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tf.sparse.cross_hashed

TensorFlow 1 version View source on GitHub

Generates hashed sparse cross from a list of sparse and dense tensors.

Aliases:

tf.sparse.cross_hashed(
    inputs,
    num_buckets=0,
    hash_key=None,
    name=None
)

For example, if the inputs are

* inputs[0]: SparseTensor with shape = [2, 2]
  [0, 0]: "a"
  [1, 0]: "b"
  [1, 1]: "c"
* inputs[1]: SparseTensor with shape = [2, 1]
  [0, 0]: "d"
  [1, 0]: "e"
* inputs[2]: Tensor [["f"], ["g"]]

then the output will be:

shape = [2, 2]
[0, 0]: FingerprintCat64(
            Fingerprint64("f"), FingerprintCat64(
                Fingerprint64("d"), Fingerprint64("a")))
[1, 0]: FingerprintCat64(
            Fingerprint64("g"), FingerprintCat64(
                Fingerprint64("e"), Fingerprint64("b")))
[1, 1]: FingerprintCat64(
            Fingerprint64("g"), FingerprintCat64(
                Fingerprint64("e"), Fingerprint64("c")))

Args:

  • inputs: An iterable of Tensor or SparseTensor.
  • num_buckets: An int that is >= 0. output = hashed_value%num_buckets if num_buckets > 0 else hashed_value.
  • hash_key: Integer hash_key that will be used by the FingerprintCat64 function. If not given, will use a default key.
  • name: Optional name for the op.

Returns:

A SparseTensor of type int64.