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Profiling shows that the majority of the time is spend in the gradient computation, which is to be expected. Sadly I wasn't able to improve this much for this PR.
I think that in principle a lot more optimization is possible, but that would require much more changes to the code. Basically, instead of separate log_p and gradient functions we'd need a class. That way, things like total_len can be easily computed once and cached, and the gradient vector grad can also be reused. In general, it should make memory reuse easier.
For now, this PR implements:
fewer allocations in bgmCompare
replace strings with enums, because comparing strings is more expensive than ints.
small tweak to the progress bar: the finish() method ensures that all progress bars are completely filled at the end of the loop. Now it no longer does this if there was a user interrupt.
Let's see if the R CMD CHECK runtime decreases (I doubt it though).
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Profiling shows that the majority of the time is spend in the gradient computation, which is to be expected. Sadly I wasn't able to improve this much for this PR.
I think that in principle a lot more optimization is possible, but that would require much more changes to the code. Basically, instead of separate log_p and gradient functions we'd need a class. That way, things like
total_lencan be easily computed once and cached, and the gradient vectorgradcan also be reused. In general, it should make memory reuse easier.For now, this PR implements:
finish()method ensures that all progress bars are completely filled at the end of the loop. Now it no longer does this if there was a user interrupt.Let's see if the R CMD CHECK runtime decreases (I doubt it though).