diff options
| -rw-r--r-- | lenet.py | 16 | 
1 files changed, 15 insertions, 1 deletions
| @@ -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 | 
