adapt to vllm-ascend v0.18.0rc1

vllm_ascend/patch/platform/patch_executor.py

@@ -0,0 +1,52 @@
+import time
+
+from vllm.v1.executor.abstract import logger, Executor
+
+
+def is_offloaded(self) -> bool:
+    if not hasattr(self, "_is_offloaded"):
+        self._is_offloaded = False
+    return self._is_offloaded
+
+def offload_vram(self):
+    if self.is_offloaded():
+        logger.warning("Executor is already offloaded.")
+        return
+    time_before_offload = time.perf_counter()
+    self.collective_rpc("offload_vram")
+    time_after_offload = time.perf_counter()
+
+    self._is_offloaded = True
+    logger.info(f"Offloading VRAM costs {time_after_offload - time_before_offload:.6f} seconds.")
+
+
+def reload_vram(self) -> bool:
+    if not self.is_offloaded():
+        logger.warning("Executor is not offloaded.")
+        return True
+
+    while True:
+        time_before_reload = time.perf_counter()
+        res = self.collective_rpc("try_reload_vram")
+        time_after_reload = time.perf_counter()
+
+        succ = all(x[0] for x in res)
+        if succ:
+            self._is_offloaded = False
+            logger.info(f"Reloading VRAM costs {time_after_reload - time_before_reload:.6f} seconds.")
+            prev_is_self = all(x[1] for x in res)
+            return prev_is_self
+        else:
+            # some workers not get lock
+            self.collective_rpc("vnpu_unlock_gpu")
+            time.sleep(0.001)
+
+
+def determine_available_memory_vnpu_offload_mode(self) -> int:
+    return self.collective_rpc("determine_available_memory_vnpu_offload_mode")
+
+
+Executor.is_offloaded = is_offloaded
+Executor.offload_vram = offload_vram
+Executor.reload_vram = reload_vram
+Executor.determine_available_memory_vnpu_offload_mode = determine_available_memory_vnpu_offload_mode