Is there a way to save the execution of a particular block of code in a notebook such that I don't have to run it again. And can continue with the rest of code after reloading?
For example,
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf
from tensorflow.keras import datasets, layers, models
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
(train_images1, train_labels), (test_images1, test_labels) = datasets.cifar10.load_data()
# Normalize pixel values to be between 0 and 1
train_images, test_images = train_images1 / 255.0, test_images1 / 255.0
#My cnn model, upto the training
#Save upto here.
Can I save the execution upto here for later usage, that is including the downloaded files and trained model.
Save Model:
model_json = model.to_json()
with open("model.json", "w") as json_file:
json_file.write(model_json)
model.save_weights("model.h5")
print("Saved model .......")
Load saved Model:
json_file = open('model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
loaded_model.load_weights("model.h5")
print("Loaded model...........")
For more details, You can find my implementation here. Now this will save both dataset as well as trained model also.