Merge pull request #66 from AlexImmer/symeig-device-fix

Fix device of eye in symeig

laplace/utils.py

@@ -131,7 +131,7 @@ def diagonal_add_scalar(X, value):
     values = X.new_ones(X.shape[0]).mul(value)
     return X.index_put(tuple(indices.t()), values, accumulate=True)
 
- 
+
 def symeig(M):
     """Symetric eigendecomposition avoiding failure cases by
     adding and removing jitter to the diagonal.
@@ -152,7 +152,7 @@ def symeig(M):
     except RuntimeError:  # did not converge
         logging.info('SYMEIG: adding jitter, did not converge.')
         # use W L W^T + I = W (L + I) W^T
-        M = M + torch.eye(M.shape[0])
+        M = M + torch.eye(M.shape[0], device=M.device)
         try:
             L, W = torch.linalg.eigh(M, UPLO='U')
             L -= 1.
@@ -195,13 +195,13 @@ def expand_prior_precision(prior_prec, model):
     Parameters
     ----------
     prior_prec : torch.Tensor 1-dimensional
-        prior precision 
+        prior precision
     model : torch.nn.Module
         torch model with parameters that are regularized by prior_prec
 
     Returns
     -------
-    expanded_prior_prec : torch.Tensor 
+    expanded_prior_prec : torch.Tensor
         expanded prior precision has the same shape as model parameters
     """
     theta = parameters_to_vector(model.parameters())