tf.compat.v1.multinomial
    
    
       
    
    
      
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Draws samples from a multinomial distribution. (deprecated)
tf . compat . v1 . multinomial ( 
    logits ,  num_samples ,  seed = None ,  name = None ,  output_dtype = None 
) 
 
Deprecated:  THIS FUNCTION IS DEPRECATED. It will be removed in a future version.
Instructions for updating:
Use tf.random.categorical  instead.  
Example: 
# samples has shape [1, 5], where each value is either 0 or 1 with equal 
# probability. 
samples  =  tf . random . categorical ( tf . math . log ([[ 0.5 ,  0.5 ]]),  5 ) 
 
 
Args  
logits 
 
2-D Tensor with shape [batch_size, num_classes].  Each slice
[i, :] represents the unnormalized log-probabilities for all classes.
 
 
num_samples 
 
0-D.  Number of independent samples to draw for each row slice.
 
 
seed 
 
A Python integer. Used to create a random seed for the distribution.
See tf.random.set_seed  for behavior.
 
 
name 
 
Optional name for the operation.
 
 
output_dtype 
 
The integer type of the output: int32 or int64. Defaults
to int64.
 
 
 
Returns  
The drawn samples of shape [batch_size, num_samples].
 
 
  
  
 
  
    
    
      
    
     
  
       
    
    
  
  
 
  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 2023-10-06 UTC.
 
 
  
  
  
    
      [[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-10-06 UTC."],[],[]]