tensorflow_similarity/models/contrastive_model.py [763:812]:
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    def lookup(
        self, x: Tensor, k: int = 5, verbose: int = 1
    ) -> List[List[Lookup]]:
        """Find the k closest matches in the index for a set of samples.

        Args:
            x: Samples to match.

            k: Number of nearest neighboors to lookup. Defaults to 5.

            verbose: display progress. Default to 1.

        Returns
            list of list of k nearest neighboors:
            List[List[Lookup]]
        """
        predictions = self.predict(x)
        return self._index.batch_lookup(
            predictions=predictions, k=k, verbose=verbose
        )

    def single_lookup(self, x: Tensor, k: int = 5) -> List[Lookup]:
        """Find the k closest matches in the index for a given sample.

        Args:
            x: Sample to match.

            k: Number of nearest neighboors to lookup. Defaults to 5.

        Returns
            list of the k nearest neigboors info:
            List[Lookup]
        """
        x = tf.expand_dims(x, axis=0)
        prediction = self.predict(x)
        return self._index.single_lookup(prediction=prediction, k=k)

    def index_summary(self):
        "Display index info summary."
        self._index.print_stats()

    def calibrate(
        self,
        x: FloatTensor,
        y: IntTensor,
        thresholds_targets: MutableMapping[str, float] = {},
        k: int = 1,
        calibration_metric: Union[str, ClassificationMetric] = "f1",
        matcher: Union[str, ClassificationMatch] = "match_nearest",
        extra_metrics: MutableSequence[Union[str, ClassificationMetric]] = [
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tensorflow_similarity/models/similarity_model.py [399:448]:
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    def lookup(
        self, x: Tensor, k: int = 5, verbose: int = 1
    ) -> List[List[Lookup]]:
        """Find the k closest matches in the index for a set of samples.

        Args:
            x: Samples to match.

            k: Number of nearest neighboors to lookup. Defaults to 5.

            verbose: display progress. Default to 1.

        Returns
            list of list of k nearest neighboors:
            List[List[Lookup]]
        """
        predictions = self.predict(x)
        return self._index.batch_lookup(
            predictions=predictions, k=k, verbose=verbose
        )

    def single_lookup(self, x: Tensor, k: int = 5) -> List[Lookup]:
        """Find the k closest matches in the index for a given sample.

        Args:
            x: Sample to match.

            k: Number of nearest neighboors to lookup. Defaults to 5.

        Returns
            list of the k nearest neigboors info:
            List[Lookup]
        """
        x = tf.expand_dims(x, axis=0)
        prediction = self.predict(x)
        return self._index.single_lookup(prediction=prediction, k=k)

    def index_summary(self):
        "Display index info summary."
        self._index.print_stats()

    def calibrate(
        self,
        x: FloatTensor,
        y: IntTensor,
        thresholds_targets: MutableMapping[str, float] = {},
        k: int = 1,
        calibration_metric: Union[str, ClassificationMetric] = "f1",
        matcher: Union[str, ClassificationMatch] = "match_nearest",
        extra_metrics: MutableSequence[Union[str, ClassificationMetric]] = [
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