fix bs

tools/program.py

@@ -311,14 +311,13 @@ def compute(feeds, net, config, mode='train'):
 
 
 def create_feeds(batch, use_mix):
+    image = to_variable(batch[0].numpy().astype("float32"))
     if use_mix:
-        image = batch[0]
         y_a = to_variable(batch[1].numpy().astype("int64").reshape(-1, 1))
         y_b = to_variable(batch[2].numpy().astype("int64").reshape(-1, 1))
         lam = to_variable(batch[3].numpy().astype("float32").reshape(-1, 1))
         feeds = {"image": image, "y_a": y_a, "y_b": y_b, "lam": lam}
     else:
-        image = batch[0]
         label = to_variable(batch[1].numpy().astype('int64').reshape(-1, 1))
         feeds = {"image": image, "label": label}
     return feeds
@@ -359,7 +358,7 @@ def run(dataloader, config, net, optimizer=None, epoch=0, mode='train'):
 
     tic = time.time()
     for idx, batch in enumerate(dataloader()):
-        bs = len(batch[0])
+        batch_size = len(batch[0])
         feeds = create_feeds(batch, use_mix)
         fetchs = compute(feeds, net, config, mode)
         if mode == 'train':
@@ -370,10 +369,10 @@ def run(dataloader, config, net, optimizer=None, epoch=0, mode='train'):
             optimizer.minimize(avg_loss)
             net.clear_gradients()
             metric_list['lr'].update(
-                optimizer._global_learning_rate().numpy()[0], bs)
+                optimizer._global_learning_rate().numpy()[0], batch_size)
 
         for name, fetch in fetchs.items():
-            metric_list[name].update(fetch.numpy()[0], bs)
+            metric_list[name].update(fetch.numpy()[0], batch_size)
         metric_list['batch_time'].update(time.time() - tic)
         tic = time.time()