Model Persistence
Saving and loading of neural networks.
MultiLayerNetwork and ComputationGraph both have save and load methods.
You can save/load a MultiLayerNetwork using:
Similarly, you can save/load a ComputationGraph using:
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 multi layer 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
throws IOException
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
param dataNormalization the normalizer to save (optional)
throws IOException
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
throws IOException
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
throws IOException
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
param dataNormalization the normalizer ot save (may be null)
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 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
see #restoreMultiLayerNetworkAndNormalizer(InputStream, boolean)
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
see #restoreMultiLayerNetworkAndNormalizer(InputStream, boolean)
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
throws IOException If an error occurs when reading from the stream
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
throws IOException If an error occurs when reading from the stream
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
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