org.nd4j.linalg.api.ops.impl.shape.SplitV Maven / Gradle / Ivy
/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * 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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* * SPDX-License-Identifier: Apache-2.0
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*/
package org.nd4j.linalg.api.ops.impl.shape;
import lombok.val;
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.buffer.DataType;
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.*;
/**
* SplitV op
*/
public class SplitV extends DynamicCustomOp {
private int numSplit;
private int splitDim;
@Override
public String opName() {
return "split_v";
}
@Override
public String tensorflowName() {
return "SplitV";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
val splitDim = TFGraphMapper.getArrayFrom(TFGraphMapper.getNodeWithNameFromGraph(graph,nodeDef.getInput(0)),graph);
if(splitDim != null) {
this.splitDim = splitDim.getInt(0);
addIArgument(splitDim.getInt(0));
}
val numSplits = (int) attributesForNode.get("num_split").getI();
this.numSplit = numSplits;
//addIArgument(numSplits); //libnd4j op doesn't used/need it for execution
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map map = new HashMap<>();
val splitDim = PropertyMapping.builder()
.tfInputPosition(-1)
.propertyNames(new String[]{"splitDim"})
.build();
val numSplit = PropertyMapping.builder()
.tfAttrName("num_split")
.propertyNames(new String[]{"numSplit"})
.build();
map.put("numSplit",numSplit);
map.put("splitDim",splitDim);
ret.put(tensorflowName(),map);
//ret.put(onnxName(),map);
return ret;
}
@Override
public int getNumOutputs(){
return numSplit;
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//Output types are same as first input type - just numSplits of them...
List out = new ArrayList<>(numSplit);
for( int i = 0; i < numSplit; i++) {
out.add(dataTypes.get(0));
}
return out;
}
}