[feat] Enable Ascend profiling on SGLang (#8610)

Co-authored-by: liyou_b <2953090824@qq.com>

python/sglang/srt/managers/scheduler_profiler_mixin.py

@@ -8,6 +8,18 @@ import torch
 
 from sglang.srt.managers.io_struct import ProfileReq, ProfileReqOutput, ProfileReqType
 from sglang.srt.model_executor.forward_batch_info import ForwardMode
+from sglang.srt.utils import is_npu
+
+_is_npu = is_npu()
+if _is_npu:
+    import torch_npu
+
+    patches = [
+        ["profiler.profile", torch_npu.profiler.profile],
+        ["profiler.ProfilerActivity.CUDA", torch_npu.profiler.ProfilerActivity.NPU],
+        ["profiler.ProfilerActivity.CPU", torch_npu.profiler.ProfilerActivity.CPU],
+    ]
+    torch_npu._apply_patches(patches)
 
 logger = logging.getLogger(__name__)
 
@@ -136,6 +148,13 @@ class SchedulerProfilerMixin:
                 activities=torchprof_activities,
                 with_stack=with_stack if with_stack is not None else True,
                 record_shapes=record_shapes if record_shapes is not None else False,
+                on_trace_ready=(
+                    None
+                    if not _is_npu
+                    else torch_npu.profiler.tensorboard_trace_handler(
+                        self.torch_profiler_output_dir
+                    )
+                ),
             )
             self.torch_profiler.start()
             self.profile_in_progress = True
@@ -166,15 +185,16 @@ class SchedulerProfilerMixin:
         logger.info("Stop profiling" + stage_suffix + "...")
         if self.torch_profiler is not None:
             self.torch_profiler.stop()
-            self.torch_profiler.export_chrome_trace(
-                os.path.join(
-                    self.torch_profiler_output_dir,
-                    self.profile_id
-                    + f"-TP-{self.tp_rank}"
-                    + stage_suffix
-                    + ".trace.json.gz",
+            if not _is_npu:
+                self.torch_profiler.export_chrome_trace(
+                    os.path.join(
+                        self.torch_profiler_output_dir,
+                        self.profile_id
+                        + f"-TP-{self.tp_rank}"
+                        + stage_suffix
+                        + ".trace.json.gz",
+                    )
                 )
-            )
             torch.distributed.barrier(self.tp_cpu_group)
 
         if self.rpd_profiler is not None: