Examples with UnsupportedKerasConfigurationException org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException used on opensource projects

Example 1 with UnsupportedKerasConfigurationException

use of org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException in project deeplearning4j by deeplearning4j.

the class KerasLstm method getRecurrentWeightInitFromConfig.

/**
     * Get LSTM recurrent weight initialization from Keras layer configuration.
     *
     * @param layerConfig       dictionary containing Keras layer configuration
     * @return                  epsilon
     * @throws InvalidKerasConfigurationException
     */
public static WeightInit getRecurrentWeightInitFromConfig(Map<String, Object> layerConfig, boolean train) throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
    Map<String, Object> innerConfig = getInnerLayerConfigFromConfig(layerConfig);
    if (!innerConfig.containsKey(LAYER_FIELD_INNER_INIT))
        throw new InvalidKerasConfigurationException("Keras LSTM layer config missing " + LAYER_FIELD_INNER_INIT + " field");
    String kerasInit = (String) innerConfig.get(LAYER_FIELD_INNER_INIT);
    WeightInit init;
    try {
        init = mapWeightInitialization(kerasInit);
    } catch (UnsupportedKerasConfigurationException e) {
        if (train)
            throw e;
        else {
            init = WeightInit.XAVIER;
            log.warn("Unknown weight initializer " + kerasInit + " (Using XAVIER instead).");
        }
    }
    return init;
}

Example 2 with UnsupportedKerasConfigurationException

use of org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException in project deeplearning4j by deeplearning4j.

the class KerasLstm method getForgetBiasInitFromConfig.

/**
     * Get LSTM forget gate bias initialization from Keras layer configuration.
     *
     * @param layerConfig       dictionary containing Keras layer configuration
     * @return                  epsilon
     * @throws InvalidKerasConfigurationException
     */
public static double getForgetBiasInitFromConfig(Map<String, Object> layerConfig, boolean train) throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
    Map<String, Object> innerConfig = getInnerLayerConfigFromConfig(layerConfig);
    if (!innerConfig.containsKey(LAYER_FIELD_FORGET_BIAS_INIT))
        throw new InvalidKerasConfigurationException("Keras LSTM layer config missing " + LAYER_FIELD_FORGET_BIAS_INIT + " field");
    String kerasForgetBiasInit = (String) innerConfig.get(LAYER_FIELD_FORGET_BIAS_INIT);
    double init = 0;
    switch(kerasForgetBiasInit) {
        case LSTM_FORGET_BIAS_INIT_ZERO:
            init = 0.0;
            break;
        case LSTM_FORGET_BIAS_INIT_ONE:
            init = 1.0;
            break;
        default:
            if (train)
                throw new UnsupportedKerasConfigurationException("Unsupported LSTM forget gate bias initialization: " + kerasForgetBiasInit);
            else {
                init = 1.0;
                log.warn("Unsupported LSTM forget gate bias initialization: " + kerasForgetBiasInit + " (using 1 instead)");
            }
            break;
    }
    return init;
}

Example 3 with UnsupportedKerasConfigurationException

use of org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException in project deeplearning4j by deeplearning4j.

the class KerasBatchNormalization method getBatchNormMode.

/**
     * Get BatchNormalization "mode" from Keras layer configuration. Most modes currently unsupported.
     *
     * @param layerConfig          dictionary containing Keras layer configuration
     * @return
     * @throws InvalidKerasConfigurationException
     */
protected int getBatchNormMode(Map<String, Object> layerConfig, boolean enforceTrainingConfig) throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
    Map<String, Object> innerConfig = getInnerLayerConfigFromConfig(layerConfig);
    if (!innerConfig.containsKey(LAYER_FIELD_MODE))
        throw new InvalidKerasConfigurationException("Keras BatchNorm layer config missing " + LAYER_FIELD_MODE + " field");
    int batchNormMode = (int) innerConfig.get(LAYER_FIELD_MODE);
    switch(batchNormMode) {
        case LAYER_BATCHNORM_MODE_1:
            throw new UnsupportedKerasConfigurationException("Keras BatchNormalization mode " + LAYER_BATCHNORM_MODE_1 + " (sample-wise) not supported");
        case LAYER_BATCHNORM_MODE_2:
            throw new UnsupportedKerasConfigurationException("Keras BatchNormalization (per-batch statistics during testing) " + LAYER_BATCHNORM_MODE_2 + " not supported");
    }
    return batchNormMode;
}

Example 4 with UnsupportedKerasConfigurationException

use of org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException in project deeplearning4j by deeplearning4j.

the class KerasMerge method getMergeMode.

public ElementWiseVertex.Op getMergeMode(Map<String, Object> layerConfig) throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
    Map<String, Object> innerConfig = getInnerLayerConfigFromConfig(layerConfig);
    if (!innerConfig.containsKey(LAYER_FIELD_MODE))
        throw new InvalidKerasConfigurationException("Keras Merge layer config missing " + LAYER_FIELD_MODE + " field");
    ElementWiseVertex.Op op = null;
    String mergeMode = (String) innerConfig.get(LAYER_FIELD_MODE);
    switch(mergeMode) {
        case LAYER_MERGE_MODE_SUM:
            op = ElementWiseVertex.Op.Add;
            break;
        case LAYER_MERGE_MODE_MUL:
            op = ElementWiseVertex.Op.Product;
            break;
        case LAYER_MERGE_MODE_CONCAT:
            // leave null
            break;
        case LAYER_MERGE_MODE_AVE:
        case LAYER_MERGE_MODE_COS:
        case LAYER_MERGE_MODE_DOT:
        case LAYER_MERGE_MODE_MAX:
        default:
            throw new UnsupportedKerasConfigurationException("Keras Merge layer mode " + mergeMode + " not supported");
    }
    return op;
}

Example 5 with UnsupportedKerasConfigurationException

use of org.deeplearning4j.nn.modelimport.keras.UnsupportedKerasConfigurationException in project deeplearning4j by deeplearning4j.

the class KerasZeroPadding method getPaddingFromConfig.

/**
     * Get zero padding from Keras layer configuration.
     *
     * @param layerConfig       dictionary containing Keras layer configuration
     * @return
     * @throws InvalidKerasConfigurationException
     */
public int[] getPaddingFromConfig(Map<String, Object> layerConfig) throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
    Map<String, Object> innerConfig = getInnerLayerConfigFromConfig(layerConfig);
    if (!innerConfig.containsKey(LAYER_FIELD_PADDING))
        throw new InvalidKerasConfigurationException("Field " + LAYER_FIELD_PADDING + " not found in Keras ZeroPadding layer");
    List<Integer> paddingList = (List<Integer>) innerConfig.get(LAYER_FIELD_PADDING);
    switch(this.className) {
        case LAYER_CLASS_NAME_ZERO_PADDING_2D:
            if (paddingList.size() == 2) {
                paddingList.add(paddingList.get(1));
                paddingList.add(1, paddingList.get(0));
            }
            if (paddingList.size() != 4)
                throw new InvalidKerasConfigurationException("Found Keras ZeroPadding2D layer with invalid " + paddingList.size() + "D padding.");
            break;
        case LAYER_CLASS_NAME_ZERO_PADDING_1D:
            throw new UnsupportedKerasConfigurationException("Keras ZeroPadding1D layer not supported");
        default:
            throw new UnsupportedKerasConfigurationException("Keras " + this.className + " padding layer not supported");
    }
    int[] padding = new int[paddingList.size()];
    for (int i = 0; i < paddingList.size(); i++) padding[i] = paddingList.get(i);
    return padding;
}