org.nd4j.linalg.api.ops.impl.controlflow.compat.Switch Maven / Gradle / Ivy
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* * 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.
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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
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.controlflow.compat;
import lombok.Getter;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.Op;
import org.nd4j.linalg.api.ops.Op.Type;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
public class Switch extends BaseCompatOp {
@Getter
private SDVariable predicate;
public Switch(SameDiff sameDiff, SDVariable input, SDVariable predicate){
super(sameDiff, new SDVariable[]{input, predicate});
this.predicate = predicate;
}
public Switch(INDArray input, INDArray predicate) {
addInputArgument(input, predicate);
}
public Switch(){
}
/**
* WARNING: do not change without changing serialization methods
* See {@link org.nd4j.autodiff.samediff.serde.FlatBuffersMapper#getOpNum(String, Type)}
* and {@link org.nd4j.imports.converters.DifferentialFunctionClassHolder#customOpClassForHashAndName(long, String)}
*/
public static final String OP_NAME = "switch";
public static final int OP_NUM = 30;
@Override
public String opName() {
return OP_NAME;
}
@Override
public SDVariable[] outputVariables() {
return super.outputVariables();
}
@Override
public String tensorflowName() {
return "Switch";
}
@Override
public Type opType() {
return Type.LOGIC;
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
}
@Override
public void configureFromArguments() {
super.configureFromArguments();
}
@Override
public void setPropertiesForFunction(Map properties) {
super.setPropertiesForFunction(properties);
}
@Override
public void configureWithSameDiff(SameDiff sameDiff) {
super.configureWithSameDiff(sameDiff);
//samediff instance should already be set at this point
if(args() != null && args().length > 1)
this.predicate = arg(1);
}
@Override
public int getNumOutputs(){
return 2; //2 outputs - 2 branches
}
@Override
public List calculateOutputDataTypes(List inputDataTypes) {
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == 2, "Expected 2 input dataypes for %s, got %s", getClass(), inputDataTypes);
return Arrays.asList(inputDataTypes.get(0), inputDataTypes.get(0));
}
}