diff --git a/mair/__init__.py b/mair/__init__.py
index 0909aa6..ba6fe62 100644
--- a/mair/__init__.py
+++ b/mair/__init__.py
@@ -6,4 +6,4 @@
 
 # from .utils.datasets import Datasets
 
-__version__ = "1.0.2"
+__version__ = "1.0.3"
diff --git a/mair/defenses/rm.py b/mair/defenses/rm.py
index 99ca6f4..06d0190 100644
--- a/mair/defenses/rm.py
+++ b/mair/defenses/rm.py
@@ -129,13 +129,13 @@ def progress_end(self):
 
     def print(self, record_type, str, *args, **kargs):
         if record_type is not None:
-            print(str)
+            print(str, *args, **kargs)
             self.log.append(str)
             self.save_log()
 
     def print_only(self, record_type, str, *args, **kargs):
         if record_type is not None:
-            print(str)
+            print(str, *args, **kargs)
 
     def _add_progress_time(self, dict_record):
         dict_record["s/it"] = np.array(self._progress_times).mean()
diff --git a/mair/defenses/trainer.py b/mair/defenses/trainer.py
index ef9ac3d..b953470 100644
--- a/mair/defenses/trainer.py
+++ b/mair/defenses/trainer.py
@@ -104,17 +104,16 @@ def fit(
             start_iter = 0
 
         # Print train information
-        if record_type:
-            self.rm.print("[%s]" % self.__class__.__name__)
-            self.rm.print("Training Information.")
-            self.rm.print("-Epochs: %s" % n_epochs)
-            self.rm.print("-Optimizer: %s" % self.optimizer)
-            self.rm.print("-Scheduler: %s" % self.scheduler)
-            self.rm.print("-Minmizer: %s" % self.minimizer)
-            self.rm.print("-Save Path: %s" % save_path)
-            self.rm.print("-Save Type: %s" % str(save_type))
-            self.rm.print("-Record Type: %s" % str(record_type))
-            self.rm.print("-Device: %s" % self.device)
+        self.rm.print(record_type, "[%s]" % self.__class__.__name__)
+        self.rm.print(record_type, "Training Information.")
+        self.rm.print(record_type, "-Epochs: %s" % n_epochs)
+        self.rm.print(record_type, "-Optimizer: %s" % self.optimizer)
+        self.rm.print(record_type, "-Scheduler: %s" % self.scheduler)
+        self.rm.print(record_type, "-Minmizer: %s" % self.minimizer)
+        self.rm.print(record_type, "-Save Path: %s" % save_path)
+        self.rm.print(record_type, "-Save Type: %s" % str(save_type))
+        self.rm.print(record_type, "-Record Type: %s" % str(record_type))
+        self.rm.print(record_type, "-Device: %s" % self.device)
 
         # Start training
         for epoch in range(start_epoch, n_epochs):
diff --git a/setup.py b/setup.py
index 3da14f1..31d9f9f 100644
--- a/setup.py
+++ b/setup.py
@@ -10,7 +10,7 @@
 
 setuptools.setup(
     name="mair",
-    version="1.0.2",
+    version="1.0.3",
     description="MAIR is a PyTorch-based adversarial training framework.",
     author="Harry Kim",
     author_email="24k.harry@gmail.com",