Remove unused parts of MobileNetV2

bob/ip/binseg/modeling/backbones/mobilenetv2.py

@@ -80,14 +80,14 @@ class MobileNetV2(nn.Module):
             [6, 32, 3, 2],
             [6, 64, 4, 2],
             [6, 96, 3, 1],
-            [6, 160, 3, 2],
-            [6, 320, 1, 1],
+            #[6, 160, 3, 2],
+            #[6, 320, 1, 1],
         ]
 
         # building first layer
         assert input_size % 32 == 0
         input_channel = int(input_channel * width_mult)
-        self.last_channel = int(last_channel * width_mult) if width_mult > 1.0 else last_channel
+        #self.last_channel = int(last_channel * width_mult) if width_mult > 1.0 else last_channel
         self.features = [conv_bn(3, input_channel, 2)]
         # building inverted residual blocks
         for t, c, n, s in interverted_residual_setting:
@@ -99,15 +99,15 @@ class MobileNetV2(nn.Module):
                     self.features.append(block(input_channel, output_channel, 1, expand_ratio=t))
                 input_channel = output_channel
         # building last several layers
-        self.features.append(conv_1x1_bn(input_channel, self.last_channel))
+        #self.features.append(conv_1x1_bn(input_channel, self.last_channel))
         # make it nn.Sequential
         self.features = nn.Sequential(*self.features)
 
         # building classifier
-        self.classifier = nn.Sequential(
-            nn.Dropout(0.2),
-            nn.Linear(self.last_channel, n_class),
-        )
+        #self.classifier = nn.Sequential(
+        #    nn.Dropout(0.2),
+        #    nn.Linear(self.last_channel, n_class),
+        #)
 
         self._initialize_weights()