org.nd4j.linalg.api.ops.impl.shape.Flatten2D Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
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package org.nd4j.linalg.api.ops.impl.shape;
import lombok.NoArgsConstructor;
import lombok.NonNull;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import onnx.Onnx;
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.linalg.api.buffer.DataType;
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.*;
@Slf4j
@NoArgsConstructor
public class Flatten2D extends DynamicCustomOp {
private long flattenDimension;
public Flatten2D(SameDiff sameDiff, SDVariable i_v, long axis) {
super(null, sameDiff, new SDVariable[]{i_v});
this.flattenDimension = axis;
addIArgument(axis);
}
public Flatten2D(INDArray in, long axis) {
super(new INDArray[]{in}, null);
this.flattenDimension = axis;
addIArgument(axis);
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
}
@Override
public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map attributesForNode, Onnx.GraphProto graph) {
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map map = new HashMap<>();
val axisMapping = PropertyMapping.builder()
.onnxAttrName("axis")
.propertyNames(new String[]{"axis"})
.build();
map.put("axis", axisMapping);
ret.put(onnxName(), map);
return ret;
}
@Override
public String opName() {
return "flatten_2d";
}
@Override
public String onnxName() {
return "Flatten";
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No op name found for tensorflow!");
}
@Override
public List doDiff(List i_v) {
return Arrays.asList(new Flatten2D(sameDiff,i_v.get(0),flattenDimension).outputVariables());
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
if(!dArguments.isEmpty())
return Collections.singletonList(dArguments.get(0));
//Output type is always same as input type
return Collections.singletonList(dataTypes.get(0));
}
}