From b878862fbf449178fe314d31c03c615433c17f5d Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Thu, 7 Mar 2019 00:17:41 +0000 Subject: Add get_lenet_icp --- lenet.py | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/lenet.py b/lenet.py index 97479ed..71b1c9e 100644 --- a/lenet.py +++ b/lenet.py @@ -57,7 +57,7 @@ def get_lenet(shape): model = keras.Sequential() model.add(Conv2D(filters=6, kernel_size=(3, 3), activation='relu', input_shape=shape)) model.add(AveragePooling2D()) - + model.add(Conv2D(filters=16, kernel_size=(3, 3), activation='relu')) model.add(AveragePooling2D()) model.add(Flatten()) @@ -68,6 +68,20 @@ def get_lenet(shape): model.add(Dense(units=10, activation = 'relu')) return model +def get_lenet_icp(shape): + model = keras.Sequential() + model.add(Conv2D(filters=6, kernel_size=(3, 3), activation='relu', input_shape=(32,32,1))) + model.add(AveragePooling2D()) + + model.add(Conv2D(filters=16, kernel_size=(3, 3), activation='relu')) + model.add(AveragePooling2D()) + model.add(Flatten()) + + model.add(Dense(units=120, activation='relu')) + model.add(Dense(units=84, activation='relu')) + model.add(Dense(units=10, activation = 'relu')) + return model + def plot_history(history, metric = None): # Plots the loss history of training and validation (if existing) # and a given metric -- cgit v1.2.3