gistfile1.txt

from keras.applications.vgg16 import VGG16
from keras.layers.core import Dense
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.layers.pooling import GlobalAveragePooling2D
from keras.optimizers import SGD, RMSprop, Adam

# Roughly the code I had writted
base_model = VGG16(weights='imagenet')
for layer im base_model.layers:
  layer.trainable = False
# Grab the second-to-last layer (to bypass the built-in predictions layer)
build_off = model.get_layer('fc2') 
predictions = Dense(2, activation='softmax')(build_off.output)
model = Model(base_model.input, predictions)
model.compile(optimizer=Adam(lr=0.001), loss='categorical_crossentropy', metrics=['accuracy'])