org.nd4j.linalg.api.ops.compat.CompatSparseToDense Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.compat;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
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.OpContext;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import java.util.Arrays;
import java.util.List;
public class CompatSparseToDense extends DynamicCustomOp {
public CompatSparseToDense() {
//
}
public CompatSparseToDense(INDArray indices, INDArray shape, INDArray values) {
Preconditions.checkArgument(shape.isZ() && indices.isZ(), "Shape & indices arrays must have one integer data types");
inputArguments.add(indices);
inputArguments.add(shape);
inputArguments.add(values);
}
public CompatSparseToDense(SameDiff sd, SDVariable indices, SDVariable shape, SDVariable values) {
super(sd,new SDVariable[]{indices,shape,values});
}
public CompatSparseToDense(SameDiff sd, SDVariable indices, SDVariable shape, SDVariable values, SDVariable defaultValue) {
super(sd,new SDVariable[]{indices,shape,values,defaultValue});
}
public CompatSparseToDense(INDArray indices, INDArray shape, INDArray values, INDArray defaultValue) {
super(new INDArray[]{indices,shape,values,defaultValue},null);
}
@Override
public List calculateOutputShape(OpContext oc) {
return Arrays.asList(LongShapeDescriptor.fromShape(oc.getInputArrays().get(1).toLongVector(),oc.getInputArrays().get(0).dataType()));
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
if(!dArguments.isEmpty())
return Arrays.asList(dataTypes.get(0));
return Arrays.asList(dataTypes.get(0));
}
@Override
public String opName() {
return "compat_sparse_to_dense";
}
}