Getting started with importing Keras functional Models

Let's say you start with defining a simple MLP using Keras' functional API:

In Keras there are several ways to save a model. You can store the whole model (model definition, weights and training configuration) as HDF5 file, just the model configuration (as JSON or YAML file) or just the weights (as HDF5 file). Here's how you do each:

If you decide to save the full model, you will have access to the training configuration of the model, otherwise you don't. So if you want to further train your model in DL4J after import, keep that in mind and use model.save(...) to persist your model.

Loading your Keras model

Let's start with the recommended way, loading the full model back into DL4J (we assume it's on your class path):

In case you didn't compile your Keras model, it will not come with a training configuration. In that case you need to explicitly tell model import to ignore training configuration by setting the enforceTrainingConfig flag to false like this:

To load just the model configuration from JSON, you use KerasModelImport as follows:

If additionally you also want to load the model weights with the configuration, here's what you do:

In the latter two cases no training configuration will be read.

Getting started with importing Keras Sequential models

Let's say you start with defining a simple MLP using Keras:

from keras.models import Sequential
from keras.layers import Dense

model = Sequential()
model.add(Dense(units=64, activation='relu', input_dim=100))
model.add(Dense(units=10, activation='softmax'))
model.compile(loss='categorical_crossentropy',optimizer='sgd', metrics=['accuracy'])

In Keras there are several ways to save a model. You can store the whole model (model definition, weights and training configuration) as HDF5 file, just the model configuration (as JSON or YAML file) or just the weights (as HDF5 file). Here's how you do each:

model.save('full_model.h5')  # save everything in HDF5 format

model_json = model.to_json()  # save just the config. replace with "to_yaml" for YAML serialization
with open("model_config.json", "w") as f:
    f.write(model_json)

model.save_weights('model_weights.h5') # save just the weights.

If you decide to save the full model, you will have access to the training configuration of the model, otherwise you don't. So if you want to further train your model in DL4J after import, keep that in mind and use model.save(...) to persist your model.

Loading your Keras model

Let's start with the recommended way, loading the full model back into DL4J (we assume it's on your class path):

String fullModel = new ClassPathResource("full_model.h5").getFile().getPath();
MultiLayerNetwork model = KerasModelImport.importKerasSequentialModelAndWeights(fullModel);

In case you didn't compile your Keras model, it will not come with a training configuration. In that case you need to explicitly tell model import to ignore training configuration by setting the enforceTrainingConfig flag to false like this:

MultiLayerNetwork model = KerasModelImport.importKerasSequentialModelAndWeights(fullModel, false);

To load just the model configuration from JSON, you use KerasModelImport as follows:

String modelJson = new ClassPathResource("model_config.json").getFile().getPath();
MultiLayerNetworkConfiguration modelConfig = KerasModelImport.importKerasSequentialConfiguration(modelJson)

If additionally you also want to load the model weights with the configuration, here's what you do:

String modelWeights = new ClassPathResource("model_weights.h5").getFile().getPath();
MultiLayerNetwork network = KerasModelImport.importKerasSequentialModelAndWeights(modelJson, modelWeights)

In the latter two cases no training configuration will be read.

Many more advanced models will contain custom layers, i.e. layers that aren't included in Keras.

You can import those models too, but you will have to provide an implementation of that layer yourself, as the exported model file only provides us with a name for it.

Usually, you will have found out about needing to implement a custom layer, when you saw an exception like the following:

org.deeplearning4j.nn.modelimport.keras.exceptions.UnsupportedKerasConfigurationException:
No SameDiff Lambda layer found for Lambda layer lambda_123. You can register a SameDiff Lambda layer using 
KerasLayer.registerLambdaLayer(lambdaLayerName, sameDiffLambdaLayer);

or

org.deeplearning4j.nn.modelimport.keras.exceptions.UnsupportedKerasConfigurationException: 
Unsupported keras layer type LayerName.

Implementing a custom layer for Keras import

There are two ways of implementing a custom layer for Keras import. Which one is the right approach for you, depends on the type of layer you need to implement.

1. SameDiffLambdaLayer Use this approach if your layer doesn't have any weights and defines just a computation. It is most useful when you have to define a custom layer because you are using a lambda in your model definition. This is the approach you should be using when you've gotten the exception about no lambda layer being found.

2. KerasLayer Use this approach if your layer needs its own weights. It is most useful when you have to define some complex layer that is more than just a simple computation. This is the approach you should be using when you've gotten the exception about an unsupported layer type.

SameDiffLambdaLayer

Using a SameDiffLambdaLayer is pretty easy. You create a new class that extends it, and override the defineLayer and getOutputType methods.

public class TimesThreeLambda extends SameDiffLambdaLayer {
    @Override
    public SDVariable defineLayer(SameDiff sd, SDVariable x) { 
        return x.mul(3); 
    }

    @Override
    public InputType getOutputType(int layerIndex, InputType inputType) {
        return inputType; 
    }
}

This simple lambda layer just multiplies its input by 3.

After defining your layer, you have to register it to make it available on import.

KerasLayer.registerLambdaLayer("lambda_2", new TimesThreeLambda());

The correct name for your lambda layer will depend on the model you are importing. As you, most likely, were made aware of needing to implement the lambda layer by an exception, this exception should have given you the proper name already.

KerasLayer

Implementing a full layer with weights is more complex than defining a lambda layer. You will have to create a new class that extends KerasLayer and that reads the configuration of that layer and defines it appropriately.

For examples on how this was done, take a look at KerasLRN and KerasPoolHelper which are custom layers that were needed to be able to import GoogLeNet.

After you've defined your layer, you will have to register it to make it available on import:

KerasLayer.registerCustomLayer("PoolHelper", KerasPoolHelper.class);

Again, the appropriate name will we apparent from the exception that has notified you about needing to implement the custom layer in the first place.

KerasPReLU

Imports PReLU layer from Keras

KerasPReLU

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Invalid Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Invalid Keras config

getPReLULayer

Get DL4J ActivationLayer.

• return ActivationLayer

setWeights

Set weights for layer.

• param weights Dense layer weights

KerasThresholdedReLU

Imports ThresholdedReLU layer from Keras

KerasThresholdedReLU

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Invalid Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Invalid Keras config

getActivationLayer

Get DL4J ActivationLayer.

• return ActivationLayer

KerasLeakyReLU

Imports LeakyReLU layer from Keras

KerasLeakyReLU

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Invalid Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Invalid Keras config

getActivationLayer

Get DL4J ActivationLayer.

• return ActivationLayer

KerasGaussianNoise

Keras wrapper for DL4J dropout layer with GaussianNoise.

KerasGaussianNoise

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getGaussianNoiseLayer

Get DL4J DropoutLayer with Gaussian dropout.

• return DropoutLayer

KerasAlphaDropout

Keras wrapper for DL4J dropout layer with AlphaDropout.

KerasAlphaDropout

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getAlphaDropoutLayer

Get DL4J DropoutLayer with Alpha dropout.

• return DropoutLayer

KerasGaussianDropout

Keras wrapper for DL4J dropout layer with GaussianDropout.

KerasGaussianDropout

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Invalid Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getGaussianDropoutLayer

Get DL4J DropoutLayer with Gaussian dropout.

• return DropoutLayer

Deeplearning4j: Keras model import

provides routines for importing neural network models originally configured and trained using , a popular Python deep learning library.

Once you have imported your model into DL4J, our full production stack is at your disposal. We support import of all Keras model types, most layers and practically all utility functionality. Please check for a complete list of supported Keras features.

Note to users: tf.keras models are also supported. Please check for an overview of what to expect for tf.keras as well as other features. Our documentation needs to be updated to reflect the changes between keras and tf.keras. For now, users should aware of this as you read the below docs. Migrating from keras to tf.keras mainly involves changing the imports in your python script. The equivalent kind of changes needed to happen for the model import in deeplearning4j. Those changes happened in beta7.

Getting started: Import a Keras model in 60 seconds

To import a Keras model, you need to create and such a model first. Here's a simple example that you can use. The model is a simple MLP that takes mini-batches of vectors of length 100, has two Dense layers and predicts a total of 10 categories. After defining the model, we serialize it in HDF5 format.

If you put this model file (simple_mlp.h5) into the base of your resource folder of your project, you can load the Keras model as DL4J MultiLayerNetwork as follows

You can now use your imported model for inference (here with dummy data for simplicity)

Here's how you do training in DL4J for your imported model:

Project setup

To use Keras model import in your existing project, all you need to do is add the following dependency to your pom.xml.

Backend

DL4J Keras model import is backend agnostic. No matter which backend you choose (TensorFlow, Theano, CNTK), your models can be imported into DL4J.

Popular models and applications

• Deep convolutional and Wasserstein GANs

• UNET

• ResNet50

• SqueezeNet

• MobileNet

• Inception

• Xception

Troubleshooting and support

An IncompatibleKerasConfigurationException message indicates that you are attempting to import a Keras model configuration that is not currently supported in Deeplearning4j (either because model import does not cover it, or DL4J does not implement the layer, or feature).

Once you have imported your model, we recommend our own ModelSerializer class for further saving and reloading of your model.

Why Keras model import?

Keras is a popular and user-friendly deep learning library written in Python. The intuitive API of Keras makes defining and running your deep learning models in Python easy. Keras allows you to choose which lower-level library it runs on, but provides a unified API for each such backend. Currently, Keras supports Tensorflow, CNTK and Theano backends.

There is often a gap between the production system of a company and the experimental setup of its data scientists. Keras model import allows data scientists to write their models in Python, but still seamlessly integrates with the production stack.

Keras model import is targeted at users mainly familiar with writing their models in Python with Keras. With model import you can bring your Python models to production by allowing users to import their models into the DL4J ecosystem for either further training or evaluation purposes.

KerasModelImport

Reads stored Keras configurations and weights from one of two archives: either as

• a single HDF5 file storing model and training JSON configurations and weights

• separate text file storing model JSON configuration and HDF5 file storing weights.

importKerasModelAndWeights

Load Keras (Functional API) Model saved using model.save_model(…).

• param modelHdf5Stream InputStream containing HDF5 archive storing Keras Model

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• see ComputationGraph

importKerasModelAndWeights

Load Keras (Functional API) Model saved using model.save_model(…).

• param modelHdf5Stream InputStream containing HDF5 archive storing Keras Model

• return ComputationGraph

• see ComputationGraph

importKerasSequentialModelAndWeights

Load Keras Sequential model saved using model.save_model(…).

• param modelHdf5Stream InputStream containing HDF5 archive storing Keras Sequential model

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• see ComputationGraph

importKerasSequentialModelAndWeights

Load Keras Sequential model saved using model.save_model(…).

• param modelHdf5Stream InputStream containing HDF5 archive storing Keras Sequential model

• return ComputationGraph

• see ComputationGraph

importKerasModelAndWeights

Load Keras (Functional API) Model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Model

• param inputShape optional input shape for models that come without such (e.g. notop = false models)

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• throws IOException IO exception

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

• see ComputationGraph

importKerasModelAndWeights

Load Keras (Functional API) Model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Model

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• throws IOException IO exception

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

• see ComputationGraph

importKerasModelAndWeights

Load Keras (Functional API) Model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Model

• return ComputationGraph

• throws IOException IO exception

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

• see ComputationGraph

importKerasSequentialModelAndWeights

Load Keras Sequential model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Sequential model

• param inputShape optional input shape for models that come without such (e.g. notop = false models)

• param enforceTrainingConfig whether to enforce training configuration options

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasSequentialModelAndWeights

Load Keras Sequential model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Sequential model

• param enforceTrainingConfig whether to enforce training configuration options

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasSequentialModelAndWeights

Load Keras Sequential model saved using model.save_model(…).

• param modelHdf5Filename path to HDF5 archive storing Keras Sequential model

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasModelAndWeights

Load Keras (Functional API) Model for which the configuration and weights were saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Model configuration

• param weightsHdf5Filename path to HDF5 archive storing Keras model weights

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• throws IOException IO exception

• see ComputationGraph

importKerasModelAndWeights

Load Keras (Functional API) Model for which the configuration and weights were saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Model configuration

• param weightsHdf5Filename path to HDF5 archive storing Keras model weights

• return ComputationGraph

• throws IOException IO exception

• see ComputationGraph

importKerasSequentialModelAndWeights

Load Keras Sequential model for which the configuration and weights were saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Sequential model configuration

• param weightsHdf5Filename path to HDF5 archive storing Keras model weights

• param enforceTrainingConfig whether to enforce training configuration options

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasSequentialModelAndWeights

Load Keras Sequential model for which the configuration and weights were saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Sequential model configuration

• param weightsHdf5Filename path to HDF5 archive storing Keras model weights

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasModelConfiguration

Load Keras (Functional API) Model for which the configuration was saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Model configuration

• param enforceTrainingConfig whether to enforce training configuration options

• return ComputationGraph

• throws IOException IO exception

• see ComputationGraph

importKerasModelConfiguration

Load Keras (Functional API) Model for which the configuration was saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Model configuration

• return ComputationGraph

• throws IOException IO exception

• see ComputationGraph

importKerasSequentialConfiguration

Load Keras Sequential model for which the configuration was saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Sequential model configuration

• param enforceTrainingConfig whether to enforce training configuration options

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

importKerasSequentialConfiguration

Load Keras Sequential model for which the configuration was saved separately using calls to model.to_json() and model.save_weights(…).

• param modelJsonFilename path to JSON file storing Keras Sequential model configuration

• return MultiLayerNetwork

• throws IOException IO exception

• see MultiLayerNetwork

KerasPermute

Imports Permute layer from Keras

KerasPermute

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

isInputPreProcessor

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getInputPreprocessor

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras config

• see InputPreProcessor

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasFlatten

Imports a Keras Flatten layer as a DL4J {Cnn,Rnn}ToFeedForwardInputPreProcessor.

KerasFlatten

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

isInputPreProcessor

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getInputPreprocessor

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras config

• see org.deeplearning4j.nn.conf.InputPreProcessor

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasReshape

Imports Reshape layer from Keras

KerasReshape

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

isInputPreProcessor

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getInputPreprocessor

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras config

• see org.deeplearning4j.nn.conf.InputPreProcessor

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasMerge

Imports a Keras Merge layer as a DL4J Merge (graph) vertex.

TODO: handle axes arguments that alter merge behavior (requires changes to DL4J?)

KerasMerge

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

KerasDropout

Imports a Dropout layer from Keras.

KerasDropout

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getDropoutLayer

Get DL4J DropoutLayer.

• return DropoutLayer

KerasMasking

Imports Keras masking layers.

KerasMasking

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getMaskingLayer

Get DL4J MaskZeroLayer.

• return MaskZeroLayer

KerasSpatialDropout

Keras wrapper for DL4J dropout layer with SpatialDropout, works 1D-3D.

KerasSpatialDropout

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSpatialDropoutLayer

Get DL4J DropoutLayer with spatial dropout.

• return DropoutLayer

KerasLambda

Wraps a DL4J SameDiffLambda into a KerasLayer

KerasLambda

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSameDiffLayer

Get DL4J SameDiffLayer.

• return SameDiffLayer

KerasActivation

Imports an Activation layer from Keras.

KerasActivation

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getActivationLayer

Get DL4J ActivationLayer.

• return ActivationLayer

KerasDense

Imports a Dense layer from Keras.

KerasDense

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getDenseLayer

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

Returns number of trainable parameters in layer.

• return number of trainable parameters (2)

setWeights

Set weights for layer.

• param weights Dense layer weights

KerasRepeatVector

Imports a Keras RepeatVector layer

KerasRepeatVector

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getRepeatVectorLayer

Get DL4J RepeatVector.

• return RepeatVector

KerasEmbedding

Imports an Embedding layer from Keras.

KerasEmbedding

Pass through constructor for unit tests

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getEmbeddingLayer

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

Returns number of trainable parameters in layer.

• return number of trainable parameters (1)

setWeights

Set weights for layer.

• param weights Embedding layer weights

KerasLocallyConnected1D

Imports a 1D locally connected layer from Keras.

KerasLocallyConnected1D

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getLocallyConnected1DLayer

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

setWeights

Set weights for 1D locally connected layer.

• param weights Map from parameter name to INDArray.

KerasLocallyConnected2D

Imports a 2D locally connected layer from Keras.

KerasLocallyConnected2D

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getLocallyConnected2DLayer

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

setWeights

Set weights for 2D locally connected layer.

• param weights Map from parameter name to INDArray.

We support all Keras activation functions, namely:

• softmax

• elu

• selu

• softplus

• softsign

• relu

• tanh

• sigmoid

• hard_sigmoid

• linear

The mapping of Keras to DL4J activation functions is defined in KerasActivationUtils

KerasConvolution2D

[source]

Imports a 2D Convolution layer from Keras.

KerasConvolution2D

public KerasConvolution2D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getConvolution2DLayer

public ConvolutionLayer getConvolution2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasCropping2D

[source]

Imports a Keras Cropping 2D layer.

KerasCropping2D

public KerasCropping2D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getCropping2DLayer

public Cropping2D getCropping2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasUpsampling3D

[source]

Keras Upsampling3D layer support

KerasUpsampling3D

public KerasUpsampling3D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration exception

getUpsampling3DLayer

public Upsampling3D getUpsampling3DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Invalid Keras configuration exception

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasConvolution1D

[source]

Imports a 1D Convolution layer from Keras.

KerasConvolution1D

public KerasConvolution1D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException

getConvolution1DLayer

public Convolution1DLayer getConvolution1DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException

• throws UnsupportedKerasConfigurationException

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException

getInputPreprocessor

public InputPreProcessor getInputPreprocessor(InputType... inputType) throws InvalidKerasConfigurationException

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• see org.deeplearning4j.nn.conf.InputPreProcessor

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Set weights for layer.

• param weights Map from parameter name to INDArray.

KerasUpsampling1D

[source]

Keras Upsampling1D layer support

KerasUpsampling1D

public KerasUpsampling1D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration exception

getUpsampling1DLayer

public Upsampling1D getUpsampling1DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Invalid Keras configuration exception

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasAtrousConvolution2D

[source]

Keras 1D atrous / dilated convolution layer. Note that in keras 2 this layer has been removed and dilations are now available through the “dilated” argument in regular Conv1D layers

author: Max Pumperla

KerasAtrousConvolution2D

public KerasAtrousConvolution2D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getAtrousConvolution2D

public ConvolutionLayer getAtrousConvolution2D()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasAtrousConvolution1D

[source]

Keras 1D atrous / dilated convolution layer. Note that in keras 2 this layer has been removed and dilations are now available through the “dilated” argument in regular Conv1D layers

author: Max Pumperla

KerasAtrousConvolution1D

public KerasAtrousConvolution1D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getAtrousConvolution1D

public Convolution1DLayer getAtrousConvolution1D()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasCropping3D

[source]

Imports a Keras Cropping 3D layer.

KerasCropping3D

public KerasCropping3D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getCropping3DLayer

public Cropping3D getCropping3DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasZeroPadding2D

[source]

Imports a Keras ZeroPadding 2D layer.

KerasZeroPadding2D

public KerasZeroPadding2D(Map<String, Object> layerConfig)
                    throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getZeroPadding2DLayer

public ZeroPaddingLayer getZeroPadding2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasConvolution3D

[source]

Imports a 3D Convolution layer from Keras.

KerasConvolution3D

public KerasConvolution3D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getConvolution3DLayer

public ConvolutionLayer getConvolution3DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasDeconvolution2D

[source]

Imports a 2D Deconvolution layer from Keras.

KerasDeconvolution2D

public KerasDeconvolution2D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getDeconvolution2DLayer

public Deconvolution2D getDeconvolution2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasZeroPadding3D

[source]

Imports a Keras ZeroPadding 3D layer.

KerasZeroPadding3D

public KerasZeroPadding3D(Map<String, Object> layerConfig)
                    throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getZeroPadding3DLayer

public ZeroPadding3DLayer getZeroPadding3DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasConvolutionUtils

[source]

Utility functionality for Keras convolution layers.

getConvolutionModeFromConfig

public static ConvolutionMode getConvolutionModeFromConfig(Map<String, Object> layerConfig,
                                                               KerasLayerConfiguration conf)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Get (convolution) stride from Keras layer configuration.

• param layerConfig dictionary containing Keras layer configuration

• return Strides array from Keras configuration

• throws InvalidKerasConfigurationException Invalid Keras config

KerasZeroPadding1D

[source]

Imports a Keras ZeroPadding 1D layer.

KerasZeroPadding1D

public KerasZeroPadding1D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getZeroPadding1DLayer

public ZeroPadding1DLayer getZeroPadding1DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasCropping1D

[source]

Imports a Keras Cropping 1D layer.

KerasCropping1D

public KerasCropping1D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getCropping1DLayer

public Cropping1D getCropping1DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasSpaceToDepth

[source]

Constructor from parsed Keras layer configuration dictionary.

KerasSpaceToDepth

public KerasSpaceToDepth(Map<String, Object> layerConfig, boolean enforceTrainingConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration exception

getSpaceToDepthLayer

public SpaceToDepthLayer getSpaceToDepthLayer()

Get DL4J SpaceToDepth layer.

• return SpaceToDepth layer

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasUpsampling2D

[source]

Keras Upsampling2D layer support

KerasUpsampling2D

public KerasUpsampling2D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration exception

getUpsampling2DLayer

public Upsampling2D getUpsampling2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• throws UnsupportedKerasConfigurationException Invalid Keras configuration exception

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasSeparableConvolution2D

[source]

Keras separable convolution 2D layer support

KerasSeparableConvolution2D

public KerasSeparableConvolution2D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras configuration

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration

getSeparableConvolution2DLayer

public SeparableConvolution2D getSeparableConvolution2DLayer()

Get DL4J SeparableConvolution2D.

• return SeparableConvolution2D

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasDepthwiseConvolution2D

[source]

Keras depth-wise convolution 2D layer support

KerasDepthwiseConvolution2D

public KerasDepthwiseConvolution2D(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras configuration

• throws UnsupportedKerasConfigurationException Unsupported Keras configuration

getDepthwiseConvolution2DLayer

public DepthwiseConvolution2D getDepthwiseConvolution2DLayer()

Get DL4J DepthwiseConvolution2D.

• return DepthwiseConvolution2D

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasBatchNormalization

[source]

Imports a BatchNormalization layer from Keras.

KerasBatchNormalization

public KerasBatchNormalization(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getBatchNormalizationLayer

public BatchNormalization getBatchNormalizationLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

public int getNumParams()

Returns number of trainable parameters in layer.

• return number of trainable parameters (4)

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Set weights for layer.

• param weights Map from parameter name to INDArray.

KerasSimpleRnn

[source]

Imports a Keras SimpleRNN layer as a DL4J SimpleRnn layer.

KerasSimpleRnn

public KerasSimpleRnn(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSimpleRnnLayer

public Layer getSimpleRnnLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

public int getNumParams()

Returns number of trainable parameters in layer.

• return number of trainable parameters (12)

getInputPreprocessor

public InputPreProcessor getInputPreprocessor(InputType... inputType) throws InvalidKerasConfigurationException

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• see org.deeplearning4j.nn.conf.InputPreProcessor

getUnroll

public boolean getUnroll()

Get whether SimpleRnn layer should be unrolled (for truncated BPTT).

• return whether RNN should be unrolled (boolean)

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Set weights for layer.

• param weights Simple RNN weights

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

KerasRnnUtils

[source]

Utility functions for Keras RNN layers

getUnrollRecurrentLayer

public static boolean getUnrollRecurrentLayer(KerasLayerConfiguration conf, Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException

Get unroll parameter to decide whether to unroll RNN with BPTT or not.

• param conf KerasLayerConfiguration

• param layerConfig dictionary containing Keras layer properties

• return boolean unroll parameter

• throws InvalidKerasConfigurationException Invalid Keras configuration

getRecurrentDropout

public static double getRecurrentDropout(KerasLayerConfiguration conf, Map<String, Object> layerConfig)
            throws UnsupportedKerasConfigurationException, InvalidKerasConfigurationException

Get recurrent weight dropout from Keras layer configuration. Non-zero dropout rates are currently not supported.

• param conf KerasLayerConfiguration

• param layerConfig dictionary containing Keras layer properties

• return recurrent dropout rate

• throws InvalidKerasConfigurationException Invalid Keras configuration

KerasLSTM

[source]

Imports a Keras LSTM layer as a DL4J LSTM layer.

KerasLSTM

public KerasLSTM(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getLSTMLayer

public Layer getLSTMLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

public int getNumParams()

Returns number of trainable parameters in layer.

• return number of trainable parameters (12)

getInputPreprocessor

public InputPreProcessor getInputPreprocessor(InputType... inputType) throws InvalidKerasConfigurationException

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• see org.deeplearning4j.nn.conf.InputPreProcessor

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Set weights for layer.

• param weights LSTM layer weights

getUnroll

public boolean getUnroll()

Get whether LSTM layer should be unrolled (for truncated BPTT).

• return whether to unroll the LSTM

getGateActivationFromConfig

public IActivation getGateActivationFromConfig(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Get LSTM gate activation function from Keras layer configuration.

• param layerConfig dictionary containing Keras layer configuration

• return LSTM inner activation function

• throws InvalidKerasConfigurationException Invalid Keras config

getForgetBiasInitFromConfig

public double getForgetBiasInitFromConfig(Map<String, Object> layerConfig, boolean train)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Get LSTM forget gate bias initialization from Keras layer configuration.

• param layerConfig dictionary containing Keras layer configuration

• return LSTM forget gate bias init

• throws InvalidKerasConfigurationException Unsupported Keras config

Keras Model Import: Supported Features

While not every concept in DL4J has an equivalent in Keras and vice versa, many of the key concepts can be matched. Importing keras models into DL4J is done in our deeplearning4j-modelimport module. Below is a comprehensive list of currently supported features.

Note that we also support importing tf.keras models as well. The format only changed a little bit from keras to tf.keras. We handle this transition from beta7 and above.

• Layers

• Losses

• Activations

• Initializers

• Regularizers

• Constraints

• Metrics

• Optimizers

Layers

Mapping keras to DL4J layers is done in the layers sub-module of model import. The structure of this project loosely reflects the structure of Keras.

Core Layers

• ✅ Dense

• ✅ Activation

• ✅ Dropout

• ✅ Flatten

• ✅ Reshape

• ✅ Merge

• ✅ Permute

• ✅ RepeatVector

• ✅ Lambda

• ❌ ActivityRegularization

• ✅ Masking

• ✅ SpatialDropout1D

• ✅ SpatialDropout2D

• ✅ SpatialDropout3D

Convolutional Layers

• ✅ Conv1D

• ✅ Conv2D

• ✅ Conv3D

• ✅ AtrousConvolution1D

• ✅ AtrousConvolution2D

• ❌ SeparableConv1D

• ✅ SeparableConv2D

• ✅ Conv2DTranspose

• ❌ Conv3DTranspose

• ✅ Cropping1D

• ✅ Cropping2D

• ✅ Cropping3D

• ✅ UpSampling1D

• ✅ UpSampling2D

• ✅ UpSampling3D

• ✅ ZeroPadding1D

• ✅ ZeroPadding2D

• ✅ ZeroPadding3D

Pooling Layers

• ✅ MaxPooling1D

• ✅ MaxPooling2D

• ✅ MaxPooling3D

• ✅ AveragePooling1D

• ✅ AveragePooling2D

• ✅ AveragePooling3D

• ✅ GlobalMaxPooling1D

• ✅ GlobalMaxPooling2D

• ✅ GlobalMaxPooling3D

• ✅ GlobalAveragePooling1D

• ✅ GlobalAveragePooling2D

• ✅ GlobalAveragePooling3D

Locally-connected Layers

• ✅ LocallyConnected1D

• ✅ LocallyConnected2D

Recurrent Layers

• ✅ SimpleRNN

• ❌ GRU

• ✅ LSTM

• ❌ ConvLSTM2D

Embedding Layers

• ✅ Embedding

Merge Layers

• ✅ Add / add

• ✅ Multiply / multiply

• ✅ Subtract / subtract

• ✅ Average / average

• ✅ Maximum / maximum

• ✅ Concatenate / concatenate

• ❌ Dot / dot

Advanced Activation Layers

• ✅ LeakyReLU

• ✅ PReLU

• ✅ ELU

• ✅ ThresholdedReLU

Normalization Layers

• ✅ BatchNormalization

Noise Layers

• ✅ GaussianNoise

• ✅ GaussianDropout

• ✅ AlphaDropout

Layer Wrappers

• ❌ TimeDistributed

• ✅ Bidirectional

Losses

• ✅ mean_squared_error

• ✅ mean_absolute_error

• ✅ mean_absolute_percentage_error

• ✅ mean_squared_logarithmic_error

• ✅ squared_hinge

• ✅ hinge

• ✅ categorical_hinge

• ❌ logcosh

• ✅ categorical_crossentropy

• ✅ sparse_categorical_crossentropy

• ✅ binary_crossentropy

• ✅ kullback_leibler_divergence

• ✅ poisson

• ✅ cosine_proximity

Activations

• ✅ softmax

• ✅ elu

• ✅ selu

• ✅ softplus

• ✅ softsign

• ✅ relu

• ✅ tanh

• ✅ sigmoid

• ✅ hard_sigmoid

• ✅ linear

Initializers

• ✅ Zeros

• ✅ Ones

• ✅ Constant

• ✅ RandomNormal

• ✅ RandomUniform

• ✅ TruncatedNormal

• ✅ VarianceScaling

• ✅ Orthogonal

• ✅ Identity

• ✅ lecun_uniform

• ✅ lecun_normal

• ✅ glorot_normal

• ✅ glorot_uniform

• ✅ he_normal

• ✅ he_uniform

Regularizers

• ✅ l1

• ✅ l2

• ✅ l1_l2

Constraints

• ✅ max_norm

• ✅ non_neg

• ✅ unit_norm

• ✅ min_max_norm

Optimizers

• ✅ SGD

• ✅ RMSprop

• ✅ Adagrad

• ✅ Adadelta

• ✅ Adam

• ✅ Adamax

• ✅ Nadam

• ❌ TFOptimizer

KerasBidirectional

[source]

Builds a DL4J Bidirectional layer from a Keras Bidirectional layer wrapper

KerasBidirectional

public KerasBidirectional(Integer kerasVersion) throws UnsupportedKerasConfigurationException

Pass-through constructor from KerasLayer

• param kerasVersion major keras version

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getUnderlyingRecurrentLayer

public Layer getUnderlyingRecurrentLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getBidirectionalLayer

public Bidirectional getBidirectionalLayer()

Get DL4J Bidirectional layer.

• return Bidirectional Layer

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

getNumParams

public int getNumParams()

Returns number of trainable parameters in layer.

• return number of trainable parameters

getInputPreprocessor

public InputPreProcessor getInputPreprocessor(InputType... inputType) throws InvalidKerasConfigurationException

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras configuration exception

• see org.deeplearning4j.nn.conf.InputPreProcessor

setWeights

public void setWeights(Map<String, INDArray> weights) throws InvalidKerasConfigurationException

Set weights for Bidirectional layer.

• param weights Map of weights

KerasPooling1D

[source]

Imports a Keras 1D Pooling layer as a DL4J Subsampling layer.

KerasPooling1D

public KerasPooling1D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSubsampling1DLayer

public Subsampling1DLayer getSubsampling1DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasPoolingUtils

[source]

Utility functionality for Keras pooling layers.

mapPoolingType

public static PoolingType mapPoolingType(String className, KerasLayerConfiguration conf)
            throws UnsupportedKerasConfigurationException

Map Keras pooling layers to DL4J pooling types.

• param className name of the Keras pooling class

• return DL4J pooling type

• throws UnsupportedKerasConfigurationException Unsupported Keras config

KerasPooling3D

[source]

Imports a Keras 3D Pooling layer as a DL4J Subsampling3D layer.

KerasPooling3D

public KerasPooling3D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSubsampling3DLayer

public Subsampling3DLayer getSubsampling3DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasGlobalPooling

[source]

Imports a Keras Pooling layer as a DL4J Subsampling layer.

KerasGlobalPooling

public KerasGlobalPooling(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getGlobalPoolingLayer

public GlobalPoolingLayer getGlobalPoolingLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getInputPreprocessor

public InputPreProcessor getInputPreprocessor(InputType... inputType) throws InvalidKerasConfigurationException

Gets appropriate DL4J InputPreProcessor for given InputTypes.

• param inputType Array of InputTypes

• return DL4J InputPreProcessor

• throws InvalidKerasConfigurationException Invalid Keras config

• see org.deeplearning4j.nn.conf.InputPreProcessor

getOutputType

public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException

Get layer output type.

• param inputType Array of InputTypes

• return output type as InputType

• throws InvalidKerasConfigurationException Invalid Keras config

KerasPooling2D

[source]

Imports a Keras 2D Pooling layer as a DL4J Subsampling layer.

KerasPooling2D

public KerasPooling2D(Map<String, Object> layerConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration.

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config

getSubsampling2DLayer

public SubsamplingLayer getSubsampling2DLayer()

Constructor from parsed Keras layer configuration dictionary.

• param layerConfig dictionary containing Keras layer configuration

• param enforceTrainingConfig whether to enforce training-related configuration options

• throws InvalidKerasConfigurationException Invalid Keras config

• throws UnsupportedKerasConfigurationException Unsupported Keras config