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package org.nd4j.linalg.api.ops;
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.shape.LongShapeDescriptor;
import org.nd4j.linalg.api.shape.Shape;
import org.nd4j.linalg.factory.Nd4j;
import java.util.Collections;
import java.util.List;
public abstract class BaseReduceSameOp extends BaseReduceOp implements ReduceSameOp {
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions) {
super(sameDiff, i_v, i_v2, dimensions);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, boolean keepDims) {
super(sameDiff, i_v, keepDims);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims) {
super(sameDiff, i_v, dimensions, keepDims);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2) {
super(sameDiff, i_v, i_v2);
}
protected BaseReduceSameOp(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims) {
super(sameDiff, input, dimensions, keepDims);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims) {
super(sameDiff, i_v, i_v2, dimensions, keepDims);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v) {
super(sameDiff, i_v);
}
protected BaseReduceSameOp(SameDiff sameDiff, SDVariable input, int... dimensions) {
super(sameDiff, input, dimensions);
}
public BaseReduceSameOp(INDArray x, INDArray z, boolean keepDims, int[] dimensions) {
super(x, null, z, keepDims, dimensions);
}
public BaseReduceSameOp(INDArray x, INDArray y, INDArray z, int... dimensions) {
super(x, y, z, dimensions);
}
public BaseReduceSameOp(SameDiff sameDiff) {
super(sameDiff);
}
public BaseReduceSameOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions) {
super(sameDiff, i_v, i_v2, dimensions);
}
public BaseReduceSameOp(INDArray x, int... dimensions) {
super(x, dimensions);
}
public BaseReduceSameOp(INDArray x, boolean keepDims, int... dimensions) {
super(x, keepDims, dimensions);
}
public BaseReduceSameOp(INDArray x, INDArray y, int... dimensions) {
super(x, y, dimensions);
}
protected BaseReduceSameOp() {
super();
}
public BaseReduceSameOp(INDArray x, INDArray y, INDArray z, boolean keepDims, int[] dimensions) {
super(x, y, z, keepDims, dimensions);
}
@Override
public Type opType() {
return Type.REDUCE_SAME;
}
@Override
public Type getOpType() {
return opType();
}
@Override
public DataType resultType() {
return this.x().dataType();
}
@Override
public DataType resultType(OpContext oc){
return oc.getInputArray(0).dataType();
}
@Override
public boolean validateDataTypes(OpContext oc) {
INDArray x = oc != null ? oc.getInputArray(0) : x();
INDArray y = oc != null ? oc.getInputArray(1) : y();
INDArray z = oc != null ? oc.getOutputArray(0) : z();
if (z != null)
Preconditions.checkArgument(z.dataType() == x.dataType(), "Op.Z must be the same as Op.X type. Op.X.datatype=%s, " +
"Op.Z.datatype=%s", x.dataType(), z.dataType());
return true;
}
@Override
public INDArray dimensions() {
if(dimensionz == null && dimensions != null) {
this.dimensionz = Nd4j.create(Nd4j.createBuffer(dimensions));
} else if(dimensionz == null && y != null) {
this.dimensionz = y;
}
return dimensionz;
}
@Override
public List calculateOutputShape() {
return calculateOutputShape(null);
}
@Override
public List calculateOutputShape(OpContext oc) {
INDArray x = oc != null ? oc.getInputArray(0) : x();
if(x == null)
return Collections.emptyList();
//Calculate reduction shape. Note that reduction on scalar - returns a scalar
long[] reducedShape = x.rank() == 0 ? x.shape() : Shape.getReducedShape(x.shape(),dimensions, isKeepDims());
DataType rt = oc != null ? resultType(oc) : resultType();
return Collections.singletonList(LongShapeDescriptor.fromShape(reducedShape, rt));
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
//Output type: same as input type for BaseReduceSameOp
//Note TF uses 2 inputs - i.e., axis arg is a variable or constant
Preconditions.checkState(dataTypes != null && (dataTypes.size() == 1 || dataTypes.size() == 2),
"Expected 1 or 2 input datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.size() == 1 || dataTypes.get(1).isIntType(), "When executing reductions" +
" with 2 inputs, second input (axis) must be an integer datatype for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}