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tensorflow::
ops::
InTopKV2
#include <nn_ops.h>
Says whether the targets are in the top
K
predictions.
Summary
This 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
differs from the
TopK
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
.
More formally, let
\(predictions_i\) 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
,
$$out_i = predictions_{i, targets_i} TopKIncludingTies(predictions_i)$$
Args:
-
scope: A
Scope
object
-
predictions: A
batch_size
x
classes
tensor.
-
targets: A
batch_size
vector of class ids.
-
k: Number of top elements to look at for computing precision.
Returns:
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
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Last updated 2021-05-14 UTC.
[null,null,["Last updated 2021-05-14 UTC."],[],[],null,["# tensorflow::ops::InTopKV2 Class Reference\n\ntensorflow::\nops::\nInTopKV2\n===========================\n\n`\n#include \u003cnn_ops.h\u003e\n`\n\n\nSays whether the targets are in the top\n`\nK\n`\npredictions.\n\nSummary\n-------\n\n\nThis outputs a\n`\nbatch_size\n`\nbool array, an entry\n`\nout[i]\n`\nis\n`\ntrue\n`\nif the prediction for the target class is among the top\n`\nk\n`\npredictions among all predictions for example\n`\ni\n`\n. Note that the behavior of\n`\n`[InTopK](/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k#classtensorflow_1_1ops_1_1_in_top_k)`\n`\ndiffers from the\n`\n`[TopK](/versions/r2.5/api_docs/cc/class/tensorflow/ops/top-k#classtensorflow_1_1ops_1_1_top_k)`\n`\nop in its handling of ties; if multiple classes have the same prediction value and straddle the top-\n`\nk\n`\nboundary, all of those classes are considered to be in the top\n`\nk\n`\n.\n\n\nMore formally, let\n\n\n\\\\(predictions_i\\\\) be the predictions for all classes for example\n`\ni\n`\n, \\\\(targets_i\\\\) be the target class for example\n`\ni\n`\n, \\\\(out_i\\\\) be the output for example\n`\ni\n`\n,\n\n\n$$out_i = predictions_{i, targets_i} TopKIncludingTies(predictions_i)$$\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- predictions: A `\n batch_size\n ` x `\n classes\n ` tensor.\n- targets: A `\n batch_size\n ` vector of class ids.\n- k: Number of top elements to look at for computing precision.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : Computed precision at `\n k\n ` as a `\n bool\n `[Tensor](/versions/r2.5/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor)`\n ` .\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/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` predictions, :: `[tensorflow::Input](/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` targets, :: `[tensorflow::Input](/versions/r2.5/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/r2.5/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/r2.5/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```"]]
