From 7248478262e743f6429db57121143167079223da Mon Sep 17 00:00:00 2001 From: Himaghna Bhattacharjee Date: Mon, 1 Aug 2022 10:20:56 -0700 Subject: [PATCH] Increase number of samples and decrease step size in MALA nightly tests Summary: Due to failure of nightly conjugate test of Metropolis Adapted Langevin Algorithm (MALA), we have increased the number of stepd and decreased step size. Differential Revision: D38319379 fbshipit-source-id: 6a3444be49dd2a27164e0ea316f42291f85694fe --- ..._langevin_algorithm_conjugate_test_nightly.py | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/src/beanmachine/ppl/experimental/tests/mala/single_site_metropolis_adjusted_langevin_algorithm_conjugate_test_nightly.py b/src/beanmachine/ppl/experimental/tests/mala/single_site_metropolis_adjusted_langevin_algorithm_conjugate_test_nightly.py index 9a1f2c06f1..e8ad354739 100644 --- a/src/beanmachine/ppl/experimental/tests/mala/single_site_metropolis_adjusted_langevin_algorithm_conjugate_test_nightly.py +++ b/src/beanmachine/ppl/experimental/tests/mala/single_site_metropolis_adjusted_langevin_algorithm_conjugate_test_nightly.py @@ -15,25 +15,27 @@ class SingleSiteMetropolisAdapatedLangevinAlgorithmConjugateTest( unittest.TestCase, AbstractConjugateTests ): def test_beta_binomial_conjugate_run(self): - mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.05) + mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.01) self.beta_binomial_conjugate_run( - mala, num_samples=500, num_adaptive_samples=500 + mala, num_samples=1000, num_adaptive_samples=1000 ) def test_gamma_gamma_conjugate_run(self): - mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.05) + mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.01) self.gamma_gamma_conjugate_run( mala, num_samples=1000, num_adaptive_samples=1000 ) def test_gamma_normal_conjugate_run(self): - mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.05) - self.gamma_normal_conjugate_run(mala, num_samples=500, num_adaptive_samples=500) + mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.01) + self.gamma_normal_conjugate_run( + mala, num_samples=1000, num_adaptive_samples=1000 + ) def test_normal_normal_conjugate_run(self): - mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.05) + mala = SingleSiteMetropolisAdapatedLangevinAlgorithm(0.01) self.normal_normal_conjugate_run( - mala, num_samples=500, num_adaptive_samples=500 + mala, num_samples=1000, num_adaptive_samples=1000 ) def test_dirichlet_categorical_conjugate_run(self):