Merge branch 'python3.8' into python3.7

# Conflicts:
#	utils/configuration.py

2 files changed, 7 insertions, 7 deletions

diff --git a/config.py b/config.py
index b9df470..25846a2 100644
--- a/config.py
+++ b/config.py
@@ -7,7 +7,9 @@ config = {
         # Directory used in training or testing for temporary storage
         'save_dir': 'runs',
         # Recorde disentangled image or not
-        'image_log_on': False
+        'image_log_on': False,
+        # The number of subjects for validating (Part of testing set)
+        'val_size': 10,
     },
     # Dataset settings
     'dataset': {
@@ -17,8 +19,6 @@ config = {
         'root_dir': 'data/CASIA-B-MRCNN-V2/SEG',
         # The number of subjects for training
         'train_size': 74,
-        # The number of subjects for validating (Part of testing set)
-        'val_size': 10,
         # Number of sampled frames per sequence (Training only)
         'num_sampled_frames': 30,
         # Truncate clips longer than `truncate_threshold`
diff --git a/models/model.py b/models/model.py
index 7eaaaf0..78a9c0f 100644
--- a/models/model.py
+++ b/models/model.py
@@ -76,6 +76,7 @@ class Model:
         self.scheduler: Optional[optim.lr_scheduler.StepLR] = None
         self.writer: Optional[SummaryWriter] = None
         self.image_log_on = system_config.get('image_log_on', False)
+        self.val_size = system_config.get('val_size', 10)
 
         self.CASIAB_GALLERY_SELECTOR = {
             'selector': {'conditions': ClipConditions({r'nm-0[1-4]'})}
@@ -144,13 +145,12 @@ class Model:
         self.is_train = True
         # Validation dataset
         # (the first `val_size` subjects from evaluation set)
-        val_size = dataset_config.pop('val_size', 10)
         val_dataset_config = copy.deepcopy(dataset_config)
         train_size = dataset_config.get('train_size', 74)
-        val_dataset_config['train_size'] = train_size + val_size
+        val_dataset_config['train_size'] = train_size + self.val_size
         val_dataset_config['selector']['classes'] = ClipClasses({
             str(c).zfill(3)
-            for c in range(train_size + 1, train_size + val_size + 1)
+            for c in range(train_size + 1, train_size + self.val_size + 1)
         })
         val_dataset = self._parse_dataset_config(val_dataset_config)
         val_dataloader = iter(self._parse_dataloader_config(
@@ -566,7 +566,7 @@ class Model:
         for (iter_, total_iter, (condition, selector)) in zip(
                 iters, self.total_iters, dataset_selectors.items()
         ):
-            self.curr_iter = iter_
+            self.curr_iter = iter_ - 1
             self.total_iter = total_iter
             self._dataset_sig = self._make_signature(
                 dict(**dataset_config, **selector),