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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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 *  *  See the NOTICE file distributed with this work for additional
 *  *  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
 *  * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 *  * License for the specific language governing permissions and limitations
 *  * under the License.
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package org.nd4j.linalg.api.ops.impl.layers.convolution;

import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.enums.DataFormat;
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 DepthToSpace extends DynamicCustomOp {
    private DataFormat dataFormat = DataFormat.NHWC;
    private int blockSize;

    public DepthToSpace() {
    }

    public DepthToSpace(SameDiff sameDiff, SDVariable args, int blockSize, DataFormat dataFormat) {
        this(sameDiff, new SDVariable[]{args}, blockSize, dataFormat);
    }

    public DepthToSpace(SameDiff sameDiff, SDVariable[] args, int blockSize, DataFormat dataFormat) {
        super(null, sameDiff, args, false);
        this.blockSize = blockSize;
        this.dataFormat = dataFormat;
        boolean isNHWC = dataFormat.equals(DataFormat.NHWC);
        addIArgument(blockSize, isNHWC ? 1 : 0);
    }

    public DepthToSpace(INDArray in, INDArray out, int blockSize, DataFormat dataFormat) {
        super(null, in, out, null, null);
        this.blockSize = blockSize;
        this.dataFormat = dataFormat;
        boolean isNHWC = dataFormat.equals(DataFormat.NHWC);
        addIArgument(blockSize, isNHWC ? 1 : 0);
    }

    public DepthToSpace(INDArray in, int blockSize, DataFormat dataFormat) {
        this(in, null, blockSize, dataFormat);
    }

    @Override
    public List doDiff(List i_v) {
        // Gradient to DepthToSpace is just SpaceToDepth of same block size and data format.
        SDVariable gradient = i_v.get(0);
        SDVariable ret = new SpaceToDepth(sameDiff, new SDVariable[]{gradient}, blockSize, dataFormat).outputVariable();
        return Arrays.asList(ret);
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
        TFGraphMapper.initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
        boolean isNHWC = dataFormat.equals(DataFormat.NHWC);
        addIArgument(blockSize, isNHWC ? 1 : 0);
    }


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

        val blockSize = PropertyMapping.builder()
                .tfAttrName("block_size")
                .propertyNames(new String[]{"blockSize"})
                .build();
        attrs.put("blockSize", blockSize);

        val dataFormatMapping = PropertyMapping.builder()
                .tfAttrName("data_format")
                .propertyNames(new String[]{"dataFormat"})
                .build();
        attrs.put("dataFormat", dataFormatMapping);

        ret.put(tensorflowName(), attrs);
        return ret;
    }

    @Override
    public void setPropertiesForFunction(Map properties) {
        if(properties.containsKey("block_size")) {
            Long blockSize = (Long) properties.get("block_size");
            this.blockSize = blockSize.intValue();
        }

        if(properties.containsKey("isNHWC")) {
            Long isNHWC = (Long) properties.get("isNHWC");
            this.dataFormat = isNHWC > 0 ? DataFormat.NHWC : DataFormat.NCHW;
        }

    }

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

    @Override
    public String[] tensorflowNames() {
        return new String[]{"DepthToSpace"};
    }

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

    @Override
    public List calculateOutputDataTypes(List dataTypes){
        return Collections.singletonList(dataTypes.get(0));
    }
}