Added batch norm and activation before avg pooling (raghakot#31)

xhwhappy · Feb 2, 2017 · 6abded5 · 6abded5
1 parent 5017ca9
commit 6abded5
Showing 1 changed file with 4 additions and 1 deletion.
diff --git a/resnet.py b/resnet.py
@@ -200,10 +200,13 @@ def build(input_shape, num_outputs, block_fn, repetitions):
         # Last activation
         block = _bn_relu(block)
 
+        block_norm = BatchNormalization(mode=0, axis=CHANNEL_AXIS)(block)
+        block_output = Activation("relu")(block_norm)
+
         # Classifier block
         pool2 = AveragePooling2D(pool_size=(block._keras_shape[ROW_AXIS],
                                             block._keras_shape[COL_AXIS]),
-                                 strides=(1, 1))(block)
+                                 strides=(1, 1))(block_output)
         flatten1 = Flatten()(pool2)
         dense = Dense(output_dim=num_outputs, init="he_normal", activation="softmax")(flatten1)