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 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
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 *  *  information regarding copyright ownership.
 *  * Unless required by applicable law or agreed to in writing, software
 *  * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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 *  * License for the specific language governing permissions and limitations
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package org.deeplearning4j.nn.conf.layers.samediff;

import org.deeplearning4j.nn.conf.inputs.InputType;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.Map;

public abstract class SameDiffLambdaLayer extends SameDiffLayer {

    /**
     * The defineLayer method is used to define the forward pass for the layer
     *
     * @param sameDiff   SameDiff instance to use to define the vertex
     * @param layerInput Layer input variable
     * @return The output variable (corresponding to the output activations for the layer)
     */
    public abstract SDVariable defineLayer(SameDiff sameDiff, SDVariable layerInput);

    @Override
    public SDVariable defineLayer(SameDiff sameDiff, SDVariable layerInput, Map<String, SDVariable> paramTable, SDVariable mask) {
        return defineLayer(sameDiff, layerInput);
    }

    @Override
    public InputType getOutputType(int layerIndex, InputType inputType) {
        //TODO let's try to infer output shape from input shape, using SameDiff + DefineLayer
        throw new UnsupportedOperationException(
                        "Override SameDiffLamdaLayer.getOutputType to use OutputType functionality");
    }

    @Override
    public void defineParameters(SDLayerParams params) {
        //No op: lambda layer doesn't have parameters
    }

    @Override
    public void initializeParameters(Map<String, INDArray> params) {
        //No op: lambda layer doesn't have parameters
    }
}
