[keras] layers: added get_config for saving and loading

keras.py

@@ -846,6 +846,12 @@ class DenseLayer(tf.keras.layers.Layer):
 
     def __init__(self, nodes=0, activation=None, dropout=0.0, l2=0, batch_norm=False):
         super().__init__()
+        self.nodes = nodes
+        self.activation = activation
+        self.dropout = dropout
+        self.l2 = l2
+        self.batch_norm = batch_norm
+
         parts = []
 
         l2 = tf.keras.regularizers.l2(l2 if l2 else 0.0)
@@ -874,6 +880,15 @@ class DenseLayer(tf.keras.layers.Layer):
             x = part(x, training=training)
         return x
 
+    def get_config(self):
+        return {
+            "nodes": self.nodes,
+            "activation": self.activation,
+            "dropout": self.dropout,
+            "l2": self.l2,
+            "batch_norm": self.batch_norm,
+        }
+
 
 class ResNetBlock(tf.keras.layers.Layer):
     """
@@ -890,9 +905,9 @@ class ResNetBlock(tf.keras.layers.Layer):
 
     def __init__(self, config, jump=2, **kwargs):
         super().__init__(name="ResNetBlock")
-
+        self.jump = jump
         layers = []
-        for i in range(jump - 1):
+        for i in range(self.jump - 1):
             layers.append(DenseLayer(**kwargs))
 
         activation = kwargs.pop("activation")
@@ -908,6 +923,9 @@ class ResNetBlock(tf.keras.layers.Layer):
         x = self.out_activation(x)
         return x
 
+    def get_config(self):
+        return {"jump": self.jump}
+
 
 class FullyConnected(tf.keras.layers.Layer):
     """
@@ -924,9 +942,9 @@ class FullyConnected(tf.keras.layers.Layer):
 
     def __init__(self, number_layers=0, **kwargs):
         super().__init__(name="FullyConnected")
-
+        self.number_layers = number_layers
         layers = []
-        for layer in range(number_layers):
+        for layer in range(self.number_layers):
             layers.append(DenseLayer(**kwargs))
         self.layers = layers
 
@@ -936,6 +954,9 @@ class FullyConnected(tf.keras.layers.Layer):
             x = layer(x, training=training)
         return x
 
+    def get_config(self):
+        return {"number_layers": self.number_layers}
+
 
 class ResNet(tf.keras.layers.Layer):
     """
@@ -952,9 +973,9 @@ class ResNet(tf.keras.layers.Layer):
 
     def __init__(self, number_layers=1, **kwargs):
         super().__init__(name="ResNet")
-
+        self.number_layers = number_layers
         layers = []
-        for i in range(number_layers):
+        for i in range(self.number_layers):
             layers.append(ResNetBlock(**kwargs))
         self.layers = layers
 
@@ -963,3 +984,8 @@ class ResNet(tf.keras.layers.Layer):
         for layer in self.layers:
             x = layer(x, training=training)
         return x
+
+    def get_config(self):
+        return {"number_layers": self.number_layers}
+
+