Fix some bugs (PaddlePaddle#140)

* fix some bugs

* update configs

configs/cyclegan_cityscapes.yaml

@@ -67,7 +67,7 @@ dataset:
     batch_size: 1
     max_size: inf
     is_train: False
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: A
       - name: LoadImageFromFile

configs/cyclegan_horse2zebra.yaml

@@ -35,7 +35,7 @@ dataset:
     batch_size: 1
     is_train: True
     max_size: inf
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: A
       - name: LoadImageFromFile
@@ -67,7 +67,7 @@ dataset:
     batch_size: 1
     max_size: inf
     is_train: False
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: A
       - name: LoadImageFromFile

configs/pix2pix_cityscapes.yaml

@@ -61,7 +61,7 @@ dataset:
     dataroot: data/cityscapes/test
     num_workers: 4
     batch_size: 1
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: pair
       - name: SplitPairedImage

configs/pix2pix_cityscapes_2gpus.yaml

@@ -61,7 +61,7 @@ dataset:
     dataroot: data/cityscapes/test
     num_workers: 4
     batch_size: 1
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: pair
     - name: Transforms

configs/pix2pix_facades.yaml

@@ -61,7 +61,7 @@ dataset:
     dataroot: data/facades/test
     num_workers: 4
     batch_size: 1
-    load_pipeline:
+    preprocess:
       - name: LoadImageFromFile
         key: pair
     - name: Transforms

ppgan/apps/realsr_predictor.py

@@ -60,7 +60,8 @@ def run_image(self, img):
 
         img = self.norm(ori_img)
         x = paddle.to_tensor(img[np.newaxis, ...])
-        out = self.model(x)
+        with paddle.no_grad():
+            out = self.model(x)
 
         pred_img = self.denorm(out.numpy()[0])
         pred_img = Image.fromarray(pred_img)

ppgan/engine/trainer.py

@@ -124,6 +124,9 @@ def __init__(self, cfg):
         self.weight_interval = cfg.snapshot_config.interval
         self.log_interval = cfg.log_config.interval
         self.visual_interval = cfg.log_config.visiual_interval
+        if self.by_epoch:
+            self.weight_interval *= self.iters_per_epoch
+
         self.validate_interval = -1
         if cfg.get('validate', None) is not None:
             self.validate_interval = cfg.validate.get('interval', -1)
@@ -177,16 +180,12 @@ def train(self):
 
             self.model.lr_scheduler.step()
 
-            if self.by_epoch:
-                temp = self.current_epoch
-            else:
-                temp = self.current_iter
-            if self.validate_interval > -1 and temp % self.validate_interval == 0:
+            if self.validate_interval > -1 and self.current_iter % self.validate_interval == 0:
                 self.test()
 
-            if temp % self.weight_interval == 0:
-                self.save(temp, 'weight', keep=-1)
-                self.save(temp)
+            if self.current_iter % self.weight_interval == 0:
+                self.save(self.current_iter, 'weight', keep=-1)
+                self.save(self.current_iter)
 
             self.current_iter += 1
 
@@ -335,7 +334,12 @@ def save(self, epoch, name='checkpoint', keep=1):
         assert name in ['checkpoint', 'weight']
 
         state_dicts = {}
-        save_filename = 'epoch_%s_%s.pdparams' % (epoch, name)
+        if self.by_epoch:
+            save_filename = 'epoch_%s_%s.pdparams' % (
+                epoch // self.iters_per_epoch, name)
+        else:
+            save_filename = 'iter_%s_%s.pdparams' % (epoch, name)
+
         save_path = os.path.join(self.output_dir, save_filename)
         for net_name, net in self.model.nets.items():
             state_dicts[net_name] = net.state_dict()
@@ -353,9 +357,16 @@ def save(self, epoch, name='checkpoint', keep=1):
 
         if keep > 0:
             try:
-                checkpoint_name_to_be_removed = os.path.join(
-                    self.output_dir,
-                    'epoch_%s_%s.pdparams' % (epoch - keep, name))
+                if self.by_epoch:
+                    checkpoint_name_to_be_removed = os.path.join(
+                        self.output_dir, 'epoch_%s_%s.pdparams' %
+                        ((epoch - keep * self.weight_interval) //
+                         self.iters_per_epoch, name))
+                else:
+                    checkpoint_name_to_be_removed = os.path.join(
+                        self.output_dir, 'iter_%s_%s.pdparams' %
+                        (epoch - keep * self.weight_interval, name))
+
                 if os.path.exists(checkpoint_name_to_be_removed):
                     os.remove(checkpoint_name_to_be_removed)
 
@@ -366,7 +377,7 @@ def resume(self, checkpoint_path):
         state_dicts = load(checkpoint_path)
         if state_dicts.get('epoch', None) is not None:
             self.start_epoch = state_dicts['epoch'] + 1
-            self.global_steps = self.steps_per_epoch * state_dicts['epoch']
+            self.global_steps = self.iters_per_epoch * state_dicts['epoch']
 
         for net_name, net in self.model.nets.items():
             net.set_state_dict(state_dicts[net_name])

ppgan/utils/options.py

@@ -17,7 +17,8 @@
 
 def parse_args():
     parser = argparse.ArgumentParser(description='PaddleGAN')
-    parser.add_argument('--config-file',
+    parser.add_argument('-c',
+                        '--config-file',
                         metavar="FILE",
                         help='config file path')
     # cuda setting

ppgan/utils/setup.py

@@ -26,8 +26,10 @@ def setup(args, cfg):
         cfg.is_train = True
 
     cfg.timestamp = time.strftime('-%Y-%m-%d-%H-%M', time.localtime())
-    cfg.output_dir = os.path.join(cfg.output_dir,
-                                  str(cfg.model.name) + cfg.timestamp)
+    cfg.output_dir = os.path.join(
+        cfg.output_dir,
+        os.path.splitext(os.path.basename(str(args.config_file)))[0] +
+        cfg.timestamp)
 
     logger = setup_logger(cfg.output_dir)