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27 November 2021, 02:00:58 UTC
Revision 77be468c95e06730f613726ec7a09b9594602b46 authored by John Bradshaw on 10 October 2017, 10:53:08 UTC, committed by John Bradshaw on 10 October 2017, 10:53:08 UTC 
Binary classification with EP
 
* fixed a bug in log likelihood that was causing NaNs
* fixed the gradients for likelihood as was doing too many tf.stop_gradients
* added the option to not rerun EP each time you call log_likelihood
* tidied up the demo so that get nice clean comparison between VGP and EP
* soem numerical fixes and minor refactoring of EP code.
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Tip revision: 77be468c95e06730f613726ec7a09b9594602b46 authored by John Bradshaw on 10 October 2017, 10:53:08 UTC
Binary classification with EP
Tip revision: 77be468
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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