diff --git a/TTS/tts/models/vits.py b/TTS/tts/models/vits.py
index d1755b47..ae607c47 100644
--- a/TTS/tts/models/vits.py
+++ b/TTS/tts/models/vits.py
@@ -402,6 +402,7 @@ class Vits(BaseTTS):
         # speaker embedding
         if self.num_speakers > 1 and sid is not None:
             g = self.emb_g(sid).unsqueeze(-1)  # [b, h, 1]
+
         # posterior encoder
         z, m_q, logs_q, y_mask = self.posterior_encoder(y, y_lengths, g=g)
 
@@ -638,7 +639,7 @@ class Vits(BaseTTS):
         return self._log(ap, batch, outputs, "eval")
 
     @torch.no_grad()
-    def test_run(self, ap) -> Tuple[Dict, Dict]:
+    def test_run(self, ap, eval_loader=None) -> Tuple[Dict, Dict]:
         """Generic test run for `tts` models used by `Trainer`.
 
         You can override this for a different behaviour.
@@ -650,16 +651,13 @@ class Vits(BaseTTS):
         test_audios = {}
         test_figures = {}
         test_sentences = self.config.test_sentences
-        aux_inputs = {
-            "speaker_id": None
-            if not self.config.use_speaker_embedding
-            else random.sample(sorted(self.speaker_manager.speaker_ids.values()), 1),
-            "d_vector": None
-            if not self.config.use_d_vector_file
-            else random.samples(sorted(self.speaker_manager.d_vectors.values()), 1),
-            "style_wav": None,
-        }
+        if hasattr(self, "speaker_manager"):
+            aux_inputs = self.speaker_manager.get_random_speaker_aux_input()
+        else:
+            aux_inputs = self.get_aux_input()
+
         for idx, sen in enumerate(test_sentences):
+
             wav, alignment, _, _ = synthesis(
                 self,
                 sen,
diff --git a/TTS/tts/utils/speakers.py b/TTS/tts/utils/speakers.py
index 13696a20..ae001155 100644
--- a/TTS/tts/utils/speakers.py
+++ b/TTS/tts/utils/speakers.py
@@ -209,6 +209,14 @@ class SpeakerManager:
                 d_vectors = np.stack(d_vectors[:num_samples]).mean(0)
         return d_vectors
 
+    def get_random_speaker_aux_input(self) -> Dict:
+        if self.d_vectors:
+            return {"speaker_id": None, "style_wav": None, "d_vector":  self.d_vectors[random.choices(list(self.d_vectors.keys()))[0]]["embedding"]}
+        elif self.speaker_ids:
+            return {"speaker_id": self.speaker_ids[random.choices(list(self.speaker_ids.keys()))[0]], "style_wav": None, "d_vector": None}
+        else:
+            return {"speaker_id": None, "style_wav": None, "d_vector": None}
+
     def get_speakers(self) -> List:
         return self.speaker_ids