Modify network arch

longinus/longinus/coeff_encoders/neural_network.py

@@ -29,13 +29,13 @@ class NeuralNetworkEncoder:
             self.model = keras.Sequential([
                 layers.Reshape((512, 512, 1), input_shape=(262144,)),
                 #layers.InputLayer(input_shape=(512 * 512, 1, 1)),
-                layers.Conv2D(32, (3, 3), activation=internal_activation_function, padding='same'),
+                layers.Conv2D(256, (3, 3), activation=internal_activation_function, padding='same'),
-                layers.MaxPooling2D((2, 2)),
-                layers.Conv2D(64, (3, 3), activation=internal_activation_function, padding='same'),
                 layers.MaxPooling2D((2, 2)),
                 layers.Conv2D(128, (3, 3), activation=internal_activation_function, padding='same'),
                 layers.MaxPooling2D((2, 2)),
-                layers.Conv2D(256, (3, 3), activation=internal_activation_function, padding='same'),
+                layers.Conv2D(64, (3, 3), activation=internal_activation_function, padding='same'),
+                layers.MaxPooling2D((2, 2)),
+                layers.Conv2D(32, (3, 3), activation=internal_activation_function, padding='same'),
                 layers.Flatten(),
                 layers.Dense(64, activation=external_activation_function)
             ])