diff --git a/README.md b/README.md
index e2054ed623..e9d5666c17 100644
--- a/README.md
+++ b/README.md
@@ -146,7 +146,7 @@ class LitAutoEncoder(L.LightningModule):
 
     def training_step(self, batch, batch_idx):
         # training_step defines the train loop. It is independent of forward
-        x, y = batch
+        x, _ = batch
         x = x.view(x.size(0), -1)
         z = self.encoder(x)
         x_hat = self.decoder(z)
diff --git a/docs/source-app/code_samples/convert_pl_to_app/train.py b/docs/source-app/code_samples/convert_pl_to_app/train.py
index e9f9de3a6a..d0b7919b75 100644
--- a/docs/source-app/code_samples/convert_pl_to_app/train.py
+++ b/docs/source-app/code_samples/convert_pl_to_app/train.py
@@ -25,7 +25,7 @@ class LitAutoEncoder(pl.LightningModule):
     def training_step(self, batch, batch_idx):
         # training_step defines the train loop.
         # It is independent of forward
-        x, y = batch
+        x, _ = batch
         x = x.view(x.size(0), -1)
         z = self.encoder(x)
         x_hat = self.decoder(z)
diff --git a/docs/source-pytorch/common/evaluation_basic.rst b/docs/source-pytorch/common/evaluation_basic.rst
index 3dc7867de1..9eb1b9400c 100644
--- a/docs/source-pytorch/common/evaluation_basic.rst
+++ b/docs/source-pytorch/common/evaluation_basic.rst
@@ -45,7 +45,7 @@ To add a test loop, implement the **test_step** method of the LightningModule
 
         def test_step(self, batch, batch_idx):
             # this is the test loop
-            x, y = batch
+            x, _ = batch
             x = x.view(x.size(0), -1)
             z = self.encoder(x)
             x_hat = self.decoder(z)
@@ -105,7 +105,7 @@ To add a validation loop, implement the **validation_step** method of the Lightn
 
         def validation_step(self, batch, batch_idx):
             # this is the validation loop
-            x, y = batch
+            x, _ = batch
             x = x.view(x.size(0), -1)
             z = self.encoder(x)
             x_hat = self.decoder(z)
diff --git a/docs/source-pytorch/common/notebooks.rst b/docs/source-pytorch/common/notebooks.rst
index 1652d9dcb4..d4777f675b 100644
--- a/docs/source-pytorch/common/notebooks.rst
+++ b/docs/source-pytorch/common/notebooks.rst
@@ -57,7 +57,7 @@ Paste the following code block into a notebook cell:
             self.decoder = decoder
 
         def training_step(self, batch, batch_idx):
-            x, y = batch
+            x, _ = batch
             x = x.view(x.size(0), -1)
             z = self.encoder(x)
             x_hat = self.decoder(z)
diff --git a/docs/source-pytorch/model/train_model_basic.rst b/docs/source-pytorch/model/train_model_basic.rst
index 68111fea5d..f5aeb8b689 100644
--- a/docs/source-pytorch/model/train_model_basic.rst
+++ b/docs/source-pytorch/model/train_model_basic.rst
@@ -68,7 +68,7 @@ The LightningModule is the full **recipe** that defines how your nn.Modules inte
 
         def training_step(self, batch, batch_idx):
             # training_step defines the train loop.
-            x, y = batch
+            x, _ = batch
             x = x.view(x.size(0), -1)
             z = self.encoder(x)
             x_hat = self.decoder(z)
diff --git a/docs/source-pytorch/starter/introduction.rst b/docs/source-pytorch/starter/introduction.rst
index 3cfe872613..8e55afb907 100644
--- a/docs/source-pytorch/starter/introduction.rst
+++ b/docs/source-pytorch/starter/introduction.rst
@@ -129,7 +129,7 @@ A LightningModule enables your PyTorch nn.Module to play together in complex way
         def training_step(self, batch, batch_idx):
             # training_step defines the train loop.
             # it is independent of forward
-            x, y = batch
+            x, _ = batch
             x = x.view(x.size(0), -1)
             z = self.encoder(x)
             x_hat = self.decoder(z)
diff --git a/src/pytorch_lightning/README.md b/src/pytorch_lightning/README.md
index f1e1d5dfc7..a9200baa27 100644
--- a/src/pytorch_lightning/README.md
+++ b/src/pytorch_lightning/README.md
@@ -174,7 +174,7 @@ class LitAutoEncoder(pl.LightningModule):
 
     def training_step(self, batch, batch_idx):
         # training_step defines the train loop. It is independent of forward
-        x, y = batch
+        x, _ = batch
         x = x.view(x.size(0), -1)
         z = self.encoder(x)
         x_hat = self.decoder(z)