diff --git a/beginner_source/Intro_to_TorchScript_tutorial.py b/beginner_source/Intro_to_TorchScript_tutorial.py
index 1c7502b8a46..d9b0023a6ab 100644
--- a/beginner_source/Intro_to_TorchScript_tutorial.py
+++ b/beginner_source/Intro_to_TorchScript_tutorial.py
@@ -31,7 +31,7 @@
 
 """
 
-import torch # This is all you need to use both PyTorch and TorchScript!
+import torch  # This is all you need to use both PyTorch and TorchScript!
 print(torch.__version__)
 
 
@@ -125,11 +125,11 @@ def forward(self, x, h):
 #
 
 class MyDecisionGate(torch.nn.Module):
-  def forward(self, x):
-    if x.sum() > 0:
-      return x
-    else:
-      return -x
+    def forward(self, x):
+        if x.sum() > 0:
+            return x
+        else:
+            return -x
 
 class MyCell(torch.nn.Module):
     def __init__(self):
@@ -256,11 +256,11 @@ def forward(self, x, h):
 #
 
 class MyDecisionGate(torch.nn.Module):
-  def forward(self, x):
-    if x.sum() > 0:
-      return x
-    else:
-      return -x
+    def forward(self, x):
+        if x.sum() > 0:
+            return x
+        else:
+            return -x
 
 class MyCell(torch.nn.Module):
     def __init__(self, dg):
@@ -342,13 +342,13 @@ def forward(self, xs):
 #
 
 class WrapRNN(torch.nn.Module):
-  def __init__(self):
-    super(WrapRNN, self).__init__()
-    self.loop = torch.jit.script(MyRNNLoop())
+    def __init__(self):
+        super(WrapRNN, self).__init__()
+        self.loop = torch.jit.script(MyRNNLoop())
 
-  def forward(self, xs):
-    y, h = self.loop(xs)
-    return torch.relu(y)
+    def forward(self, xs):
+        y, h = self.loop(xs)
+        return torch.relu(y)
 
 traced = torch.jit.trace(WrapRNN(), (torch.rand(10, 3, 4)))
 print(traced.code)