From 1b9f07918e508cdd88dc30240363c64063ddd9bf Mon Sep 17 00:00:00 2001
From: Eren Golge <egolge@mozilla.com>
Date: Fri, 9 Mar 2018 15:37:58 -0800
Subject: [PATCH] bug fix

---
 config.json |  2 +-
 train.py    | 24 +++++++++++++-----------
 2 files changed, 14 insertions(+), 12 deletions(-)

diff --git a/config.json b/config.json
index b4fbd7a5..29b62a11 100644
--- a/config.json
+++ b/config.json
@@ -14,7 +14,7 @@
   "epochs": 2000,
   "lr": 0.00001875,
   "warmup_steps": 4000,
-  "batch_size": 1,
+  "batch_size": 2,
   "eval_batch_size": 32,
   "r": 5,
 
diff --git a/train.py b/train.py
index 8ca4ed78..3b7ff638 100644
--- a/train.py
+++ b/train.py
@@ -177,9 +177,10 @@ def train(model, criterion, data_loader, optimizer, epoch):
                 tb.add_audio('SampleAudio', audio_signal, current_step,
                              sample_rate=c.sample_rate)
             except:
-                print("\n > Error at audio signal on TB!!")
-                print(audio_signal.max())
-                print(audio_signal.min())
+                # print("\n > Error at audio signal on TB!!")
+                # print(audio_signal.max())
+                # print(audio_signal.min())
+                pass
                 
             
     avg_linear_loss /= (num_iter + 1)
@@ -197,12 +198,12 @@ def train(model, criterion, data_loader, optimizer, epoch):
 
         
 def evaluate(model, criterion, data_loader, current_step):
-    model = model.train()
+    model = model.eval()
     epoch_time = 0
     
     print(" | > Validation")
     n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
-    progbar = Progbar(len(data_loader.dataset) / c.batch_size)
+    progbar = Progbar(len(data_loader.dataset) / c.eval_batch_size)
     
     avg_linear_loss = 0
     avg_mel_loss = 0
@@ -271,9 +272,10 @@ def evaluate(model, criterion, data_loader, current_step):
         tb.add_audio('ValSampleAudio', audio_signal, current_step,
                      sample_rate=c.sample_rate)
     except:
-        print(" | > Error at audio signal on TB!!")
-        print(audio_signal.max())
-        print(audio_signal.min())
+        # print(" | > Error at audio signal on TB!!")
+        # print(audio_signal.max())
+        # print(audio_signal.min())
+        pass
                 
     # compute average losses
     avg_linear_loss /= (num_iter + 1)
@@ -307,9 +309,9 @@ def main(args):
                              )
 
     train_loader = DataLoader(train_dataset, batch_size=c.batch_size,
-                            shuffle=False, collate_fn=train_dataset.collate_fn,
-                            drop_last=False, num_workers=c.num_loader_workers,
-                            pin_memory=True)
+                              shuffle=False, collate_fn=train_dataset.collate_fn,
+                              drop_last=False, num_workers=c.num_loader_workers,
+                              pin_memory=True)
     
     val_dataset = LJSpeechDataset(os.path.join(c.data_path, 'metadata_val.csv'),
                               os.path.join(c.data_path, 'wavs'),