diff --git a/gensim/models/keyedvectors.py b/gensim/models/keyedvectors.py
index 3dd6cf61d0..475a0b4810 100644
--- a/gensim/models/keyedvectors.py
+++ b/gensim/models/keyedvectors.py
@@ -495,9 +495,9 @@ def get_mean_vector(self, keys, weights=None, pre_normalize=True, post_normalize
         if len(keys) == 0:
             raise ValueError("cannot compute mean with no input")
         if isinstance(weights, list):
-            weights = np.array(weights)
+            weights = np.array(weights, dtype=self.vectors.dtype)
         if weights is None:
-            weights = np.ones(len(keys))
+            weights = np.ones(len(keys), dtype=self.vectors.dtype)
         if len(keys) != weights.shape[0]:  # weights is a 1-D numpy array
             raise ValueError(
                 "keys and weights array must have same number of elements"
diff --git a/gensim/models/ldamodel.py b/gensim/models/ldamodel.py
index 945ff04599..c3e8afbf85 100755
--- a/gensim/models/ldamodel.py
+++ b/gensim/models/ldamodel.py
@@ -133,10 +133,11 @@ def update_dir_prior(prior, N, logphat, rho):
         The updated prior.
 
     """
+    dtype = logphat.dtype
     gradf = N * (psi(np.sum(prior)) - psi(prior) + logphat)
 
-    c = N * polygamma(1, np.sum(prior))
-    q = -N * polygamma(1, prior)
+    c = N * polygamma(1, np.sum(prior)).astype(dtype)
+    q = -N * polygamma(1, prior).astype(dtype)
 
     b = np.sum(gradf / q) / (1 / c + np.sum(1 / q))