How to Fit my model using transfer learning Vgg - tensorflow

Question

I'm new to Machine learning i got 1 example of Cat vs Dog image classification
and here is the link to it
https://pythonprogramming.net/convolutional-neural-network-kats-vs-dogs-machine-learning-tutorial/
It worked perfectly , but now when i want to implement transfer learning to it using VGG16 , it's not working
from keras.models import Sequential, Model, load_model
from keras.applications.vgg16 import VGG16
from keras import optimizers
from keras.layers import Dropout, Flatten, Dense, Activation
from keras.models import Sequential
from keras import utils
train = train_data[:-500]
test = train_data[-500:]
X = np.array([i[0] for i in train]).reshape(-1,IMG_SIZE,IMG_SIZE,3)
Y = [i[1] for i in train]
test_x = np.array([i[0] for i in test]).reshape(-1,IMG_SIZE,IMG_SIZE,3)
test_y = np.array([i[1] for i in test])
from keras.layers import Activation, Conv2D, Dense, Dropout, Flatten, MaxPooling2D
from keras.models import Sequential
modelvgg = VGG16(weights='imagenet', include_top=False, input_shape=(50,50,3))
type(modelvgg)
modelvgg.layers.pop()
model = Sequential()
for layer in modelvgg.layers:
model.add(layer)
for layer in model.layers:
layer.trainable = False
model.add(Dense(1, activation= 'sigmoid'))
model.compile(optimizer='adam', learning_rate=LR, loss='categorical_crossentropy', name='targets')
model.summary()
model.fit({'input': X}, {'targets': Y}, n_epoch=10, validation_set=({'input': test_x}, {'targets': test_y}),
snapshot_step=500, show_metric=True, run_id=MODEL_NAME)
Here is the Error i always get
I guess there's a problem i guess of how i'm fitting my module so please i need help with that
Unrecognized keyword arguments: {'n_epoch': 10, 'validation_set': ({'input': array([[[[ 41, 40, 36],
[ 43, 42, 38],
[ 43, 42, 38],

Answer 1

The tutorial you linked does not use keras but tflearn, no wonder the fit call does not work. A correct call with keras would be:
model.fit(X, Y, epochs=10, validation_data=(test_x, test_y))