alexnet.py

# Import necessary components to build LeNet
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Conv2D, MaxPooling2D, ZeroPadding2D
from keras.layers.normalization import BatchNormalization
from keras.regularizers import l2

# Initialize model
alexnet = Sequential()

# Layer 1
alexnet.add(Conv2D(96, (11, 11), input_shape=(150,150,3)))
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))

# Layer 2
alexnet.add(Conv2D(256, (5, 5), padding='same'))
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))

# Layer 3
alexnet.add(Conv2D(512, (3, 3), padding='same'))
alexnet.add(Activation('relu'))

# Layer 4
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(Activation('relu'))

# Layer 5
alexnet.add(Conv2D(1024, (3, 3), padding='same'))
alexnet.add(Activation('relu'))
alexnet.add(MaxPooling2D(pool_size=(2, 2)))

# Layer 6
alexnet.add(Flatten())
alexnet.add(Dense(3072))
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))

# Layer 7
alexnet.add(Dense(4096))
alexnet.add(Activation('relu'))
alexnet.add(Dropout(0.5))

# Layer 8
alexnet.add(Dense(1000))
alexnet.add(Activation('softmax'))

alexnet.summary()