fix CUDAGraph memory being counted twice (#37426)

Signed-off-by: Peter Pan <Peter.Pan@daocloud.io>
Signed-off-by: Peter Pan <peter.pan@daocloud.io>
Co-authored-by: Matthew Bonanni <mbonanni@redhat.com>

vllm/v1/worker/gpu_worker.py

@@ -417,9 +417,7 @@ class Worker(WorkerBase):
         )
 
         self.non_torch_memory = profile_result.non_torch_increase
-        self.peak_activation_memory = (
-            profile_result.torch_peak_increase + cudagraph_memory_estimate_applied
-        )
+        self.peak_activation_memory = profile_result.torch_peak_increase
         self.cudagraph_memory_estimate = cudagraph_memory_estimate
 
         free_gpu_memory = profile_result.after_profile.free_memory
@@ -638,6 +636,7 @@ class Worker(WorkerBase):
             # slightly underestimate the memory consumption.
             # So leave a small buffer (=150MiB) to avoid OOM.
             redundancy_buffer_memory = 150 * (1 << 20)
+
             non_kv_cache_memory = (
                 self.model_runner.model_memory_usage
                 + self.peak_activation_memory