From e0ea811bfc8255760bebfb560aee4e22964e142e Mon Sep 17 00:00:00 2001 From: Geoff Pleiss Date: Fri, 16 Oct 2020 16:28:52 +0000 Subject: [PATCH] Update gpytorch and gpflow benchmark --- benchmark/gpytorch_variational_models.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/benchmark/gpytorch_variational_models.py b/benchmark/gpytorch_variational_models.py index c64d50d6..313c7e99 100644 --- a/benchmark/gpytorch_variational_models.py +++ b/benchmark/gpytorch_variational_models.py @@ -5,7 +5,7 @@ import gpytorch from gpytorch.models import ApproximateGP from gpytorch.variational import CholeskyVariationalDistribution -from gpytorch.variational import VariationalStrategy, UnwhitenedVariationalStrategy +from gpytorch.variational import VariationalStrategy __all__ = ("get_rbf_kernel", "RegressionVGP", "TwoClassVGP", "MultiClassVGP") @@ -43,7 +43,7 @@ def _choose_var_strat(model, var_strat, var_dist, ind_pt, learn_ind=True, num_cl num_tasks=num_classes, task_dim=0, ) else: - return UnwhitenedVariationalStrategy(model, ind_pt, var_dist, learn_inducing_locations=learn_ind) + return VariationalStrategy(model, ind_pt, var_dist, learn_inducing_locations=learn_ind) def get_rbf_kernel(ard=None, batch_shape=1): @@ -189,9 +189,9 @@ def do_train(self, Xtr, Ytr, Xval, Yval): # Define dataset iterators train_dataset = torch.utils.data.TensorDataset(Xtr, Ytr) if self.mb_size == 1: - train_loader = torch.utils.data.DataLoader(train_dataset, shuffle=True, num_workers=8) + train_loader = torch.utils.data.DataLoader(train_dataset, shuffle=True, num_workers=0) else: - train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=self.mb_size, shuffle=True, num_workers=8) + train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=self.mb_size, shuffle=True, num_workers=0) # Start training t_elapsed = 0