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/*
* ******************************************************************************
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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.
* *
* * 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.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
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.api.ops.impl.shape.bp.TileBp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class Tile extends DynamicCustomOp {
private int[] jaxis;
private boolean is_static_reps = false;
public Tile(SameDiff sameDiff, SDVariable i_v, int[] axis) {
super(null,sameDiff, new SDVariable[]{i_v}, false);
this.jaxis = axis;
addArguments();
}
public Tile(SameDiff sameDiff, SDVariable i_v, SDVariable axis) {
super(null,sameDiff, new SDVariable[]{i_v, axis}, false);
this.jaxis = null;
}
public Tile(INDArray[] inputs, INDArray[] outputs, int[] axis, boolean is_static_reps) {
super(null, inputs, outputs);
this.jaxis = axis;
this.is_static_reps = is_static_reps;
addArguments();
}
public Tile(INDArray[] inputs, INDArray[] outputs, int[] axis) {
this(inputs,outputs,axis,false);
}
public Tile(INDArray x, INDArray repeat){
super(null, new INDArray[] {x, repeat}, null);
this.jaxis = null;
}
public Tile(INDArray inputs, int... axis){
super(null, new INDArray[] {inputs}, null);
this.jaxis = axis;
this.is_static_reps = true;
addArguments();
}
public Tile() {}
private void addArguments() {
this.is_static_reps = true;
addIArgument(jaxis);
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map map = new HashMap<>();
val axisMapping = PropertyMapping.builder()
.onnxAttrName("axis")
.tfInputPosition(-1)
.propertyNames(new String[]{"axis"})
.build();
map.put("axis",axisMapping);
ret.put(tensorflowName(),map);
ret.put(onnxName(),map);
return ret;
}
@Override
public String opName() {
return "tile";
}
@Override
public String onnxName() {
return "Tile";
}
@Override
public String tensorflowName() {
return "Tile";
}
@Override
public List doDiff(List i_v) {
if(jaxis != null){
return new TileBp(sameDiff, arg(), i_v.get(0), jaxis).outputs();
}else{
return new TileBp(sameDiff, arg(0), arg(1), i_v.get(0)).outputs();
}
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//2nd isput is dynamic repeat
Preconditions.checkState(dataTypes != null && (dataTypes.size() == 1 || (jaxis == null && dataTypes.size() == 2)),
"Expected 1 or 2 input datatypes for %s, got %s", getClass(), dataTypes);
//Output type is same as input type
return Collections.singletonList(dataTypes.get(0));
}
}