Model Persistence

MultiLayerNetwork and ComputationGraph both have save and load methods.

You can save/load a MultiLayerNetwork using:

MultiLayerNetwork net = ...
net.save(new File("...");

MultiLayerNetwork net2 = MultiLayerNetwork.load(new File("..."), true);

Similarly, you can save/load a ComputationGraph using:

ComputationGraph net = ...
net.save(new File("..."));

ComputationGraph net2 = ComputationGraph.load(new File("..."), true);

Internally, these methods use the ModelSerializer class, which handles loading and saving models. There are two methods for saving models shown in the examples through the link. The first example saves a normal multilayer network, the second one saves a computation graph.

Here is a basic example with code to save a computation graph using the ModelSerializer class, as well as an example of using ModelSerializer to save a neural net built using MultiLayer configuration.

RNG Seed

If your model uses probabilities (i.e. DropOut/DropConnect), it may make sense to save it separately, and apply it after model is restored; i.e:

This will guarantee equal results between sessions/JVMs.

ModelSerializer

Utility class suited to save/restore neural net models

writeModel

Write a model to a file

• param model the model to write

• param file the file to write to

• param saveUpdater whether to save the updater or not

writeModel

Write a model to a file

• param model the model to write

• param file the file to write to

• param saveUpdater whether to save the updater or not

writeModel

Write a model to a file path

• param model the model to write

• param path the path to write to

• param saveUpdater whether to save the updater or not

writeModel

Write a model to an output stream

• param model the model to save

• param stream the output stream to write to

• param saveUpdater whether to save the updater for the model or not

writeModel

Write a model to an output stream

• param model the model to save

• param stream the output stream to write to

• param saveUpdater whether to save the updater for the model or not

restoreMultiLayerNetwork

Load a multi layer network from a file

• param file the file to load from

• return the loaded multi layer network

• throws IOException

restoreMultiLayerNetwork

Load a multi layer network from a file

• param file the file to load from

• return the loaded multi layer network

• throws IOException

restoreMultiLayerNetwork

Load a MultiLayerNetwork from InputStream from an input stream Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.

• param is the inputstream to load from

• return the loaded multi layer network

• throws IOException

restoreMultiLayerNetwork

Restore a multi layer network from an input stream Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.

• param is the input stream to restore from

• return the loaded multi layer network

• throws IOException

restoreMultiLayerNetwork

Load a MultilayerNetwork model from a file

• param path path to the model file, to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreMultiLayerNetwork

Load a MultilayerNetwork model from a file

• param path path to the model file, to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreComputationGraph

Restore a MultiLayerNetwork and Normalizer (if present - null if not) from the InputStream. Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.

• param is Input stream to read from

• param loadUpdater Whether to load the updater from the model or not

• return Model and normalizer, if present

restoreComputationGraph

Load a computation graph from a file

• param path path to the model file, to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreComputationGraph

Load a computation graph from a InputStream

• param is the inputstream to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreComputationGraph

Load a computation graph from a InputStream

• param is the inputstream to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreComputationGraph

Load a computation graph from a file

• param file the file to get the computation graph from

• return the loaded computation graph

• throws IOException

restoreComputationGraph

Restore a ComputationGraph and Normalizer (if present - null if not) from the InputStream. Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.

• param is Input stream to read from

• param loadUpdater Whether to load the updater from the model or not

• return Model and normalizer, if present

taskByModel

• param model

• return

addNormalizerToModel

This method appends normalizer to a given persisted model.

PLEASE NOTE: File should be model file saved earlier with ModelSerializer

• param f

• param normalizer

addObjectToFile

Add an object to the (already existing) model file using Java Object Serialization. Objects can be restored using {- link #getObjectFromFile(File, String)}

• param f File to add the object to

• param key Key to store the object under

• param o Object to store using Java object serialization