Creating custom layer in java Deeplearning4J

I have some problems importing my custom layer into my Java project. I read the documentation (Custom Layers - Deeplearning4j) but without succes. I’ve seen the two examples but it isn’t clear for me how to exactly implement my method in Java, like what should I implement etc?

This is the python code:

class lstm_bottleneck(tf.keras.layers.Layer):
    def __init__(self, lstm_units, time_steps, **kwargs):
        self.lstm_units = lstm_units
        self.time_steps = time_steps
        self.lstm_layer = Bidirectional(LSTM(lstm_units, return_sequences=False))
        self.repeat_layer = RepeatVector(time_steps)
        super(lstm_bottleneck, self).__init__(**kwargs)

    def call(self, inputs):
        # just call the two initialized layers
        return self.repeat_layer(self.lstm_layer(inputs))

    def compute_mask(self, inputs, mask=None):
        # return the input_mask directly
        return mask

    def get_config(self):
        thisDict = {
            "lstm_layer": self.lstm_layer.get_config(),
            "repeat_layer": self.repeat_layer.get_config()
        return thisDict

And this is my Java code. Ofcourse it isn’t working because i’m just trying to get the examples given in the documentation… (lstm_units and time_steps are fixed numbers so i guess i shouldn’t implement that in the get_config() method).

public class lstm_bottleneck extends KerasLayer {

    private int lstm_units = 45;
    private int time_steps = 322;

    public lstm_bottleneck(Map<String, Object> layerconfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
        this(layerconfig, true);

    public lstm_bottleneck(Map<String, Object> layerconfig, boolean enforceTrainingConfig)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException{
        super(layerconfig, enforceTrainingConfig);

        Map<String, Object> lrnParams = KerasLayerUtils.getInnerLayerConfigFromConfig(layerconfig, conf);



Anyone who can help? Thanks in advance!!

@DataPlanningEngineer did you respond to my comment on github earlier? I actually replied to you. Happy to continue the discussion here if you’d like.