org.nd4j.linalg.api.ops.impl.shape.MergeMax Maven / Gradle / Ivy

Show more of this group Show more artifacts with this name
Show all versions of nd4j-api Show documentation
There is a newer version: 1.0.0-M2.1
/*******************************************************************************
 * 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.shape;

import lombok.extern.slf4j.Slf4j;
import lombok.val;
import onnx.Onnx;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.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.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Map;

@Slf4j
public class MergeMax extends DynamicCustomOp {

    public MergeMax(SameDiff sameDiff, SDVariable... inputs) {
        super(null, sameDiff, inputs);
    }

    public MergeMax(INDArray... inputs){
        super(inputs, null);
    }

    public MergeMax(){ }

    @Override
    public String opName() {
        return "mergemax";
    }
/*
    @Override
    public List calculateOutputShape() {
        List ret = new ArrayList<>(1);
        ret.add(arg().getShapeDescriptor());
        return ret;
    }
*/

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
        // no-op
    }

    @Override
    public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map attributesForNode, Onnx.GraphProto graph) {
        super.initFromOnnx(node, initWith, attributesForNode, graph);
    }

    @Override
    public List doDiff(List i_v) {
        SDVariable gradient = sameDiff.setupFunction(i_v.get(0));
        List ret = new ArrayList<>();
        SDVariable out = outputVariable();
        for (int i = 0; i < args().length; i++){
            SDVariable isMax = out.eq(arg(i)).castTo(arg(i).dataType());
            ret.add(isMax.mul(gradient));
        }
        return ret;
    }

    @Override
    public List calculateOutputDataTypes(List dataTypes){
        DataType first = dataTypes.get(0);
        for( int i=1; i