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tf.math.in_top_k

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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 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,

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