How to Save and Load a Model Explained

Reference: https://machinelearningmastery.com/save-load-keras-deep-learning-models/

Save:

Import Libraries

from tensorflow.keras.models import model_from_json

serialize model to JSON

model_json = model.to_json()

with open("model.json", "w") as json_file: json_file.write(model_json)

serialize weights to HDF5

model.save_weights("model.h5")

print("Saved model to disk")

Once you have saved your model in the current folder, you can load it in any location by specifying the path to the directory where you saved it.

Load:

load json and create model

json_file = open('model.json', 'r')

loaded_model_json = json_file.read()

json_file.close()

loaded_model = model_from_json(loaded_model_json)

load weights into new model

loaded_model.load_weights("model.h5")

print("Loaded model from disk")

Evaluate your model on your data:

evaluate loaded model on test data

loaded_model.compile(loss='binary_crossentropy', optimizer='rmsprop', metrics=['accuracy'])

score = loaded_model.evaluate(X, Y, verbose=0)

print("%s: %.2f%%" % (loaded_model.metrics_names[1], score[1]*100))