tf.strings.substr

Converts each string in the input Tensor to its hash mod by a number of buckets.

View aliases

Compat aliases for migration

tf.compat.v1.string_to_hash_bucket_fast, tf.compat.v1.strings.to_hash_bucket_fast

tf.strings.to_hash_bucket_fast(
    input, num_buckets, name=None
)

Used in the notebooks

Used in the guide
Ragged tensors

The hash function is deterministic on the content of the string within the process and will never change. However, it is not suitable for cryptography. This function may be used when CPU time is scarce and inputs are trusted or unimportant. There is a risk of adversaries constructing inputs that all hash to the same bucket. To prevent this problem, use a strong hash function with tf.string_to_hash_bucket_strong.

Examples:

tf.strings.to_hash_bucket_fast(["Hello", "TensorFlow", "2.x"], 3).numpy()
array([0, 2, 2])

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.
`name`	A name for the operation (optional).

Returns
A `Tensor` of type `int64`.

TensorFlow

tf

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tf.compat

tf.config

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tf.raw_ops

tf.saved_model

tf.sets

tf.signal

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tf.strings

tf.summary

tf.sysconfig

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tf.tpu

tf.train

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tf.strings / substr

View aliases

Used in the notebooks

Examples:

Args

Returns