4 ms·
Your benchmark is terrible - it's impossible to run it because you don't provide a dataset that you used (or I'm missing some description). It also stresses one
by fijal 11y ago
Your benchmark is terrible - it's impossible to run it because you don't provide a dataset that you used (or I'm missing some description). It also stresses one aspect of the language (processing strings, in a very specific way) and yet you claim this is representative.
However, we're more than happy to consider it a pypy bug if we're not faster than CPython. Please provide clearer instructions how to reproduce it and ideally also other benchmarks that did not work for you.
- brendano 11y ago"Terrible" is a little harsh. I found the benchmark to be interesting because it's similar to many NLP-style analysis tasks I have myself. Of course reproducible ones would be great too.
- andor 11y agoGreat, next time I'll hit your bug tracker directly ;-) The script and data are available here: http://zentrale1.com/~an/literal-translation.tar.xz http://zentrale1.com/~an/literal-translation.tar.xz The texts were scraped from the European Parliament web site. The phrase table was built with Moses from the Europarl parallel corpus [0] minus the texts. The script itself was supposed the be baseline input for another experiment, basically it's the worst way of translating something i could think of. [0] http://statmt.org/europarl/ http://statmt.org/europarl/
- fijal 11y agocan you please provide me the data in somehow reproducible form (I have no clue how to use all the tools you mentioned for example), ideally as a .tar.bz2 file somewhere I can download and run without any prior knowledge. I'm happy to improve pypy for that particular use case.