org.nd4j.linalg.api.ops.impl.transforms.custom.Unique 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
* 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.transforms.custom;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
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.Arrays;
import java.util.List;
import java.util.Map;
public class Unique extends DynamicCustomOp {
public static final DataType DEFAULT_IDX_DTYPE = DataType.INT;
private DataType idxDataType;
public Unique(){ }
public Unique(SameDiff sd, SDVariable in){
super(sd, new SDVariable[]{in}, false);
}
@Override
public String opName(){
return "unique";
}
@Override
public String[] tensorflowNames() {
return new String[]{"Unique","UniqueV2"};
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not implemented yet");
}
@Override
public int numOutputArguments(){
return 2;
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
idxDataType = TFGraphMapper.convertType(nodeDef.getAttrOrThrow("out_idx").getType());
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got %s", getClass(), dataTypes);
return Arrays.asList(dataTypes.get(0), (idxDataType == null ? DEFAULT_IDX_DTYPE : idxDataType));
}
}