diff --git a/datasets/.LJSpeech.py.swp b/datasets/.LJSpeech.py.swp
index 2cc0c4af..72acb3f7 100644
Binary files a/datasets/.LJSpeech.py.swp and b/datasets/.LJSpeech.py.swp differ
diff --git a/datasets/LJSpeech.py b/datasets/LJSpeech.py
index 4c4ddc2d..b15bc29e 100644
--- a/datasets/LJSpeech.py
+++ b/datasets/LJSpeech.py
@@ -52,6 +52,8 @@ class LJSpeechDataset(Dataset):
             keys = list()
 
             text = [d['text'] for d in batch]
+            text_lenghts = [len(x) for x in text]
+            max_text_len = np.max(text_lengths)
             wav = [d['wav'] for d in batch]
 
             # PAD sequences with largest length of the batch
diff --git a/train.py b/train.py
index 72d58d19..3bf3f4ee 100644
--- a/train.py
+++ b/train.py
@@ -97,7 +97,7 @@ def main(args):
     else:
         criterion = nn.L1Loss()
 
-n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
+    n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
 
     #lr_scheduler = ReduceLROnPlateau(optimizer, factor=c.lr_decay,
     #                               patience=c.lr_patience, verbose=True)
@@ -121,7 +121,7 @@ n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
             current_step = i + args.restore_step + epoch * len(dataloader) + 1
 
             # setup lr
-            current_lr = lr_decay(init_lr, current_step)
+            current_lr = lr_decay(c.lr, current_step)
             for params_group in optimizer.param_groups:
                 param_group['lr'] = current_lr