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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 | |
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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 | |
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A SparseTensor of type int64 . |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/sparse/cross_hashed