- do not generate and load all datasets to save memory for larger tes…

…t sets
dsmic · Aug 23, 2019 · 2850bf8 · 2850bf8
1 parent 871f24a
commit 2850bf8
Showing 1 changed file with 3 additions and 5 deletions.
diff --git a/few_shot_tests.py b/few_shot_tests.py
@@ -61,20 +61,18 @@ def idx_to_big(self, phase, idx):
 cathegories = 5
 dataloader = OurMiniImageNetDataLoader(shot_num=5 * 2, way_num=cathegories, episode_test_sample_num=args.episode_test_sample_num, shuffle_images = args.shuffle_images) #twice shot_num is because one might be uses as the base for the samples
 
-dataloader.generate_data_list(phase='train')
-dataloader.generate_data_list(phase='val')
-dataloader.generate_data_list(phase='test')
+dataloader.generate_data_list(phase=args.dataset)
 
 print('mode is',args.dataset)
-dataloader.load_list('all')
+dataloader.load_list(args.dataset)
 
 #print('train',dataloader.train_filenames)
 #print('val',dataloader.val_filenames)
 #print('test',dataloader.test_filenames)
 
 
 base_train_img, base_train_label, base_test_img, base_test_label = \
-        dataloader.get_batch(phase='train', idx=0) 
+        dataloader.get_batch(phase=args.dataset, idx=0) 
 
 train_epoch_size = base_train_img.shape[0]
 if not args.train_indep_and_dependent: