| View source on GitHub |
Says whether the targets are in the top K predictions.
tf.math.in_top_k(
predictions, targets, k, name=None
)
This outputs a batch_size bool array, an entry out[i] is true if the prediction for the target class is finite (not inf, -inf, or nan) and 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,
| Args | |
|---|---|
predictions | A Tensor of type float32. A batch_size x classes tensor. |
targets | A Tensor. Must be one of the following types: int32, int64. A batch_size vector of class ids. |
k | An int. Number of top elements to look at for computing precision. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor of type bool. Computed Precision at k as a bool Tensor. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/in_top_k