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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.impl.accum.bp;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.List;
/**
* @author Alex Black
*/
public abstract class BaseReductionBp extends DynamicCustomOp {
protected boolean keepDims;
protected int[] dimensions;
/**
*
* @param origInput Pre-reduced input
* @param gradAtOutput Gradient at the output
* @param keepDims If true: reduction dimensions were kept
* @param dimensions Dimensions to reduce. May be null
*/
public BaseReductionBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions) {
super(null, sameDiff, new SDVariable[]{origInput, gradAtOutput}, false);
this.keepDims = keepDims;
this.dimensions = dimensions;
addArgs();
}
/**
*
* @param origInput1 Pre-reduced input 1
* @param origInput2 Pre-reduced input 2
* @param gradAtOutput Gradient at the output
* @param keepDims If true: reduction dimensions were kept
* @param dimensions Dimensions to reduce. May be null
*/
public BaseReductionBp(SameDiff sameDiff, SDVariable origInput1, SDVariable origInput2, SDVariable gradAtOutput, boolean keepDims, int... dimensions) {
super(null, sameDiff, new SDVariable[]{origInput1, origInput2, gradAtOutput}, false);
this.keepDims = keepDims;
this.dimensions = dimensions;
addArgs();
}
/**
*
* @param origInput Pre-reduced input
* @param gradAtOutput Gradient at the output
* @param output Output array - i.e., gradient at the input to the reduction function
* @param keepDims If true: reduction dimensions were kept
* @param dimensions Dimensions to reduce. May be null
*/
public BaseReductionBp(INDArray origInput, INDArray gradAtOutput, INDArray output, boolean keepDims, int... dimensions){
super(null, new INDArray[]{origInput, gradAtOutput}, (output == null ? null : new INDArray[]{output}));
this.keepDims = keepDims;
this.dimensions = dimensions;
addArgs();
}
/**
*
* @param origInput1 Pre-reduced input1
* @param origInput2 Pre-reduced input2
* @param gradAtOutput Gradient at the output
* @param output Output array - i.e., gradient at the input to the reduction function
* @param keepDims If true: reduction dimensions were kept
* @param dimensions Dimensions to reduce. May be null
*/
public BaseReductionBp(INDArray origInput1, INDArray origInput2, INDArray gradAtOutput, INDArray output, boolean keepDims, int... dimensions){
super(null, new INDArray[]{origInput1, origInput2, gradAtOutput}, (output == null ? null : new INDArray[]{output}));
this.keepDims = keepDims;
this.dimensions = dimensions;
addArgs();
}
public BaseReductionBp(){}
protected void addArgs(){
addTArgument(keepDims ? 1 : 0);
if(dimensions != null && dimensions.length > 0){
if(dimensions.length != 1 || dimensions[0] != Integer.MAX_VALUE ){
//Integer.MAX_VALUE means "full array" but here no dimension args == full array
addIArgument(dimensions);
}
}
}
public abstract String opName();
}
