tensorflow::ops::SparseCrossV2

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

Summary

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")))

Arguments:

• scope: A Scope object
• indices: 2-D. Indices of each input SparseTensor.
• values: 1-D. values of each SparseTensor.
• shapes: 1-D. Shapes of each SparseTensor.
• dense_inputs: 2-D. Columns represented by dense Tensor.
• sep: string used when joining a list of string inputs, can be used as separator later.

Returns:

• Output output_indices: 2-D. Indices of the concatenated SparseTensor.
• Output output_values: 1-D. Non-empty values of the concatenated or hashed SparseTensor.
• Output output_shape: 1-D. Shape of the concatenated SparseTensor.

Public attributes

Operation operation

::tensorflow::Output output_indices

::tensorflow::Output output_shape

::tensorflow::Output output_values

 SparseCrossV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::InputList indices,
  ::tensorflow::InputList values,
  ::tensorflow::InputList shapes,
  ::tensorflow::InputList dense_inputs,
  ::tensorflow::Input sep
)