diff --git a/README.md b/README.md
index a6a40a5b..4bd698c5 100644
--- a/README.md
+++ b/README.md
@@ -269,6 +269,7 @@ tensorboard --logdir /some/path
 - [Make model overfit on subset of data](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#make-model-overfit-on-subset-of-data)
 - [Print the parameter count by layer](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-the-parameter-count-by-layer)
 - [Print which gradients are nan](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-which-gradients-are-nan)
+- [Print input and output size of every module in system](https://williamfalcon.github.io/pytorch-lightning/LightningModule/properties/#example_input_array)
 
 
 ###### Distributed training    
diff --git a/docs/Trainer/index.md b/docs/Trainer/index.md
index 7d363a21..118f128e 100644
--- a/docs/Trainer/index.md
+++ b/docs/Trainer/index.md
@@ -36,6 +36,7 @@ But of course the fun is in all the advanced things it can do:
 - [Make model overfit on subset of data](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#make-model-overfit-on-subset-of-data)
 - [Print the parameter count by layer](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-the-parameter-count-by-layer)
 - [Pring which gradients are nan](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-which-gradients-are-nan)
+- [Print input and output size of every module in system](https://williamfalcon.github.io/pytorch-lightning/LightningModule/properties/#example_input_array)
 
 
 **Distributed training**    
diff --git a/docs/index.md b/docs/index.md
index 45f3e25c..24440728 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -43,6 +43,7 @@ one could be a seq-2-seq model, both (optionally) ran by the same trainer file.
 - [Make model overfit on subset of data](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#make-model-overfit-on-subset-of-data)
 - [Print the parameter count by layer](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-the-parameter-count-by-layer)
 - [Pring which gradients are nan](https://williamfalcon.github.io/pytorch-lightning/Trainer/debugging/#print-which-gradients-are-nan)
+- [Print input and output size of every module in system](https://williamfalcon.github.io/pytorch-lightning/LightningModule/properties/#example_input_array)
 
 
 ###### Distributed training