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

//
// @author GS (sgazeos@gmail.com), created on 10/1/2018
//


#include<ops/declarable/helpers/cross.h>
#include <helpers/ShapeUtils.h>
#include <ops/declarable/CustomOperations.h>

namespace nd4j 	  {
namespace ops 	  {
namespace helpers {

void crossBatched(nd4j::LaunchContext * context, NDArray *a, NDArray *b, NDArray *o) {
    auto _a = a->reshape(a->ordering(), {-1, 3});
    auto _b = b->reshape(b->ordering(), {-1, 3});
    auto _o = o->reshape(o->ordering(), {-1, 3}, false);

    auto tadsA = _a.allTensorsAlongDimension({1});
    auto tadsB = _b.allTensorsAlongDimension({1});
    auto tadsO = _o.allTensorsAlongDimension({1});

    int tads = tadsA.size();

    auto func = PRAGMA_THREADS_FOR {
        for (auto e = start; e < stop; e += increment) {
            auto a_ = tadsA.at(e);
            auto b_ = tadsB.at(e);
            auto o_ = tadsO.at(e);

            helpers::cross(context, a_, b_, o_);
        }
    };

    samediff::Threads::parallel_tad(func, 0, tads);
}

}
}
}