/* ******************************************************************************
 *
 *
 * 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 AbdelRauf (rauf@konduit.ai)
//
// CPU implementation of summary stat reductions (variance, standardDeviation)
//

#include <helpers/ConstantTadHelper.h>
#include <legacy/NativeOpExecutioner.h>
#include <ops/declarable/helpers/reductions.h>
#include <system/op_enums.h>

namespace sd {
namespace ops {
namespace helpers {

//////////////////////////////////////////////////////////////////////////
void variance(NDArray& input, NDArray& output, const std::vector<LongType>& dimensions, bool biasCorrected) {
    // Prepares (syncs) buffer of which NDArrays will be used as read, write
    NDArray::prepareSpecialUse({&output}, {&input});

    if (output.isScalar()) {
        NativeOpExecutioner::execSummaryStatsScalar(
            LaunchContext::defaultContext(), variance::SummaryStatsVariance,
            input.buffer(), input.shapeInfo(), input.specialBuffer(), input.specialShapeInfo(),
            nullptr,
            output.buffer(), output.shapeInfo(), output.specialBuffer(), output.specialShapeInfo(),
            biasCorrected);
    } else {
        auto tadPack = ConstantTadHelper::getInstance().tadForDimensions(
            input.shapeInfo(), const_cast<sd::LongType*>(dimensions.data()), dimensions.size());

        NativeOpExecutioner::execSummaryStats(
            LaunchContext::defaultContext(), variance::SummaryStatsVariance,
            input.buffer(), input.shapeInfo(), input.specialBuffer(), input.specialShapeInfo(),
            nullptr,
            output.buffer(), output.shapeInfo(), output.specialBuffer(), output.specialShapeInfo(),
            const_cast<LongType*>(dimensions.data()), dimensions.size(),
            tadPack->primaryShapeInfo(), tadPack->primaryOffsets(),
            biasCorrected);
    }

    // Inform that we are done with those buffers
    NDArray::registerSpecialUse({&output}, {&input});
}

//////////////////////////////////////////////////////////////////////////
void standardDeviation(NDArray& input, NDArray& output, const std::vector<LongType>& dimensions, bool biasCorrected) {
    // Prepares (syncs) buffer of which NDArrays will be used as read, write
    NDArray::prepareSpecialUse({&output}, {&input});

    if (output.isScalar()) {
        NativeOpExecutioner::execSummaryStatsScalar(
            LaunchContext::defaultContext(), variance::SummaryStatsStandardDeviation,
            input.buffer(), input.shapeInfo(), input.specialBuffer(), input.specialShapeInfo(),
            nullptr,
            output.buffer(), output.shapeInfo(), output.specialBuffer(), output.specialShapeInfo(),
            biasCorrected);
    } else {
        auto tadPack = ConstantTadHelper::getInstance().tadForDimensions(
            input.shapeInfo(), const_cast<sd::LongType*>(dimensions.data()), dimensions.size());

        NativeOpExecutioner::execSummaryStats(
            LaunchContext::defaultContext(), variance::SummaryStatsStandardDeviation,
            input.buffer(), input.shapeInfo(), input.specialBuffer(), input.specialShapeInfo(),
            nullptr,
            output.buffer(), output.shapeInfo(), output.specialBuffer(), output.specialShapeInfo(),
            const_cast<LongType*>(dimensions.data()), dimensions.size(),
            tadPack->primaryShapeInfo(), tadPack->primaryOffsets(),
            biasCorrected);
    }

    // Inform that we are done with those buffers
    NDArray::registerSpecialUse({&output}, {&input});
}

}  // namespace helpers
}  // namespace ops
}  // namespace sd