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tensoreflusso:: ops:: SparseCrossHashed
#include <sparse_ops.h> Genera una croce sparsa da un elenco di tensori sparsi e densi.
Riepilogo
L'operazione richiede due elenchi, uno di 2D SparseTensor e uno di 2D Tensor , ciascuno dei quali rappresenta le caratteristiche di una colonna di caratteristiche. Genera uno SparseTensor 2D con le croci batch di queste funzionalità.
Ad esempio, se gli input sono
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"]]
quindi l'output sarà
shape = [2, 2]
[0, 0]: "a_X_d_X_f"
[1, 0]: "b_X_e_X_g"
[1, 1]: "c_X_e_X_g"
se hasshed_output=true allora l'output sarà
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"))) Argomenti:
- scope: un oggetto Scope
- indici: 2-D. Indici di ogni ingresso
SparseTensor . - valori: 1-D. valori di ogni
SparseTensor . - forme: 1-D. Forme di ogni
SparseTensor . - ingressi_densi: 2-D. Colonne rappresentate dal
Tensor denso. - num_buckets: viene utilizzato se hashed_output è vero. output = valore_hashednum_buckets se num_buckets > 0 altrimenti valore_hashed.
- strong_hash: booleano, se vero, verrà utilizzato siphash con salt al posto di farmhash.
- salt: specifica il sale che verrà utilizzato dalla funzione siphash.
Resi:
-
Output output_indices: 2-D. Indici dello SparseTensor concatenato. -
Output valori_output: 1-D. Valori non vuoti dello SparseTensor concatenato o con hash. -
Output forma_output: 1-D. Forma dello SparseTensor concatenato.
Attributi pubblici
Funzioni pubbliche
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-27 UTC.
[null,null,["Ultimo aggiornamento 2025-07-27 UTC."],[],[],null,["# tensorflow::ops::SparseCrossHashed Class Reference\n\ntensorflow::ops::SparseCrossHashed\n==================================\n\n`#include \u003csparse_ops.h\u003e`\n\nGenerates sparse cross from a list of sparse and dense tensors.\n\nSummary\n-------\n\nThe op takes two lists, one of 2D `SparseTensor` and one of 2D [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor), each representing features of one feature column. It outputs a 2D `SparseTensor` with the batchwise crosses of these features.\n\nFor example, if the inputs are \n\n```text\ninputs[0]: SparseTensor with shape = [2, 2]\n[0, 0]: \"a\"\n[1, 0]: \"b\"\n[1, 1]: \"c\"\n\ninputs[1]: SparseTensor with shape = [2, 1]\n[0, 0]: \"d\"\n[1, 0]: \"e\"\n\ninputs[2]: Tensor [[\"f\"], [\"g\"]]\n```\n\n\u003cbr /\u003e\n\nthen the output will be \n\n```scdoc\nshape = [2, 2]\n[0, 0]: \"a_X_d_X_f\"\n[1, 0]: \"b_X_e_X_g\"\n[1, 1]: \"c_X_e_X_g\"\n```\n\n\u003cbr /\u003e\n\nif hashed_output=true then the output will be \n\n```text\nshape = [2, 2]\n[0, 0]: FingerprintCat64(\n Fingerprint64(\"f\"), FingerprintCat64(\n Fingerprint64(\"d\"), Fingerprint64(\"a\")))\n[1, 0]: FingerprintCat64(\n Fingerprint64(\"g\"), FingerprintCat64(\n Fingerprint64(\"e\"), Fingerprint64(\"b\")))\n[1, 1]: FingerprintCat64(\n Fingerprint64(\"g\"), FingerprintCat64(\n Fingerprint64(\"e\"), Fingerprint64(\"c\")))\n```\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- indices: 2-D. Indices of each input `SparseTensor`.\n- values: 1-D. values of each `SparseTensor`.\n- shapes: 1-D. Shapes of each `SparseTensor`.\n- dense_inputs: 2-D. Columns represented by dense [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n- num_buckets: It is used if hashed_output is true. output = hashed_valuenum_buckets if num_buckets \\\u003e 0 else hashed_value.\n- strong_hash: boolean, if true, siphash with salt will be used instead of farmhash.\n- salt: Specify the salt that will be used by the siphash function.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_indices: 2-D. Indices of the concatenated `SparseTensor`.\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_values: 1-D. Non-empty values of the concatenated or hashed `SparseTensor`.\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_shape: 1-D. Shape of the concatenated `SparseTensor`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseCrossHashed](#classtensorflow_1_1ops_1_1_sparse_cross_hashed_1a75df417d574408f2c120294be39de389)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::InputList](/versions/r2.3/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` indices, ::`[tensorflow::InputList](/versions/r2.3/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` values, ::`[tensorflow::InputList](/versions/r2.3/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` shapes, ::`[tensorflow::InputList](/versions/r2.3/api_docs/cc/class/tensorflow/input-list#classtensorflow_1_1_input_list)` dense_inputs, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` num_buckets, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` strong_hash, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` salt)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_cross_hashed_1a68e99ac704684420839783001f5f37f4) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output_indices](#classtensorflow_1_1ops_1_1_sparse_cross_hashed_1a13ce1f14f64b18d1c495ccf725acf0bb) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_shape](#classtensorflow_1_1ops_1_1_sparse_cross_hashed_1a89578d009bb75ad63a153f89045c46a2) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_values](#classtensorflow_1_1ops_1_1_sparse_cross_hashed_1a6371e5ae28289305864042629e0b4fe5) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output_indices\n\n```scdoc\n::tensorflow::Output output_indices\n``` \n\n### output_shape\n\n```scdoc\n::tensorflow::Output output_shape\n``` \n\n### output_values\n\n```scdoc\n::tensorflow::Output output_values\n``` \n\nPublic functions\n----------------\n\n### SparseCrossHashed\n\n```gdscript\n SparseCrossHashed(\n const ::tensorflow::Scope & scope,\n ::tensorflow::InputList indices,\n ::tensorflow::InputList values,\n ::tensorflow::InputList shapes,\n ::tensorflow::InputList dense_inputs,\n ::tensorflow::Input num_buckets,\n ::tensorflow::Input strong_hash,\n ::tensorflow::Input salt\n)\n```"]]
