Update custom_interface.py

custom_interface.py

@@ -139,7 +139,6 @@ class CustomEncoderWav2vec2Classifier(Pretrained):
         batch = waveform.unsqueeze(0)
         rel_length = torch.tensor([1.0])
         outputs = self.encode_batch(batch, rel_length)
-        outputs = self.mods.output_mlp(outputs).squeeze(1)
         return outputs
         
 
@@ -164,6 +163,7 @@ class CustomEncoderWav2vec2Classifier(Pretrained):
             (label encoder should be provided).
         """
         outputs = self.embed_file(path)
+        outputs = self.mods.output_mlp(outputs).squeeze(1)
         out_prob = self.hparams.softmax(outputs)
         score, index = torch.max(out_prob, dim=-1)
         text_lab = self.hparams.label_encoder.decode_torch(index)