diff --git a/train.py b/train.py
index 612ee8a6..13bda5ef 100644
--- a/train.py
+++ b/train.py
@@ -331,13 +331,14 @@ def evaluate(model, criterion, ap, global_step, epoch):
             assert mel_input.shape[1] % model.decoder.r == 0
 
             # forward pass model
-            if c.bidirectional_decoder:
+            if c.bidirectional_decoder or c.double_decoder_consistency:
                 decoder_output, postnet_output, alignments, stop_tokens, decoder_backward_output, alignments_backward = model(
                     text_input, text_lengths, mel_input, speaker_ids=speaker_ids)
             else:
                 decoder_output, postnet_output, alignments, stop_tokens = model(
                     text_input, text_lengths, mel_input, speaker_ids=speaker_ids)
                 decoder_backward_output = None
+                alignments_backward = None
 
             # set the alignment lengths wrt reduction factor for guided attention
             if mel_lengths.max() % model.decoder.r != 0:
@@ -349,7 +350,8 @@ def evaluate(model, criterion, ap, global_step, epoch):
             loss_dict = criterion(postnet_output, decoder_output, mel_input,
                                   linear_input, stop_tokens, stop_targets,
                                   mel_lengths, decoder_backward_output,
-                                  alignments, alignment_lengths, text_lengths)
+                                  alignments, alignment_lengths, alignments_backward, 
+                                  text_lengths)
             if c.bidirectional_decoder:
                 keep_avg.update_values({'avg_decoder_b_loss': loss_dict['decoder_b_loss'].item(),
                                         'avg_decoder_c_loss': loss_dict['decoder_c_loss'].item()})