Simple python snippet for downloading a VGG16 model and saving it as savedmodel

savedmodel_simple.py

import os
os.environ["CUDA_VISIBLE_DEVICES"] = ""
import tensorflow as tf
import tensorflow.keras.backend as K
from pathlib import Path 

#leaving this line in case someone needs it, just uncomment the line below and comment the next line
#model = tf.keras.models.load_model(model_path,compile=False)
model = tf.keras.applications.vgg16.VGG16(include_top = True, weights="imagenet", input_shape=(224,224,3))

@tf.function
def serve(*args, **kwargs):
    outputs = model(*args, **kwargs)
    # Apply postprocessing steps, or add additional outputs.
    ...
    return outputs

# arg_specs is `[tf.TensorSpec(...), ...]`. kwarg_specs, in this
# example, is an empty dict since functional models do not use keyword
# arguments.
arg_specs, kwarg_specs = model.save_spec()
#we create the output folder in case it does not exist

op_folder = "output_foler"
Path(op_folder).mkdir(parents=True, exist_ok = True)


savepath = f"{op_folder}/testmodel"

model.save(savepath, signatures={
  'serving_default': serve.get_concrete_function(*arg_specs,
                                                 **kwarg_specs)
})