# tensorflow::ops::InTopKV2 Class Reference

# 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
`
https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k#classtensorflow_1_1ops_1_1_in_top_k
`
differs from the
`
https://www.tensorflow.org/versions/r2.5/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
`
.


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
`
,


$$out_i = predictions_{i, targets_i} TopKIncludingTies(predictions_i)$$

<br />


Args:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_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.

<br />


Returns:

- `
  https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output
  ` : Computed precision at `
  k
  ` as a `
  bool
  https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor
  ` .

<br />

| ### Constructors and Destructors ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1a7c731af26675d2a0a5e65d4bf0501a07 (const :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input predictions, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input targets, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k) ` ||

| ### Public attributes ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1ad9127d0ee0e56405da77c8f8f0b0ad34 ` | ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1a66a3668a94dcfe6ed4412c6d48fac92b ` | ` :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output ` |

| ### Public functions ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1aca4c7a082803ec5e95dfcafac0999657 () const ` | ` ::tensorflow::Node * ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1a7197986e89c2315b1a6458dcffdfd0d5 () const ` | ` ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/in-top-k-v2#classtensorflow_1_1ops_1_1_in_top_k_v2_1aa8a166a0b803daf34df7fd9ef3c91d40 () const ` | ` ` |

## Public attributes

### operation

```
Operation operation
```

### precision

```
::tensorflow::Output precision
```

## Public functions

### InTopKV2

```
 InTopKV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input predictions,
  ::tensorflow::Input targets,
  ::tensorflow::Input k
)
```

### node

```
::tensorflow::Node * node() const 
```

### operator::tensorflow::Input

```
 operator::tensorflow::Input() const 
```

### operator::tensorflow::Output

```
 operator::tensorflow::Output() const 
```