add missing he_normal initializer to final dense layer

Author: andrewferlitsch

zoo/resnext/resnext.py

@@ -155,7 +155,7 @@ def classifier(x, n_classes):
     """
     # Final Dense Outputting Layer 
     x = GlobalAveragePooling2D()(x)
-    outputs = Dense(n_classes, activation='softmax')(x)
+    outputs = Dense(n_classes, activation='softmax', kernel_initializer='he_normal')(x)
     return outputs
 
 # Meta-parameter: number of filters in, out and number of blocks

zoo/resnext/resnext_c.py

@@ -207,7 +207,7 @@ def classifier(self, x, n_classes):
         """
         # Final Dense Outputting Layer 
         x = GlobalAveragePooling2D()(x)
-        outputs = Dense(n_classes, activation='softmax')(x)
+        outputs = Dense(n_classes, activation='softmax', kernel_initializer=self.init_weights)(x)
         return outputs
 
 

zoo/resnext/resnext_cifar10.py

@@ -99,7 +99,7 @@ def classifier(x, nclasses):
     """
     # Final Dense Outputting Layer for the outputs
     x = GlobalAveragePooling2D()(x)
-    outputs = Dense(nclasses, activation='softmax')(x)
+    outputs = Dense(nclasses, activation='softmax', kernel_initializer='he_normal')(x)
     return outputs
 
 # Meta-parameter: width of group convolutional