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/*******************************************************************************
* 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;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataBuffer;
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 org.nd4j.linalg.primitives.Pair;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
/**
* Index based reduction algo
*
* @author Adam Gibson
*/
@Slf4j
@Data
public abstract class BaseIndexAccumulation extends BaseOp implements IndexAccumulation {
protected boolean keepDims = false;
public BaseIndexAccumulation(SameDiff sameDiff,
SDVariable i_v,
boolean keepDims,
int[] dimensions) {
super(sameDiff,null);
if (i_v != null) {
this.dimensions = dimensions;
f().validateDifferentialFunctionsameDiff(i_v);
sameDiff.addArgsFor(new SDVariable[]{i_v},this);
if(Shape.isPlaceholderShape(i_v.getShape())) {
sameDiff.addPropertyToResolve(this,i_v.getVarName());
}
this.xVertexId = i_v.getVarName();
} else {
throw new IllegalArgumentException("Input not null variable.");
}
this.keepDims = keepDims;
defineDimensions(dimensions);
}
public BaseIndexAccumulation(SameDiff sameDiff,
SDVariable i_v,
SDVariable i_v2,
boolean keepDims,
int[] dimensions) {
super(sameDiff,null);
if (i_v != null) {
this.dimensions = dimensions;
f().validateDifferentialFunctionsameDiff(i_v);
f().validateDifferentialFunctionsameDiff(i_v2);
this.xVertexId = i_v.getVarName();
this.yVertexId = i_v2.getVarName();
sameDiff.addArgsFor(new SDVariable[]{i_v,i_v2},this);
if(Shape.isPlaceholderShape(i_v.getShape())) {
sameDiff.addPropertyToResolve(this,i_v.getVarName());
}
if(Shape.isPlaceholderShape(i_v2.getShape())) {
sameDiff.addPropertyToResolve(this,i_v2.getVarName());
}
} else {
throw new IllegalArgumentException("Input not null variable.");
}
this.keepDims = keepDims;
defineDimensions(dimensions);
}
public BaseIndexAccumulation() {}
public BaseIndexAccumulation(INDArray x, int[] dimensions) {
this(x, null, dimensions);
}
public BaseIndexAccumulation(INDArray x, INDArray z, int[] dimensions) {
super(x, z);
defineDimensions(dimensions);
}
@Override
public List calculateOutputShape() {
if(x == null)
return Collections.emptyList();
long[] reducedShape = Shape.getReducedShape(x.shape(), dimensions, keepDims);
return Collections.singletonList(LongShapeDescriptor.fromShape(reducedShape, DataType.LONG));
}
@Override
public Type opType() {
return Type.INDEXREDUCE;
}
@Override
public boolean validateDataTypes() {
if (z() != null)
Preconditions.checkArgument(z().dataType() == DataType.LONG, "IndexReduce operations require LONG output: " +
"got result array of type %s for op %s", z.dataType(), getClass());
return true;
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//All index accumulation ops: always long output type
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got input %s", getClass(), dataTypes);
return Collections.singletonList(DataType.LONG);
}
}