Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
tensor akışı:: işlem:: LogSoftmax
#include <nn_ops.h>
Günlük softmax aktivasyonlarını hesaplar.
Özet
Her parti i
ve sınıf j
için elimizdekiler
logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- logitler:
[batch_size, num_classes]
şeklinde 2 boyutlu.
İade:
-
Output
: logits
ile aynı şekil.
Genel özellikler
Kamu işlevleri
düğüm
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatör::tensorflow::Çıktı
operator::tensorflow::Output() const
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::LogSoftmax Class Reference\n\ntensorflow::ops::LogSoftmax\n===========================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes log softmax activations.\n\nSummary\n-------\n\nFor each batch `i` and class `j` we have \n\n```transact-sql\nlogsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))\n```\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- logits: 2-D with shape `[batch_size, num_classes]`.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same shape as `logits`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [LogSoftmax](#classtensorflow_1_1ops_1_1_log_softmax_1a73483652ac6fcd6e2162f224c5459235)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` logits)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [logsoftmax](#classtensorflow_1_1ops_1_1_log_softmax_1aaa7ca17002b410b0a6992c5f604a13a6) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_log_softmax_1acb2eb968de24da07c71196bfd2da5e36) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_log_softmax_1a1ef7bed8e2017ceda2891e1568c32072)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_log_softmax_1ae15a3807bd29485ca7e6c0a0408bd656)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_log_softmax_1a38da28934ec15aab2813d6d074a25386)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### logsoftmax\n\n```text\n::tensorflow::Output logsoftmax\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### LogSoftmax\n\n```gdscript\n LogSoftmax(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input logits\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]