catch NaN standardizing transforms, add err msg.

sbi/utils/sbiutils.py

@@ -224,6 +224,12 @@ def standardizing_net(
             not the case, please be sure to use a larger batch."""
         )
 
+    assert not (
+        torch.isnan(t_mean).any() or torch.isnan(torch.tensor(t_std)).any(),
+    ), """Training data mean and std for standardizing net must not contain NaNs.
+        In case you are encoding missing trials with NaNs, consider setting
+        z_score_x = 'none' to disable z-scoring."""
+
     return Standardize(t_mean, t_std)
 
 
@@ -255,6 +261,12 @@ def handle_invalid_x(
     else:
         is_valid_x = ones(batch_size, dtype=torch.bool)
 
+    assert (
+        is_valid_x.sum() > 0
+    ), """No valid data entries left after excluding NaNs and Infs. In case you are
+        encoding missing trials with NaNs consider setting exclude_invalid_x=False and
+        z_score_x = 'none' to disable z-scoring."""
+
     return is_valid_x, num_nans, num_infs