refactor with list comprehension

refactoring code with truth value test list comprehension which is more pythonic, concise, readable and efficient; how do think this change which has practical value？

Author: idiomaticrefactoring

tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/default_n_bit_quantize_registry.py

@@ -451,10 +451,7 @@ def get_activations_and_quantizers(self, layer):
     return activations_quantizers
 
   def _flatten(self, list_of_lists):
-    flat_list = []
-    for sublist in list_of_lists:
-      for item in sublist:
-        flat_list.append(item)
+    flat_list = [item for sublist in list_of_lists for item in sublist]
     return flat_list
 
   def set_quantize_weights(self, layer, quantize_weights):