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Elasticsearch contains a class, ExtensiblePlugin, that allows a plugin to define an spi and then load classes from other plugins. There is example code for doing this in the painless extension. If we want to support JNI rankers, such as tensorflow, in the future having them as separate plugins would be desirable.
The text was updated successfully, but these errors were encountered:
I previously hacked up the plugin to test run models through tensorflow[1]. While interesting the complications of JNI along with performance concerns (we could only batch model evaluation per segment, and in our prod use case 1 result per segment is reasonably common) basically means we didn't pursue this path. If someone wanted to plug TF into the ltr plugin, I still think something done via ExtensiblePlugin is probably the right way.
Elasticsearch contains a class, ExtensiblePlugin, that allows a plugin to define an spi and then load classes from other plugins. There is example code for doing this in the painless extension. If we want to support JNI rankers, such as tensorflow, in the future having them as separate plugins would be desirable.
The text was updated successfully, but these errors were encountered: