deeplearning4j/deeplearning4j

/* ******************************************************************************
 *
 *
 * 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.
 *
 *  See the NOTICE file distributed with this work for additional
 *  information regarding copyright ownership.
 * 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
 ******************************************************************************/

//
// @author raver119@gmail.com, created on 24.11.17.
// @author Yurii Shyrma (iuriish@yahoo.com)
//

#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_scatter_add)

#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/generic/helpers/ScatterHelper.h>

namespace sd {
namespace ops {

OP_IMPL(scatter_add, 3, 1, true) {
    auto input = INPUT_VARIABLE(0);
    auto indices = INPUT_VARIABLE(1);
    auto updates = INPUT_VARIABLE(2);

    auto output = OUTPUT_VARIABLE(0);

    if (!block.isInplace())
        output->assign(input);

    const bool lock = block.getBArguments()->empty() ? false : B_ARG(0);
    const bool checkIndices = block.getBArguments()->size() <= 1 ? false : B_ARG(1);

    const int inRank  = input->rankOf();
    const int indRank = indices->rankOf();
    const int updRank = updates->rankOf();
    const sd::LongType indLen = indices->lengthOf();

    REQUIRE_TRUE(inRank > 0, 0, "SCATTER_ADD OP: input should not be scalar !");

    if(inRank == 1) {
        REQUIRE_TRUE(indices->isSameShape(updates), 0, "SCATTER_ADD OP: when input array has rank = 1 then indices and updates must have the same shapes, but got %s and %s correspondingly !", ShapeUtils::shapeAsString(indices).c_str(), ShapeUtils::shapeAsString(updates).c_str());
    }
    else if (inRank == updRank && indices->isVector()) {
        std::vector<sd::LongType> updShape = updates->getShapeAsVector();
        std::vector<sd::LongType> inShape  = input->getShapeAsVector();
        std::vector<sd::LongType> expectedUpdShape = {indices->lengthOf()};
        expectedUpdShape.insert(expectedUpdShape.end(), inShape.begin()+1, inShape.end());

    }
    else {

        REQUIRE_TRUE(updRank == indRank + inRank - 1, 0, "SCATTER_ADD OP: wrong rank of updates array, expected is %i, but got %i instead !", indRank + inRank - 1 , updRank);

        std::vector<sd::LongType> updShape = updates->getShapeAsVector();
        std::vector<sd::LongType> inShape  = input->getShapeAsVector();
        std::vector<sd::LongType> expectedUpdShape = indices->getShapeAsVector();
        expectedUpdShape.insert(expectedUpdShape.end(), inShape.begin() + sd::LongType(1L), inShape.end());

    }

    if (!indices->isEmpty()) {

        if(checkIndices) {
            const sd::LongType numOfBadIndx = helpers::checkIndices(block.launchContext(), *indices, *output, 0);
            REQUIRE_TRUE(numOfBadIndx == 0, 0, "SCATTER_ADD OP: please check elements of indices-array, total number of wrong elements is %lld!", numOfBadIndx);
        }

        helpers::scatter(block.launchContext(), pairwise::Add, *indices, *updates, *output, lock);
    }

    return Status::OK;
}

DECLARE_SYN(ScatterAdd, scatter_add);

DECLARE_TYPES(scatter_add) {
    getOpDescriptor()
        ->setAllowedInputTypes(0, {ALL_INTS, ALL_FLOATS})
        ->setAllowedInputTypes(1, {ALL_INTS})
        ->setAllowedInputTypes(2, {ALL_INTS, ALL_FLOATS})
        ->setAllowedOutputTypes({ALL_INTS, ALL_FLOATS});
}

}
}

#endif