bertModel.py

import tensorflow as tf

# Input Layers
input_layer = tf.keras.layers.Input(shape=(), dtype=tf.string, name='news')

# BERT layers
processed = bert_preprocess(input_layer)
output = bert_encoder(processed)

# Fully Connected Layers
layer = tf.keras.layers.Dropout(0.2, name='dropout')(output['pooled_output'])
layer = tf.keras.layers.Dense(10,activation='relu', name='hidden')(layer)
layer = tf.keras.layers.Dense(1,activation='sigmoid', name='output')(layer)


model = tf.keras.Model(inputs=[input_layer],outputs=[layer])