Fix bug in densenet

Author: calmiLovesAI

README.md

@@ -22,7 +22,7 @@ For ResNet, see : https://github.com/calmisential/TensorFlow2.0_ResNet
 ## Train
 1. Requirements:
 + Python >= 3.6
-+ Tensorflow == 2.2.0-rc1
++ Tensorflow >= 2.2.0rc3
 2. To train the network on your own dataset, you can put the dataset under the folder **original dataset**, and the directory should look like this:
 ```
 |——original dataset

configuration.py

@@ -42,5 +42,5 @@
 # b5 = (1.6, 2.2, 456, 0.4)
 # b6 = (1.8, 2.6, 528, 0.5)
 # b7 = (2.0, 3.1, 600, 0.5)
-model_index = 12
+model_index = 21
 

models/densenet.py

@@ -35,18 +35,17 @@ def __init__(self, num_layers, growth_rate, drop_rate):
         self.growth_rate = growth_rate
         self.drop_rate = drop_rate
         self.features_list = []
-
-    def _make_layer(self, x, training):
-        y = BottleNeck(growth_rate=self.growth_rate, drop_rate=self.drop_rate)(x, training=training)
-        self.features_list.append(y)
-        y = tf.concat(self.features_list, axis=-1)
-        return y
+        self.bottle_necks = []
+        for i in range(self.num_layers):
+            self.bottle_necks.append(BottleNeck(growth_rate=self.growth_rate, drop_rate=self.drop_rate))
 
     def call(self, inputs, training=None, **kwargs):
         self.features_list.append(inputs)
-        x = self._make_layer(inputs, training=training)
-        for i in range(1, self.num_layers):
-            x = self._make_layer(x, training=training)
+        x = inputs
+        for i in range(self.num_layers):
+            y = self.bottle_necks[i](x, training=training)
+            self.features_list.append(y)
+            x = tf.concat(self.features_list, axis=-1)
         self.features_list.clear()
         return x