https://github.com/GPflow/GPflow
Revision 6baeb43b1d68518e6ba0074e702d014f0fe85865 authored by jch5f on 15 June 2018, 10:31:27 UTC, committed by James Hensman on 15 June 2018, 10:31:27 UTC
* Add scaling to studentT conditional variance The conditional variance of the Student’s T distributions is proportional to the square of the scale of the distribution. See https://en.wikipedia.org/wiki/Student%27s_t-distribution#In_terms_of_sca ling_parameter_σ,_or_σ2. I’ve incorporated the correct scaling factor. * explicit scale dtype and tensor broadcasting Added an explicit data type for the Student’s T scale parameter, and made the broadcasting in the conditional_variance method explicit.
1 parent 916458e
Tip revision: 6baeb43b1d68518e6ba0074e702d014f0fe85865 authored by jch5f on 15 June 2018, 10:31:27 UTC
Likelihood/students t variance scaling (#777)
Likelihood/students t variance scaling (#777)
Tip revision: 6baeb43
run_tests.sh
#!/bin/bash
# Script for running GPflow tests in sequential and parallel modes.
# Running tensorflow based tests in distinct processes prevents
# bad memory accumulations which can lead to crashes or slow runs
# on resource limited hardware.
# Written by Artem Artemev, 06/08/2017
set -e
mode=${1:-"--sequential"}
case "$mode" in
-p|--parallel)
numproc=$([[ $(uname) == 'Darwin' ]] && sysctl -n hw.physicalcpu_max || nproc)
echo ">>> Parallel mode. Number of processes = $numproc"
echo testing/test_*.py | xargs -n 1 -P "$numproc" bash -c 'nosetests -v --nologcapture $0 || exit 255'
;;
-s|--sequential)
for test_file in testing/test_*.py; do
echo ">>> Run $test_file"
nosetests -v --nologcapture "$test_file"
rc=$?
if [ "$rc" != "0" ]; then
echo ">>> $test_file failed"
exit $rc
fi
done
;;
*)
;;
esac
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