diff --git a/applications/tools/first-order-demo.py b/applications/tools/first-order-demo.py
index 0450fb7870f1ccd9aeaca00d4f86c389d66b250a..40e6c1a35549aaeaf1181d23c47c3f968fe94f21 100644
--- a/applications/tools/first-order-demo.py
+++ b/applications/tools/first-order-demo.py
@@ -3,10 +3,6 @@ matplotlib.use('Agg')
 import os
 import sys
 
-# cur_path = os.path.abspath(os.path.dirname(__file__))
-# root_path = os.path.split(cur_path)[0]
-# sys.path.append(root_path)
-
 import yaml
 import pickle
 from argparse import ArgumentParser
diff --git a/ppgan/models/generators/occlusion_aware.py b/ppgan/models/generators/occlusion_aware.py
index df4264cf82c49c585ac5816407804606dbec3316..05289d6b21481319f1dcc6fdc407c978e01cff70 100644
--- a/ppgan/models/generators/occlusion_aware.py
+++ b/ppgan/models/generators/occlusion_aware.py
@@ -81,9 +81,10 @@ class OcclusionAwareGenerator(nn.Layer):
             deformation = deformation.transpose([0, 3, 1, 2])
             deformation = F.interpolate(deformation,
                                         size=(h, w),
-                                        mode='bilinear')
+                                        mode='bilinear',
+                                        align_corners=False)
             deformation = deformation.transpose([0, 2, 3, 1])
-        return F.grid_sample(inp, deformation)
+        return F.grid_sample(inp, deformation, align_corners=False)
 
     def forward(self, source_image, kp_driving, kp_source):
         # Encoding (downsampling) part
@@ -113,7 +114,8 @@ class OcclusionAwareGenerator(nn.Layer):
                         3] != occlusion_map.shape[3]:
                     occlusion_map = F.interpolate(occlusion_map,
                                                   size=out.shape[2:],
-                                                  mode='bilinear')
+                                                  mode='bilinear',
+                                                  align_corners=False)
                 out = out * occlusion_map
 
             output_dict["deformed"] = self.deform_input(source_image,
diff --git a/ppgan/modules/first_order.py b/ppgan/modules/first_order.py
index 1e02c36c175ee7fdbedf0e859e1cbdabb2d30595..fde071ad5d164fb9497cb23c2189e6cc1584657f 100644
--- a/ppgan/modules/first_order.py
+++ b/ppgan/modules/first_order.py
@@ -2,8 +2,6 @@ import paddle
 import paddle.nn as nn
 import paddle.nn.functional as F
 
-# from sync_batchnorm import SynchronizedBatchNorm2d as BatchNorm2d
-
 
 def kp2gaussian(kp, spatial_size, kp_variance):
     """
@@ -44,7 +42,6 @@ def make_coordinate_grid(spatial_size, type):
     xx = paddle.tile(x.reshape([1, -1]), [h, 1])
 
     meshed = paddle.concat([xx.unsqueeze(2), yy.unsqueeze(2)], 2)
-    # meshed = paddle.concat([xx.unsqueeze_(2), yy.unsqueeze_(2)], 2)
 
     return meshed
 
@@ -261,10 +258,7 @@ class AntiAliasInterpolation2d(nn.Layer):
         # Make sure sum of values in gaussian kernel equals 1.
         kernel = kernel / paddle.sum(kernel)
         # Reshape to depthwise convolutional weight
-        # print('debug shape:', kernel.shape)
-        # print('debug shape 1:', kernel.dim())
         kernel = kernel.reshape([1, 1, *kernel.shape])
-        # kernel = kernel.repeat(channels, *[1] * (kernel.dim() - 1))
         kernel = paddle.tile(kernel, [channels, *[1] * (kernel.dim() - 1)])
 
         self.register_buffer('weight', kernel)
diff --git a/requirments.txt b/requirments.txt
index fa9cf06427ae88cdded67bd3d5853f32a1f5e34f..51a8cf8ad94a9680d93b277d97fbdf4a3b6325a7 100644
--- a/requirments.txt
+++ b/requirments.txt
@@ -1 +1,4 @@
-tqdm
\ No newline at end of file
+tqdm
+PyYAML>=5.1
+scikit-image>=0.14.0
+scipy>=1.1.0