Keras VGG-16 model with functional API

vgg16.py

from keras.layers import Dense, Dropout, Flatten, Input
from keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.models import Model
from keras.utils.layer_utils import print_summary

VGG_PATH = 'vgg16_weights.h5'

vis_input = Input(shape=visual_shape, name="vis_input")

x = ZeroPadding2D((1,1))                           (vis_input)
x = Convolution2D(64, 3, 3, activation='relu')     (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(64, 3, 3, activation='relu')     (x)
x = MaxPooling2D((2,2), strides=(2,2))             (x)

x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(128, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(128, 3, 3, activation='relu')    (x)
x = MaxPooling2D((2,2), strides=(2,2))             (x)

x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(256, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(256, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(256, 3, 3, activation='relu')    (x)
x = MaxPooling2D((2,2), strides=(2,2))             (x)

x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = MaxPooling2D((2,2), strides=(2,2))             (x)

x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = ZeroPadding2D((1,1))                           (x)
x = Convolution2D(512, 3, 3, activation='relu')    (x)
x = MaxPooling2D((2,2), strides=(2,2))             (x)

x = Flatten()                                      (x)
x = Dense(4096, activation='relu')                 (x)
x = Dropout(0.5)                                   (x)
x = Dense(4096, activation='relu')                 (x)
x = Dropout(0.5)                                   (x)
x = Dense(1000, activation='relu')                 (x)

model = Model(input=vis_input, output=x)

print_summary(model.layers)

model.load_weights(vgg_path)