I am new to tensorflow and keras.
I trained a CNN for sentence classification using keras and exported the model using following code

```
K.set_learning_phase(0)
config = model.get_config()
weights = model.get_weights()

new_model = Sequential.from_config(config)
new_model.set_weights(weights)

builder = saved_model_builder.SavedModelBuilder(export_path)
signature = predict_signature_def(
    inputs={'input': new_model.inputs[0]},
    outputs={'prob': new_model.outputs[0]})

with K.get_session() as sess:

    builder.add_meta_graph_and_variables(
        sess=sess,
        tags=[tag_constants.SERVING],
        clear_devices = True,
        signature_def_map={
            signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signature}
    )
builder.save()

```

I got variables.data-00000-of-00001 and variables.index in variables folder and saved\_model.pb.

I want to combine these files into one file before deploying for prediction.
In the end I want to quantize the model as variables file size is really huge and I think before using the quantize functionality from tensorflow I need to have my model frozen in a pb file. 
Please help