org.nd4j.linalg.api.ops.impl.shape.Slice Maven / Gradle / Ivy
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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
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* under the License.
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* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.nd4j.linalg.api.ops.impl.shape;
import lombok.NonNull;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
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.nd4j.linalg.exception.ND4JIllegalStateException;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.*;
/**
* Slice function
*
* @author Adam Gibson
*/
@Slf4j
public class Slice extends DynamicCustomOp {
private int[] begin;
private int[] size;
public Slice() {}
public Slice(SameDiff sameDiff, @NonNull SDVariable input, @NonNull int[] begin, @NonNull int[] size){
super(null, sameDiff, new SDVariable[]{input});
this.begin = begin;
this.size = size;
addIArgument(begin);
addIArgument(size);
}
public Slice(SameDiff sameDiff, @NonNull SDVariable input, @NonNull SDVariable begin, @NonNull SDVariable end){
super(null, sameDiff, new SDVariable[]{input, begin, end});
}
@Override
public String opName() {
return "slice";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Slice";
}
@Override
public List doDiff(List grad) {
if(args().length == 1) {
return Collections.singletonList(f().sliceBp(arg(), grad.get(0), begin, size));
} else {
//Dynamic begin/size
return Collections.singletonList(f().sliceBp(arg(0), grad.get(0), arg(1), arg(2)));
}
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null & (dataTypes.size() == 1 || dataTypes.size() == 3),
"Expected list with 1 or 3 datatypes for %s, got %s", getClass(), dataTypes);
//Output type is same as input type. 3 inputs for import case
return Collections.singletonList(dataTypes.get(0));
}
}