Code in variational_strategy.py
# 🐛 Bug

Dear Gpytorch Developers

Here is a possible issue with variational_strategy.py

I am wondering whether it is a special consideration or something missing.  According to the formula in Line 121, it seems an L is missing in front of self.prior_distribution.mean in Line 115.   I understand variable inducing_values has already included L.inv() according to whitening of the inducing posterior, but this is not the case for the prior.   It is fortunate that self.prior_distribution.mean is always 0, so no errors.

Thank you for the great package

J.

## To reproduce

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# Your code goes here
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# (We much prefer small snippets rather than links to existing libraries!)
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** Stack trace/error message **
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## Expected Behavior

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## System information

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## Additional context
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diff --git a/gpytorch/variational/variational_strategy.py b/gpytorch/variational/variational_strategy.py
index 8996e6c9..3733f938 100644
--- a/gpytorch/variational/variational_strategy.py
+++ b/gpytorch/variational/variational_strategy.py
@@ -114,12 +114,7 @@ class VariationalStrategy(_VariationalStrategy):
 
         # Compute the mean of q(f)
         # k_XZ K_ZZ^{-1/2} (m - K_ZZ^{-1/2} \\mu_Z) + \\mu_X
-        predictive_mean = (
-            torch.matmul(
-                interp_term.transpose(-1, -2), (inducing_values - self.prior_distribution.mean).unsqueeze(-1)
-            ).squeeze(-1)
-            + test_mean
-        )
+        predictive_mean = (interp_term.transpose(-1, -2) @ inducing_values.unsqueeze(-1)).squeeze(-1) + test_mean
 
         # Compute the covariance of q(f)
         # K_XX + k_XZ K_ZZ^{-1/2} (S - I) K_ZZ^{-1/2} k_ZX
['gpytorch/variational/variational_strategy.py']