tensorflow::
    
   ops::
    
   StringToHashBucketStrong
  
  
   #include <string_ops.h>
  
  Converts each string in the input Tensor to its hash mod by a number of buckets.
Summary
   The hash function is deterministic on the content of the string within the process. The hash function is a keyed hash function, where attribute
   
    key
   
   defines the key of the hash function.
   
    key
   
   is an array of 2 elements.
  
A strong hash is important when inputs may be malicious, e.g. URLs with additional components. Adversaries could try to make their inputs hash to the same bucket for a denial-of-service attack or to skew the results. A strong hash can be used to make it difficult to find inputs with a skewed hash value distribution over buckets. This requires that the hash function is seeded by a high-entropy (random) "key" unknown to the adversary.
   The additional robustness comes at a cost of roughly 4x higher compute time than
   
    tf.string_to_hash_bucket_fast
   
   .
  
Examples:
tf.strings.to_hash_bucket_strong(["Hello", "TF"], 3, [1, 2]).numpy() array([2, 0])
Args:
- scope: A Scope object
 - input: The strings to assign a hash bucket.
 - num_buckets: The number of buckets.
 - key: The key used to seed the hash function, passed as a list of two uint64 elements.
 
Returns:
     Constructors and Destructors | 
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       StringToHashBucketStrong
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      input, int64 num_buckets, const gtl::ArraySlice< int > & key)
     
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     Public attributes | 
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       operation
      
     
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       output
      
     
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       node
      
      () const
     
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       ::tensorflow::Node *
      
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       operator::tensorflow::Input
      
      () const
     
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       operator::tensorflow::Output
      
      () const
     
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Public attributes
Public functions
StringToHashBucketStrong
StringToHashBucketStrong( const ::tensorflow::Scope & scope, ::tensorflow::Input input, int64 num_buckets, const gtl::ArraySlice< int > & key )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const