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tf.raw_ops.SparseCross Stay organized with collections Save and categorize content based on your preferences.

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

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.SparseCross

tf.raw_ops.SparseCross(
    indices,
    values,
    shapes,
    dense_inputs,
    hashed_output,
    num_buckets,
    hash_key,
    out_type,
    internal_type,
    name=None
)

The op takes two lists, one of 2D SparseTensor and one of 2D Tensor, each representing features of one feature column. It outputs a 2D SparseTensor with the batchwise crosses of these features.

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]: "a_X_d_X_f"
[1, 0]: "b_X_e_X_g"
[1, 1]: "c_X_e_X_g"

if hashed_output=true 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")))

indices A list of Tensor objects with type int64. 2-D. Indices of each input SparseTensor.
values A list of Tensor objects with types from: int64, string. 1-D. values of each SparseTensor.
shapes A list with the same length as indices of Tensor objects with type int64. 1-D. Shapes of each SparseTensor.
dense_inputs A list of Tensor objects with types from: int64, string. 2-D. Columns represented by dense Tensor.
hashed_output A bool. If true, returns the hash of the cross instead of the string. This will allow us avoiding string manipulations.
num_buckets An int that is >= 0. It is used if hashed_output is true. output = hashed_value%num_buckets if num_buckets > 0 else hashed_value.
hash_key An int. Specify the hash_key that will be used by the FingerprintCat64 function to combine the crosses fingerprints.
out_type A tf.DType from: tf.int64, tf.string.
internal_type A tf.DType from: tf.int64, tf.string.
name A name for the operation (optional).

A tuple of Tensor objects (output_indices, output_values, output_shape).
output_indices A Tensor of type int64.
output_values A Tensor of type out_type.
output_shape A Tensor of type int64.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2024-04-26 UTC.

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