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tensoreflusso:: ops:: SoftmaxCrossEntropyWithLogits
#include <nn_ops.h> Calcola il costo dell'entropia incrociata softmax e i gradienti per la propagazione all'indietro.
Riepilogo
Gli input sono i logit, non le probabilità.
Argomenti:
- scope: un oggetto Scope
- caratteristiche: matrice batch_size x num_classes
- etichette: matrice batch_size x num_classes Il chiamante deve garantire che ogni batch di etichette rappresenti una distribuzione di probabilità valida.
Resi:
- Perdita
Output : perdita per esempio (vettore batch_size). - Backprop
Output : gradienti retropropagati (matrice batch_size x num_classes).
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 2025-07-26 UTC.
[null,null,["Ultimo aggiornamento 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::SoftmaxCrossEntropyWithLogits Class Reference\n\ntensorflow::ops::SoftmaxCrossEntropyWithLogits\n==============================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes softmax cross entropy cost and gradients to backpropagate.\n\nSummary\n-------\n\nInputs are the logits, not probabilities.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- features: batch_size x num_classes matrix\n- labels: batch_size x num_classes matrix The caller must ensure that each batch of labels represents a valid probability distribution.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) loss: Per example loss (batch_size vector).\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop: backpropagated gradients (batch_size x num_classes matrix).\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SoftmaxCrossEntropyWithLogits](#classtensorflow_1_1ops_1_1_softmax_cross_entropy_with_logits_1a4cbff4fa9d4606e374b1a88b5de132dc)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` features, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` labels)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [backprop](#classtensorflow_1_1ops_1_1_softmax_cross_entropy_with_logits_1a3f3e88d3a28b38d7190c586e53a90391) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [loss](#classtensorflow_1_1ops_1_1_softmax_cross_entropy_with_logits_1ad3f6fea2fc731063932763fa4b3c8ce0) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_softmax_cross_entropy_with_logits_1aec7fdf4d82369e8bc00d0c9c8dd7faab) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\nPublic attributes\n-----------------\n\n### backprop\n\n```text\n::tensorflow::Output backprop\n``` \n\n### loss\n\n```text\n::tensorflow::Output loss\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### SoftmaxCrossEntropyWithLogits\n\n```gdscript\n SoftmaxCrossEntropyWithLogits(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input features,\n ::tensorflow::Input labels\n)\n```"]]
