Says whether the targets are in the top `K` predictions.
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`,
$$out_i = predictions_{i, targets_i} \in TopKIncludingTies(predictions_i)$$
Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
Output<TBool> |
asOutput()
Returns the symbolic handle of the tensor.
|
static <T extends TNumber> InTopK | |
Output<TBool> |
precision()
Computed precision at `k` as a `bool Tensor`.
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public Output<TBool> asOutput ()
Returns the symbolic handle of the tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static InTopK create (Scope scope, Operand<TFloat32> predictions, Operand<T> targets, Operand<T> k)
Factory method to create a class wrapping a new InTopK operation.
Parameters
scope | current scope |
---|---|
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
- a new instance of InTopK