meridian.backend.set_random_seed

Sets all random seeds (Python, NumPy, and backend framework, e.g. TF).

  meridian 
 . 
 backend 
 . 
 set_random_seed 
 ( 
 seed 
 ) 
 

You can use this utility to make almost any Keras program fully deterministic. Some limitations apply in cases where network communications are involved (e.g. parameter server distribution), which creates additional sources of randomness, or when certain non-deterministic cuDNN ops are involved.

Calling this utility is equivalent to the following:

  import 
  
 random 
 random 
 . 
 seed 
 ( 
 seed 
 ) 
 import 
  
 numpy 
  
 as 
  
 np 
 np 
 . 
 random 
 . 
 seed 
 ( 
 seed 
 ) 
 import 
  
 tensorflow 
  
 as 
  
 tf 
 # Only if TF is installed 
 tf 
 . 
 random 
 . 
 set_seed 
 ( 
 seed 
 ) 
 import 
  
 torch 
 # Only if the backend is 'torch' 
 torch 
 . 
 manual_seed 
 ( 
 seed 
 ) 
 

Note that the TensorFlow seed is set even if you're not using TensorFlow as your backend framework, since many workflows leverage tf.data pipelines (which feature random shuffling). Likewise many workflows might leverage NumPy APIs.