Fix Perplexity metric accumulation across tokens and sample weights in Metrax. - #159
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…n Metrax. Previously, `Perplexity.from_model_output` normalized cross-entropy per batch and weighted each batch by sequence count (`labels.shape[0]`) rather than total token count/weight. A recent KerasHub update (cl/974631537) changed the Perplexity metric calculation logic to normalize by total token count, which led to failing tests in Metrax. I have also fixed couple of legacy lint errors, because they were blocking presubmit. Updating the ci.yaml to use the keras-hub-nightly for testing in CI environment. PiperOrigin-RevId: 982091649
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Fix Perplexity metric accumulation across tokens and sample weights in Metrax.
Previously,
Perplexity.from_model_outputnormalized cross-entropy per batch and weighted each batch by sequence count (labels.shape[0]) rather than total token count/weight. A recent KerasHub update (cl/974631537) changed the Perplexity metric calculation logic to normalize by total token count, which led to failing tests in Metrax.I have also fixed couple of legacy lint errors, because they were blocking presubmit.
Updating the ci.yaml to use the keras-hub-nightly for testing in CI environment.