text_plain_output_1.png
from keras.layers import Convolution2D,MaxPooling2D,Flatten,Dense,Dropout

from keras.models import Sequential

model = Sequential()
model.add(Convolution2D(96, 11, strides=(4, 4), padding='valid', input_shape=(227, 227, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2), padding='valid'))
model.add(Convolution2D(256, 5, strides=(1, 1), padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2), padding='valid'))
model.add(Convolution2D(384, 3, strides=(1, 1), padding='same', activation='relu'))
model.add(Convolution2D(384, 3, strides=(1, 1), padding='same', activation='relu'))
model.add(Convolution2D(256, 3, strides=(1, 1), padding='same', activation='relu'))
model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2), padding='valid'))
model.add(Flatten())
model.add(Dense(units=4096, activation='relu'))
model.add(Dense(units=4096, activation='relu'))
model.add(Dense(units=10, activation='softmax'))
model.summary()