diff --git a/docs/source/common/lightning_module.rst b/docs/source/common/lightning_module.rst
index e9c138a2c12cc..c02f23ac60d09 100644
--- a/docs/source/common/lightning_module.rst
+++ b/docs/source/common/lightning_module.rst
@@ -946,7 +946,7 @@ When set to ``False``, Lightning does not automate the optimization process. Thi
         opt = self.optimizers(use_pl_optimizer=True)
 
         loss = ...
-        self.manual_backward(loss, opt)
+        self.manual_backward(loss)
         opt.step()
         opt.zero_grad()
 
@@ -961,16 +961,16 @@ In the multi-optimizer case, ignore the ``optimizer_idx`` argument and use the o
 
     def training_step(self, batch, batch_idx, optimizer_idx):
         # access your optimizers with use_pl_optimizer=False. Default is True
-        (opt_a, opt_b) = self.optimizers(use_pl_optimizer=True)
+        opt_a, opt_b = self.optimizers(use_pl_optimizer=True)
 
         gen_loss = ...
         opt_a.zero_grad()
-        self.manual_backward(gen_loss, opt_a)
+        self.manual_backward(gen_loss)
         opt_a.step()
 
         disc_loss = ...
         opt_b.zero_grad()
-        self.manual_backward(disc_loss, opt_b)
+        self.manual_backward(disc_loss)
         opt_b.step()
 
 --------------
diff --git a/pytorch_lightning/core/lightning.py b/pytorch_lightning/core/lightning.py
index 5dce0caa59720..52bcc213692ac 100644
--- a/pytorch_lightning/core/lightning.py
+++ b/pytorch_lightning/core/lightning.py
@@ -1211,10 +1211,10 @@ def manual_backward(self, loss: Tensor, optimizer: Optional[Optimizer] = None, *
         Example::
 
             def training_step(...):
-                (opt_a, opt_b) = self.optimizers()
+                opt_a, opt_b = self.optimizers()
                 loss = ...
                 # automatically applies scaling, etc...
-                self.manual_backward(loss, opt_a)
+                self.manual_backward(loss)
                 opt_a.step()
         """
         if optimizer is not None: