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Calculate the pseudo-perplexity from a PerResidueProbabilitiesMetric, which is a value defining the likelihood of a sequence given the prediction of a model (smaller is better). It is defined as the exponentiation of the average negative logarithm of the predicted probabilities.
Autogenerated Tag Syntax Documentation:
A metric for estimating the likeliness of a sequence given some predicted probabilities.
References and author information for the PseudoPerplexityMetric simple metric:
PseudoPerplexityMetric SimpleMetric's author(s): Moritz Ertelt, University of Leipzig [moritz.ertelt@gmail.com]
<PseudoPerplexityMetric name="(&string;)" custom_type="(&string;)"
        metric="(&string;)" use_cached_data="(false &bool;)"
        cache_prefix="(&string;)" cache_suffix="(&string;)"
        fail_on_missing_cache="(true &bool;)" /><ROSETTASCRIPTS>
    <RESIDUE_SELECTORS>
        <Chain name="res" chains="A" />
        <Index name="mask" resnums="25"/>
    </RESIDUE_SELECTORS>
    <SIMPLE_METRICS>
        <PerResidueEsmProbabilitiesMetric name="prediction" residue_selector="res" attention_mask_selection="mask"  write_pssm="test.pssm" model="esm2_t6_8M_UR50D" multirun="true"/>
        <PseudoPerplexityMetric name="perplex" metric="prediction"/>
    </SIMPLE_METRICS>
    <FILTERS>
    </FILTERS>
    <MOVERS>
        <RunSimpleMetrics name="run" metrics="perplex"/>
    </MOVERS>
    <PROTOCOLS>
        <Add mover_name="run"/>
    </PROTOCOLS>
</ROSETTASCRIPTS>This is currently unpublished.