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aliran tensor:: operasi:: DiTopKV2
#include <nn_ops.h> Mengatakan apakah target berada dalam prediksi K teratas.
Ringkasan
Ini menghasilkan array bool batch_size , entri out[i] true jika prediksi untuk kelas target termasuk di antara k prediksi teratas di antara semua prediksi misalnya i . Perhatikan bahwa perilaku InTopK berbeda dengan operasi TopK dalam menangani ikatan; jika beberapa kelas memiliki nilai prediksi yang sama dan mengangkangi batas k teratas, semua kelas tersebut dianggap berada di k teratas.
Lebih formalnya, biarlah
\(predictions_i\) jadilah prediksi untuk semua kelas misalnya i , \(targets_i\) jadilah kelas sasaran misalnya i , \(out_i\) jadilah output misalnya i ,
$$out_i = predictions_{i, targets_i} TopKIncludingTies(predictions_i)$$
Argumen:
- ruang lingkup: Objek Lingkup
- prediksi: Tensor
classes batch_size x. - target: Vektor
batch_size dari id kelas. - k : Jumlah elemen teratas yang harus diperhatikan untuk presisi komputasi.
Pengembalian:
Atribut publik
Fungsi publik
simpul
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Keluaran
operator::tensorflow::Output() const
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::InTopKV2 Class Reference\n\ntensorflow::ops::InTopKV2\n=========================\n\n`#include \u003cnn_ops.h\u003e`\n\nSays whether the targets are in the top `K` predictions.\n\nSummary\n-------\n\nThis outputs a `batch_size` bool array, an entry `out[i]` is `true` if the prediction for the target class is among the top `k` predictions among all predictions for example `i`. Note that the behavior of [InTopK](/versions/r1.15/api_docs/cc/class/tensorflow/ops/in-top-k#classtensorflow_1_1ops_1_1_in_top_k) differs from the [TopK](/versions/r1.15/api_docs/cc/class/tensorflow/ops/top-k#classtensorflow_1_1ops_1_1_top_k) op in its handling of ties; if multiple classes have the same prediction value and straddle the top-`k` boundary, all of those classes are considered to be in the top `k`.\n\nMore formally, let\n\n\\\\(predictions_i\\\\) be the predictions for all classes for example `i`, \\\\(targets_i\\\\) be the target class for example `i`, \\\\(out_i\\\\) be the output for example `i`,\n\n$$out_i = predictions_{i, targets_i} TopKIncludingTies(predictions_i)$$\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- predictions: A `batch_size` x `classes` tensor.\n- targets: A `batch_size` vector of class ids.\n- k: Number of top elements to look at for computing precision.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Computed precision at `k` as a `bool `[Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [InTopKV2](#classtensorflow_1_1ops_1_1_in_top_k_v2_1a7c731af26675d2a0a5e65d4bf0501a07)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` predictions, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` targets, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` k)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_in_top_k_v2_1ad9127d0ee0e56405da77c8f8f0b0ad34) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [precision](#classtensorflow_1_1ops_1_1_in_top_k_v2_1a66a3668a94dcfe6ed4412c6d48fac92b) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_in_top_k_v2_1aca4c7a082803ec5e95dfcafac0999657)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_in_top_k_v2_1a7197986e89c2315b1a6458dcffdfd0d5)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_in_top_k_v2_1aa8a166a0b803daf34df7fd9ef3c91d40)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### precision\n\n```text\n::tensorflow::Output precision\n``` \n\nPublic functions\n----------------\n\n### InTopKV2\n\n```gdscript\n InTopKV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input predictions,\n ::tensorflow::Input targets,\n ::tensorflow::Input k\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```"]]
