org.nd4j.linalg.api.ops.impl.shape.Stack Maven / Gradle / Ivy
/*******************************************************************************
* 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 onnx.OnnxProto3;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.ndarray.INDArray;
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.HashMap;
import java.util.List;
import java.util.Map;
/**
* Stack operation. Stacks n input tensors along provided axis.
*
* @author [email protected]
*/
public class Stack extends DynamicCustomOp {
protected int axis;
public Stack() {
}
public Stack(INDArray[] inputs, INDArray output, int axis){
super(null, inputs, output == null ? null : new INDArray[]{output}, null, (List)null);
this.axis = axis;
addArgs();
}
public Stack(SameDiff sameDiff, SDVariable[] values, int axis) {
super(null, sameDiff, values, false);
this.axis = axis;
addArgs();
}
public void addArgs() {
addIArgument(axis);
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx opName found for " + opName());
}
@Override
public String tensorflowName() {
return "stack";
}
@Override
public String toString() {
return opName();
}
@Override
public String[] tensorflowNames() {
return new String[]{"Pack", "Stack"};
}
@Override
public String opName() {
return "stack";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
TFGraphMapper.getInstance().initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
addArgs();
}
@Override
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map attributesForNode, OnnxProto3.GraphProto graph) {
throw new UnsupportedOperationException("No analog found for onnx for " + opName());
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map map = new HashMap<>();
val axisMapping = PropertyMapping.builder()
.onnxAttrName("axis")
.tfAttrName("axis")
.propertyNames(new String[]{"axis"})
.build();
map.put("axis", axisMapping);
for (val name : tensorflowNames())
ret.put(name, map);
return ret;
}
@Override
public List doDiff(List f1) {
return Arrays.asList(f().unstack(f1.get(0), axis, args().length));
}
}