org.nd4j.linalg.api.ops.impl.shape.ReductionShape Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * information regarding copyright ownership.
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package org.nd4j.linalg.api.ops.impl.shape;
import lombok.NonNull;
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.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.Op;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class ReductionShape extends DynamicCustomOp {
private boolean keepDims;
public ReductionShape(){ }
public ReductionShape(@NonNull SameDiff sameDiff, @NonNull SDVariable shape, @NonNull SDVariable axis, boolean keepDims){
super(sameDiff, new SDVariable[]{shape, axis});
this.keepDims = keepDims;
addBArgument(keepDims);
}
@Override
public String opName() {
return "evaluate_reduction_shape";
}
@Override
public Op.Type opType() {
return Op.Type.CUSTOM;
}
@Override
public List doDiff(List i_v) {
return Arrays.asList(sameDiff.zerosLike(arg(0)), sameDiff.zerosLike(arg(1)));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes.size() == 2, "Expected list with exactly 2 datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0).isIntType(), "Input 0 (shape) must be integer datatype, is %s", dataTypes.get(0));
Preconditions.checkState(dataTypes.get(0).isIntType(), "Input 1 (axis) must be an integer datatype, is %s", dataTypes.get(1));
return Collections.singletonList(dataTypes.get(0));
}
}