How to save and load a DNN classifier in tensorflow?

Question

How do I save and load a DNN classifier in tensorflow? Asking this for the default Iris classifier program given. (https://www.tensorflow.org/get_started/estimator)

Answer 1

To save and reuse the classifier you can just reload it with the same model_dir path.

For example in the method you want to use the classifier you can just create the classifier again with the same model_dir. This will reload it from what ever state it was previously.

I use this for training and then reload it for testing single examples.

tf.estimator.DNNClassifier
(feature_columns=feature_columns, 
hidden_units=[10, 20, 10], 
n_classes=3, 
model_dir="/tmp/iris_model")

Answer 2

Save

The first thing you need to do is to create a tensorflow Saver object inside your session:

with tf.Session(graph=graph) as sess:
    saver = tf.train.Saver()

Then, after your training - and still inside the session -, you call the save method:

saver.save(sess, 'path/to/model_file')

You don't need to specify file extension since the save method will do it for you.

Load

To restore the model, you open a new session (without a graph, of course) and do like this:

with tf.Session() as sess:
    new_saver = tf.train.import_meta_graph('path/to/model_file.meta')
    new_saver.restore(sess, tf.train.latest_checkpoint('path/to/model_dir/'))

    # restore the tensors you want (usually, the ones you use in feed_dict and sess.run)
    graph = tf.get_default_graph()
    x = graph.get_tensor_by_name("x:0")
    output = graph.get_tensor_by_name("output:0")

    feed_dict = {x:x}
    [result] = sess.run([output], feed_dict=feed_dict)

You can also check this tutorial about saving and restoring tensorflow models. I hope it helps!