cavis/libnd4j/include/ops/declarable/generic/transforms/tear.cpp

/* ******************************************************************************
 *
 *
 * 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
 ******************************************************************************/

//
// Created by raver119 on 12.10.2017.
//

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

#include <ops/declarable/CustomOperations.h>
#include <helpers/TAD.h>
#include <helpers/ConstantTadHelper.h>

namespace sd {
    namespace ops {
        CUSTOM_OP_IMPL(tear, 1, -1, false, 0, -1) {
            auto input = INPUT_VARIABLE(0);

            REQUIRE_TRUE(!block.getIArguments()->empty(), 0, "At least 1 dimension should be specified for Tear");

            std::vector<int> dims(*block.getIArguments());

            for (auto &v: dims)
                REQUIRE_TRUE(v >= 0 && v < input->rankOf(), 0, "Tear dimensions should be non-negative values, and lower then input rank. Got %i instead", v);

            auto tads = input->allTensorsAlongDimension(dims);
            for (Nd4jLong e = 0; e < tads.size(); e++) {
                auto outE = OUTPUT_VARIABLE(e);
                outE->assign(tads.at(e));

                // just for debugging purposes
                this->storeResult(block, e, *outE);
            }

            return Status::OK();
        }

        DECLARE_SHAPE_FN(tear) {
            auto inShape = inputShape->at(0);

            std::vector<int> dims(*block.getIArguments());

            if (dims.size() > 1)
                std::sort(dims.begin(), dims.end());

            auto tadPack = sd::ConstantTadHelper::getInstance().tadForDimensions(inShape, dims);
            auto numTads = tadPack.numberOfTads();

            auto result = SHAPELIST();
            for (Nd4jLong e = 0; e < numTads; e++) {
                auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(block.dataType(), shape::order(inShape), shape::rank(tadPack.primaryShapeInfo()), shape::shapeOf(tadPack.primaryShapeInfo()));
                result->push_back(newShape);
            }

            return result;
        }

        DECLARE_TYPES(tear) {
            getOpDescriptor()
                    ->setAllowedInputTypes(sd::DataType::ANY)
                    ->setSameMode(true);
        }
    }
}

#endif