diff --git a/ppgan/faceutils/face_detection/api.py b/ppgan/faceutils/face_detection/api.py
index 7b6160690daf331f4cb05bfe8328bb6fd2dd0a1d..0d503ee90d2ffbafb98d84cd1c3d85cbe7ecd870 100644
--- a/ppgan/faceutils/face_detection/api.py
+++ b/ppgan/faceutils/face_detection/api.py
@@ -64,8 +64,8 @@ class FaceAlignment:
 
         # Get the face detector
         face_detector_module = __import__(
-            'face_detection.detection.' + face_detector, globals(), locals(),
-            [face_detector], 0)
+            'ppgan.faceutils.face_detection.detection.' + face_detector,
+            globals(), locals(), [face_detector], 0)
         self.face_detector = face_detector_module.FaceDetector(verbose=verbose)
 
     def get_detections_for_batch(self, images):
diff --git a/ppgan/faceutils/face_detection/detection/sfd/sfd_detector.py b/ppgan/faceutils/face_detection/detection/sfd/sfd_detector.py
index 4db2d28364e9ac970f9458997e9bdbb155cbf170..b4d7178d939307996d822c8315a340f8086461f1 100644
--- a/ppgan/faceutils/face_detection/detection/sfd/sfd_detector.py
+++ b/ppgan/faceutils/face_detection/detection/sfd/sfd_detector.py
@@ -33,8 +33,7 @@ class SFDDetector(FaceDetector):
 
         # Initialise the face detector
         if path_to_detector is None:
-            model_weights_path = get_weights_path_from_url(
-                models_urls['s3fd'], cur_path)
+            model_weights_path = get_weights_path_from_url(models_urls['s3fd'])
             model_weights = paddle.load(model_weights_path)
         else:
             model_weights = paddle.load(path_to_detector)
diff --git a/ppgan/modules/conv.py b/ppgan/modules/conv.py
index b6018af5883072efad86bd3bc4411cf6da55f25e..2fc09c510b4073097be114393160e7f4c166bf31 100644
--- a/ppgan/modules/conv.py
+++ b/ppgan/modules/conv.py
@@ -59,7 +59,7 @@ class Conv2dTransposeRelu(nn.Layer):
                  **kwargs):
         super().__init__(*args, **kwargs)
         self.conv_block = nn.Sequential(
-            nn.ConvTranspose2D(cin, cout, kernel_size, stride, padding,
+            nn.Conv2DTranspose(cin, cout, kernel_size, stride, padding,
                                output_padding), nn.BatchNorm2D(cout))
         self.act = nn.ReLU()