One thing you want to be careful with is that DL4J models aren't threadsafe. You want to wrap them inside the ParallelInference wrapper which has a few knobs for maximizing performance. You can see how to use it from the unit tests:
My professional interests are cloud and big data technologies, machine learning, and software development. I like to read source code and research papers to understand how stuff works.
Pronoun: He
Thanks for letting me know. I was aware that the models aren't thread safe that's why I wrapped it around a synchronized block (as mentioned in the post). Definately going to take a look into the ParallelInference wrapper. Thanks for the link!
For further actions, you may consider blocking this person and/or reporting abuse
We're a place where coders share, stay up-to-date and grow their careers.
One thing you want to be careful with is that DL4J models aren't threadsafe. You want to wrap them inside the ParallelInference wrapper which has a few knobs for maximizing performance. You can see how to use it from the unit tests:
github.com/deeplearning4j/deeplear...
Thanks for letting me know. I was aware that the models aren't thread safe that's why I wrapped it around a synchronized block (as mentioned in the post). Definately going to take a look into the
ParallelInferencewrapper. Thanks for the link!