diff --git a/components/Generator_modulation_depthwise.py b/components/Generator_modulation_depthwise.py
index 79064fa..f632d4f 100644
--- a/components/Generator_modulation_depthwise.py
+++ b/components/Generator_modulation_depthwise.py
@@ -5,7 +5,7 @@
 # Created Date: Sunday January 16th 2022
 # Author: Chen Xuanhong
 # Email: chenxuanhongzju@outlook.com
-# Last Modified:  Monday, 14th February 2022 11:35:32 pm
+# Last Modified:  Tuesday, 15th February 2022 1:54:50 am
 # Modified By: Chen Xuanhong
 # Copyright (c) 2022 Shanghai Jiao Tong University
 #############################################################
@@ -119,8 +119,11 @@ class Generator(nn.Module):
 
         # self.first_layer = nn.Sequential(nn.ReflectionPad2d(3), nn.Conv2d(3, 64, kernel_size=7, padding=0, bias=False),
                                 # nn.BatchNorm2d(64), activation)
-        self.first_layer = nn.Sequential(nn.Conv2d(3, 64, kernel_size=3, padding=1, bias=False),
+        self.first_layer = nn.Sequential(nn.ReflectionPad2d(1), 
+                              nn.Conv2d(3, 64, kernel_size=3, padding=0, bias=False),
                                 nn.BatchNorm2d(64), activation)
+        # self.first_layer = nn.Sequential(nn.Conv2d(3, 64, kernel_size=3, padding=1, bias=False),
+        #                         nn.BatchNorm2d(64), activation)
         ### downsample
         self.down1 = nn.Sequential(nn.Conv2d(64, 64, kernel_size=3, groups=64, padding=1, stride=2),
                                 nn.Conv2d(64, 128, kernel_size=1, bias=False),
@@ -164,7 +167,9 @@ class Generator(nn.Module):
             DeConv(128,64,3),
             nn.BatchNorm2d(64), activation
         )
-        self.last_layer = nn.Sequential(nn.Conv2d(64, 3, kernel_size=3, padding=1))
+        # self.last_layer = nn.Sequential(nn.Conv2d(64, 3, kernel_size=3, padding=1))
+        self.last_layer = nn.Sequential(nn.ReflectionPad2d(1),
+                    nn.Conv2d(64, 3, kernel_size=3, padding=0))
         # self.last_layer = nn.Sequential(nn.ReflectionPad2d(3),
         #             nn.Conv2d(64, 3, kernel_size=7, padding=0))
 
diff --git a/data_tools/data_loader_VGGFace2HQ_multigpu.py b/data_tools/data_loader_VGGFace2HQ_multigpu.py
index 4afb779..d8e4570 100644
--- a/data_tools/data_loader_VGGFace2HQ_multigpu.py
+++ b/data_tools/data_loader_VGGFace2HQ_multigpu.py
@@ -5,7 +5,7 @@
 # Created Date: Sunday February 6th 2022
 # Author: Chen Xuanhong
 # Email: chenxuanhongzju@outlook.com
-# Last Modified:  Tuesday, 15th February 2022 1:35:41 am
+# Last Modified:  Tuesday, 15th February 2022 1:50:19 am
 # Modified By: Chen Xuanhong
 # Copyright (c) 2022 Shanghai Jiao Tong University
 #############################################################
@@ -56,7 +56,7 @@ class InfiniteSampler(torch.utils.data.Sampler):
 
 class data_prefetcher():
     def __init__(self, loader, cur_gpu):
-        torch.cuda.set_device(cur_gpu)
+        torch.cuda.set_device(cur_gpu)  # must add this line to avoid excessive use of GPU 0 by the prefetcher
         self.loader = loader
         self.dataiter = iter(loader)
         self.stream = torch.cuda.Stream(device=cur_gpu)
diff --git a/train_yamls/train_Depthwise.yaml b/train_yamls/train_Depthwise.yaml
index dabff36..dab4d2f 100644
--- a/train_yamls/train_Depthwise.yaml
+++ b/train_yamls/train_Depthwise.yaml
@@ -29,7 +29,7 @@ dataloader: VGGFace2HQ_multigpu
 dataset_name: vggface2_hq
 dataset_params:
   random_seed: 1234
-  dataloader_workers: 4
+  dataloader_workers: 6
 
 eval_dataloader: DIV2K_hdf5
 eval_dataset_name: DF2K_H5_Eval