        # strands a persistent aiter scratch buffer in a separate pool, shifting
-        # the physical placement of the real KV cache allocated afterward and
-        # slowing bandwidth-bound decode ~20%. The graphs are discarded, so a
-        # side stream is unnecessary here.
-        # cap_ctx=None keeps the side-stream path on CUDA, where the current
-        # stream is the legacy default stream, on which capture cannot begin.
+        # On ROCm, capture these throwaway profiling graphs on vLLM's dedicated
+        # compute stream instead of the fresh side stream graph_capture()
+        # allocates by default. torch's allocator pools free blocks per stream,
+        # so a side-stream forward strands a persistent aiter scratch buffer in
+        # a separate pool, shifting the physical placement of the real KV cache
+        # allocated afterward and slowing bandwidth-bound decode ~20%. The
+        # graphs are discarded, so a side stream is unnecessary here.
+        # Use current_stream(), not torch.cuda.current_stream(): before vLLM
+        # initializes its dedicated stream, torch returns the per-thread default
+        # stream (cuda_stream=0), which cannot be used for cudagraph capture.
+        # cap_ctx=None keeps the side-stream path on CUDA.
         cap_ctx = (
-            GraphCaptureContext(torch.cuda.current_stream(self.device))
+            GraphCaptureContext(current_stream())
             if current_platform.is_rocm()
             else None
         )