Update networks/decoder.py

networks/decoder.py

@@ -5,7 +5,6 @@ import torch.nn as nn
 from torch import Tensor
 import torch.nn.functional as F
 
-from mmcv.cnn import build_upsample_layer
 from mmseg.models.decode_heads.psp_head import PPM
 
 class Decoder(nn.Module):
@@ -74,15 +73,14 @@ class Decoder(nn.Module):
         """Make deconv layers."""
         layers = []
         layers.append(
-            build_upsample_layer(
-                dict(type='deconv'),
-                in_channels=in_channel,
-                out_channels=out_channel,
-                kernel_size=2,
-                stride=2,
-                padding=0,
-                output_padding=0,
-                bias=False))
+            nn.ConvTranspose2d(
+            in_channels=in_channel,
+            out_channels=out_channel,
+            kernel_size=2,
+            stride=2,
+            padding=0,
+            output_padding=0,
+            bias=False))
         layers.append(nn.BatchNorm2d(out_channel))
         layers.append(nn.ReLU(inplace=True))
         self.upper_module_dict[name] = nn.Sequential(*layers)