Warn users when release_memory_occupation is called without memory saver enabled (#4566)

python/sglang/srt/torch_memory_saver_adapter.py

@@ -1,3 +1,4 @@
+import logging
 from abc import ABC
 from contextlib import contextmanager
 
@@ -8,6 +9,8 @@ try:
 except ImportError:
     pass
 
+logger = logging.getLogger(__name__)
+
 
 class TorchMemorySaverAdapter(ABC):
     @staticmethod
@@ -16,6 +19,13 @@ class TorchMemorySaverAdapter(ABC):
             _TorchMemorySaverAdapterReal() if enable else _TorchMemorySaverAdapterNoop()
         )
 
+    def check_validity(self, caller_name):
+        if not self.enabled:
+            logger.warning(
+                f"`{caller_name}` will not save memory because torch_memory_saver is not enabled. "
+                f"Potential causes: `enable_memory_saver` is false, or torch_memory_saver has installation issues."
+            )
+
     def configure_subprocess(self):
         raise NotImplementedError
 
@@ -28,6 +38,10 @@ class TorchMemorySaverAdapter(ABC):
     def resume(self):
         raise NotImplementedError
 
+    @property
+    def enabled(self):
+        raise NotImplementedError
+
 
 class _TorchMemorySaverAdapterReal(TorchMemorySaverAdapter):
     def configure_subprocess(self):
@@ -42,6 +56,10 @@ class _TorchMemorySaverAdapterReal(TorchMemorySaverAdapter):
     def resume(self):
         return _primary_memory_saver.resume()
 
+    @property
+    def enabled(self):
+        return _primary_memory_saver.enabled
+
 
 class _TorchMemorySaverAdapterNoop(TorchMemorySaverAdapter):
     @contextmanager
@@ -57,3 +75,7 @@ class _TorchMemorySaverAdapterNoop(TorchMemorySaverAdapter):
 
     def resume(self):
         pass
+
+    @property
+    def enabled(self):
+        return False