tf.random.experimental.stateless_split
    
    
      
    
    
      
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Splits an RNG seed into num new seeds by adding a leading axis.
tf.random.experimental.stateless_split(
    seed, num=2
)
Example:
seed = [1, 2]
new_seeds = tf.random.experimental.stateless_split(seed, num=3)
print(new_seeds)
tf.Tensor(
[[1105988140 1738052849]
 [-335576002  370444179]
 [  10670227 -246211131]], shape=(3, 2), dtype=int32)
tf.random.stateless_normal(shape=[3], seed=new_seeds[0, :])
<tf.Tensor: shape=(3,), dtype=float32, numpy=array([-0.59835213, -0.9578608 ,
0.9002807 ], dtype=float32)>
| Args | 
|---|
| seed | an RNG seed (a tensor with shape [2] and dtype int32orint64). (When using XLA, onlyint32is allowed.) | 
| num | optional, a positive integer or scalar tensor indicating the number of
seeds to produce (default 2). | 
| Returns | 
|---|
| A tensor with shape [num, 2] representing numnew seeds. It will have the
same dtype asseed(ifseeddoesn't have an explict dtype, the dtype
will be determined bytf.convert_to_tensor). | 
  
  
 
  
    
    
      
       
    
    
  
  
  Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
  Last updated 2021-05-14 UTC.
  
  
  
    
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