fix scope bug for interpret

paddlex/interpret/interpretation_predict.py

@@ -15,11 +15,17 @@
 import numpy as np
 import cv2
 import copy
+import paddle.fluid as fluid
+from paddlex.cv.transforms import arrange_transforms
 
 
 def interpretation_predict(model, images):
     images = images.astype('float32')
-    model.arrange_transforms(transforms=model.test_transforms, mode='test')
+    arrange_transforms(
+        model.model_type,
+        model.__class__.__name__,
+        transforms=model.test_transforms,
+        mode='test')
     tmp_transforms = copy.deepcopy(model.test_transforms.transforms)
     model.test_transforms.transforms = model.test_transforms.transforms[-2:]
 
@@ -29,7 +35,9 @@ def interpretation_predict(model, images):
         new_imgs.append(model.test_transforms(images[i])[0])
 
     new_imgs = np.array(new_imgs)
-    out = model.exe.run(model.test_prog,
+    with fluid.scope_guard(model.scope):
+        out = model.exe.run(
+            model.test_prog,
             feed={'image': new_imgs},
             fetch_list=list(model.interpretation_feats.values()))
 

paddlex/interpret/visualize.py

@@ -22,6 +22,7 @@ from .interpretation_predict import interpretation_predict
 from .core.interpretation import Interpretation
 from .core.normlime_base import precompute_global_classifier
 from .core._session_preparation import gen_user_home
+from paddlex.cv.transforms import arrange_transforms
 
 
 def lime(img_file, model, num_samples=3000, batch_size=50, save_dir='./'):
@@ -48,7 +49,11 @@ def lime(img_file, model, num_samples=3000, batch_size=50, save_dir='./'):
             'The interpretation only can deal with the Normal model')
     if not osp.exists(save_dir):
         os.makedirs(save_dir)
-    model.arrange_transforms(transforms=model.test_transforms, mode='test')
+    arrange_transforms(
+        model.model_type,
+        model.__class__.__name__,
+        transforms=model.test_transforms,
+        mode='test')
     tmp_transforms = copy.deepcopy(model.test_transforms)
     tmp_transforms.transforms = tmp_transforms.transforms[:-2]
     img = tmp_transforms(img_file)[0]
@@ -94,7 +99,11 @@ def normlime(img_file,
             'The interpretation only can deal with the Normal model')
     if not osp.exists(save_dir):
         os.makedirs(save_dir)
-    model.arrange_transforms(transforms=model.test_transforms, mode='test')
+    arrange_transforms(
+        model.model_type,
+        model.__class__.__name__,
+        transforms=model.test_transforms,
+        mode='test')
     tmp_transforms = copy.deepcopy(model.test_transforms)
     tmp_transforms.transforms = tmp_transforms.transforms[:-2]
     img = tmp_transforms(img_file)[0]