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X = sparse.model.matrix( | |
as.formula( | |
paste("Hazard~", paste(colnames(ts.train), sep = "_", collapse=" +")) | |
), data = ts.train) |
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# performance monitor | |
nvidia-smi -q -g 0 -d UTILIZATION -l |
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yum install yum-utils | |
repoquery --list packagename |
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#from http://thirld.com/blog/2014/11/30/visualizing-the-results-of-profiling-python-code/ | |
pip install pyprof2calltree | |
#Profile your program as usual: | |
python -m cProfile -o prof.out mycode.py | |
#Then visualize the results in KCacheGrind: | |
pyprof2calltree -i prof.out -k |
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#!/usr/bin/env node | |
process.stdin.resume(); | |
process.stdin.setEncoding('utf8'); | |
function line_reader(stream, call_back) { | |
var remainder = ''; | |
stream.on('data', function (chunk) { | |
var lines = chunk.toString().split('\n'); | |
lines.unshift(remainder + lines.shift()); |
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$ locale | |
LANG=en_US.UTF-8 | |
$ cat file_in_cp1251 | vim --cmd ':set enc=cp1251' --cmd ':set tenc=utf8' - |