rec-model.py

#Book input network
input_books = tf.layers.Input(shape=[1])
embed_books = tf.layers.Embedding(nbook_id + 1,15)(input_books)
books_out = tf.layers.Flatten()(embed_books)

#user input network
input_users = tf.layers.Input(shape=[1])
embed_users = tf.layers.Embedding(nuser_id + 1,15)(input_users)
users_out = tf.layers.Flatten()(embed_users)

conc_layer = tf.layers.Concatenate()([books_out, users_out])
x = tf.layers.Dense(128, activation='relu')(conc_layer)
x_out = x = tf.layers.Dense(1, activation='relu')(x)
model = tf.Model([input_books, input_users], x_out)