tf.raw_ops.TopK
    
    
      
    
    
      
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Finds values and indices of the k largest elements for the last dimension.
tf.raw_ops.TopK(
    input, k, sorted=True, name=None
)
If the input is a vector (rank-1), finds the k largest entries in the vector
and outputs their values and indices as vectors.  Thus values[j] is the
j-th largest entry in input, and its index is indices[j].
For matrices (resp. higher rank input), computes the top k entries in each
row (resp. vector along the last dimension).  Thus,
values.shape = indices.shape = input.shape[:-1] + [k]
If two elements are equal, the lower-index element appears first.
If k varies dynamically, use TopKV2 below.
| Args | 
|---|
| input | A Tensor. Must be one of the following types:float32,float64,int32,uint8,int16,int8,int64,bfloat16,uint16,half,uint32,uint64.
1-D or higher with last dimension at leastk. | 
| k | An intthat is>= 0.
Number of top elements to look for along the last dimension (along each
row for matrices). | 
| sorted | An optional bool. Defaults toTrue.
If true the resultingkelements will be sorted by the values in
descending order. | 
| name | A name for the operation (optional). | 
| Returns | 
|---|
| A tuple of Tensorobjects (values, indices). | 
| values | A Tensor. Has the same type asinput. | 
| indices | A Tensorof typeint32. | 
  
  
 
  
    
    
      
    
    
  
       
    
    
  
  
  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 2022-10-27 UTC.
  
  
  
    
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