fix

hivemind/optim/grad_scaler.py

@@ -53,7 +53,7 @@ class GradScaler(TorchGradScaler):
     def step(self, optimizer: TorchOptimizer, *args, **kwargs) -> bool:
         if self._is_running_global_step:
             with self._lock:
-                if not self._is_ready_to_update:
+                if self._is_ready_to_update:
                     logger.warning("Please call grad_scaler.update() after each step.")
                 assert not isinstance(optimizer, (hivemind.Optimizer, hivemind.DecentralizedOptimizerBase))
                 assert self._per_optimizer_states[id(optimizer)]["stage"] == OptState.UNSCALED, \