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/*******************************************************************************
 * Copyright (c) 2015-2018 Skymind, Inc.
 *
 * This program and the accompanying materials are made available under the
 * terms of the Apache License, Version 2.0 which is available at
 * https://www.apache.org/licenses/LICENSE-2.0.
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 * License for the specific language governing permissions and limitations
 * under the License.
 *
 * SPDX-License-Identifier: Apache-2.0
 ******************************************************************************/

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

import com.google.common.primitives.Ints;
import lombok.val;
import onnx.OnnxProto3;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.exception.ND4JIllegalStateException;
import org.nd4j.linalg.util.ArrayUtil;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.*;

/**
 * Transpose function
 *
 * @author Adam Gibson
 */
public class Transpose extends DynamicCustomOp {
    protected int[] permuteDims;

    public Transpose(SameDiff sameDiff, SDVariable i_v) {
        super(null, sameDiff, new SDVariable[]{i_v});
    }

    public Transpose(INDArray input, INDArray result){
        super(null, new INDArray[]{input}, result == null ? null : new INDArray[]{result}, null, (List) null);
    }

    public Transpose() {
    }

    @Override
    public void resolvePropertiesFromSameDiffBeforeExecution() {
        super.resolvePropertiesFromSameDiffBeforeExecution();
    }

    @Override
    public Map> mappingsForFunction() {
        Map> ret = new LinkedHashMap<>();
        Map map = new LinkedHashMap<>();

        val mapping = PropertyMapping.builder()
                .onnxAttrName("perm")
                .propertyNames(new String[]{"permuteDims"})
                .tfInputPosition(1)
                .build();


        map.put("permuteDims", mapping);
        ret.put(tensorflowName(), map);
        ret.put(onnxName(), map);
        return ret;
    }

    @Override
    public Map propertiesForFunction() {
        Map ret = new LinkedHashMap<>();
        ret.put("permuteDims", permuteDims);
        return ret;
    }


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

    @Override
    public String onnxName() {
        return "Transpose";
    }

    @Override
    public String tensorflowName() {
        return "Transpose";
    }


    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
        super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
        //permute dimensions are not specified as second input
        if (nodeDef.getInputCount() < 2)
            return;
        NodeDef permuteDimsNode = null;
        for (int i = 0; i < graph.getNodeCount(); i++) {
            if (graph.getNode(i).getName().equals(nodeDef.getInput(1))) {
                permuteDimsNode = graph.getNode(i);
            }

        }

        val permuteArrayOp = TFGraphMapper.getInstance().getNDArrayFromTensor("value", permuteDimsNode, graph);
        if (permuteArrayOp != null) {
            this.permuteDims = permuteArrayOp.data().asInt();
            for (int i = 0; i < permuteDims.length; i++) {
                addIArgument(permuteDims[i]);
            }
        }

        //handle once properly mapped
        if (arg().getShape() == null) {
            return;
        }

        INDArray arr = sameDiff.getArrForVarName(arg().getVarName());
        if (arr == null) {
            val arrVar = sameDiff.getVariable(arg().getVarName());
            arr = arrVar.getWeightInitScheme().create(arrVar.getShape());
            sameDiff.putArrayForVarName(arg().getVarName(), arr);
        }

        addInputArgument(arr);

        if (arr != null && permuteDims == null) {
            this.permuteDims = ArrayUtil.reverseCopy(ArrayUtil.range(0, arr.rank()));
        }

        if (permuteDims != null && permuteDims.length < arg().getShape().length)
            throw new ND4JIllegalStateException("Illegal permute found. Not all dimensions specified");


    }

    @Override
    public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map attributesForNode, OnnxProto3.GraphProto graph) {
        if (!attributesForNode.containsKey("perm")) {

        } else
            this.permuteDims = Ints.toArray(attributesForNode.get("perm").getIntsList());
    }

    @Override
    public List calculateOutputShape() {
        if (args().length > 1){
            return super.calculateOutputShape();
        }
        if (permuteDims == null && arg() != null && arg().getShape() != null) {
            this.permuteDims = ArrayUtil.reverseCopy(ArrayUtil.range(0, arg().getShape().length));
            val permutedShape = ArrayUtil.permute(arg().getShape(), permuteDims);
            return Arrays.asList(permutedShape);
        } else if (permuteDims != null && arg() != null && arg().getShape() != null) {
            val permutedShape = ArrayUtil.permute(arg().getShape(), permuteDims);
            return Arrays.asList(permutedShape);
        }

        return Collections.emptyList();
    }


    @Override
    public List doDiff(List i_v) {
        SDVariable ret = sameDiff.transpose(i_v.get(0));
        return Arrays.asList(ret);
    }

}