gpu-limit.md

@@ -13,13 +13,14 @@ If you use TensorFlow 2.0 (or Keras with a TensorFlow backend), you can limit th
 ```python
 import tensorflow as tf
 
-megabytes = 2048
+lim = 2048 # megabytes
 gpus = tf.config.experimental.list_physical_devices('GPU')
 if gpus:
     for gpu in gpus:
-        tf.config.experimental.set_virtual_device_configuration(gpu [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=megabytes)])
+        tf.config.experimental.set_virtual_device_configuration(gpu, [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=lim)])
 ```
 
+This code first checks if your script is using GPUs. In that case, it limits the GPU memory requested to `lim` MB (2GB in the example). If you are using a single GPU you can also simplify this removing the for loop and setting the limit just for `gpus[0]`. 
 
 ## Limiting GPU Memory in PyTorch