tf.math.in_top_k

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Says whether the targets are in the top K predictions.

View aliases

Main aliases

tf.nn.in_top_k

Compat aliases for migration

See Migration guide for more details.

tf.compat.v2.math.in_top_k, tf.compat.v2.nn.in_top_k

tf.math.in_top_k(
    targets, predictions, 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,

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

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.