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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 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.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.factory.Nd4j;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.*;
/**
* Created by susaneraly on 3/14/18.
*/
public class OneHot extends DynamicCustomOp {
public static final DataType DEFAULT_DTYPE = DataType.FLOAT;
private int depth;
private int jaxis = -1;
private double on;
private double off;
private DataType outputType;
public OneHot() {
}
public OneHot(SameDiff sameDiff, SDVariable indices, int depth) {
this(sameDiff, indices, depth, -1, 1, 0, DEFAULT_DTYPE);
}
public OneHot(SameDiff sameDiff, SDVariable indices, int depth, int axis, double on, double off, DataType dataType) {
super(null, sameDiff, new SDVariable[] {indices}, false);
this.depth = depth;
this.jaxis = axis;
this.on = on;
this.off = off;
addArgs();
this.outputType = dataType;
}
public OneHot(INDArray indices, INDArray output, int depth) {
this(indices, output, depth, -1, 1, 0);
}
public OneHot(INDArray indices, INDArray output, int depth, int axis, double on, double off) {
super(null, indices, output, null, null);
this.depth = depth;
this.jaxis = axis;
this.on = on;
this.off = off;
addArgs();
}
protected void addArgs() {
addIArgument(jaxis);
addIArgument(depth);
addTArgument(on);
addTArgument(off);
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
TFGraphMapper.getInstance().initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
addArgs();
if(attributesForNode.containsKey("T")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("T").getType());
}
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map attrs = new LinkedHashMap<>();
val depth = PropertyMapping.builder()
.propertyNames(new String[]{"depth"})
.tfInputPosition(1)
.build();
attrs.put("depth", depth);
val on = PropertyMapping.builder()
.propertyNames(new String[]{"on"})
.tfInputPosition(2)
.build();
attrs.put("on", on);
val off = PropertyMapping.builder()
.propertyNames(new String[]{"off"})
.tfInputPosition(3)
.build();
attrs.put("off", off);
val axis = PropertyMapping.builder()
.propertyNames(new String[] {"jaxis"})
.tfAttrName("axis")
.build();
attrs.put("jaxis",axis);
ret.put(tensorflowName(),attrs);
return ret;
}
@Override
public String tensorflowName() {
return "OneHot";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx name found for " + opName());
}
@Override
public String opName() {
return "onehot";
}
@Override
public List doDiff(List i_v) {
return Collections.singletonList(sameDiff.zerosLike(arg()));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes.size() >= 1 && dataTypes.size() <= 4, "Expected list with 1 to 4 datatypes for %s, got %s", getClass(), dataTypes);
if(outputType != null){
return Collections.singletonList(outputType);
} else {
return Collections.singletonList(DEFAULT_DTYPE);
}
}
}