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package org.nd4j.linalg.api.ops.impl.shape;

import onnx.Onnx;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.*;

public class ParallelStack extends DynamicCustomOp {

    public ParallelStack() {
    }

    public ParallelStack(SameDiff sameDiff, SDVariable[] values) {
        super(null, sameDiff, values, false);
    }

    public ParallelStack(INDArray[] inputs){
        super(inputs, null);
    }

    @Override
    public String opName() {
        return "parallel_stack";
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
        TFGraphMapper.initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
    }

    @Override
    public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map attributesForNode, Onnx.GraphProto graph) {
        throw new UnsupportedOperationException("No analog found for onnx for " + opName());
    }


    @Override
    public Map> mappingsForFunction() {
        Map> ret = new HashMap<>();
        Map map = new HashMap<>();
        ret.put(tensorflowName(), map);
        return ret;
    }

    @Override
    public List calculateOutputDataTypes(List dataTypes){
        DataType first = dataTypes.get(0);
        for( int i=1; i




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