TensorFlow 1 version | View source on GitHub |
Generates hashed sparse cross from a list of sparse and dense tensors.
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 .
|