TensorFlow 1 version
 | 
Converts each string in the input Tensor to its hash mod by a number of buckets.
tf.strings.to_hash_bucket_strong(
    input, num_buckets, key, name=None
)
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 | |
|---|---|
input
 | 
A Tensor of type string. The strings to assign a hash bucket.
 | 
num_buckets
 | 
An int that is >= 1. The number of buckets.
 | 
key
 | 
A list of ints.
The key used to seed the hash function, passed as a list of two uint64
elements.
 | 
name
 | 
A name for the operation (optional). | 
Returns | |
|---|---|
A Tensor of type int64.
 | 
  TensorFlow 1 version