diff --git a/composer/loggers/mlflow_logger.py b/composer/loggers/mlflow_logger.py
index 660c315c8e..3da777a0ec 100644
--- a/composer/loggers/mlflow_logger.py
+++ b/composer/loggers/mlflow_logger.py
@@ -312,10 +312,7 @@ def init(self, state: State, logger: Logger) -> None:
         if self.run_name is None:
             self.run_name = state.run_name
 
-        if hasattr(state, 'device'):
-            self._global_exception_occurred = state.device.tensor_to_device(torch.tensor([0], dtype=torch.uint8),)
-        else:
-            self._global_exception_occurred = 0
+        self._global_exception_occurred = 0
 
         # Store the Composer run name in the MLFlow run tags so it can be retrieved for autoresume
         self.tags['run_name'] = os.environ.get('RUN_NAME', state.run_name)
@@ -615,10 +612,7 @@ def post_close(self):
             if hasattr(self, 'monitor_process'):
                 # Check if there is an uncaught exception, which means `post_close()` is triggered
                 # due to program crash.
-                if isinstance(self._global_exception_occurred, torch.Tensor):
-                    finish_with_exception = (self._global_exception_occurred == 1).item()
-                else:
-                    finish_with_exception = (self._global_exception_occurred == 1)
+                finish_with_exception = self._global_exception_occurred == 1
                 if finish_with_exception:
                     self.monitor_process.crash()
                     return