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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/helpers/cpu/concat.cpp
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2026-07-13 12:47:05 +08:00

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/* ******************************************************************************
*
*
* 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 Yurii Shyrma (iuriish@yahoo.com), created on 20.04.2018
//
#include <ops/declarable/helpers/transforms.h>
#include <ops/specials.h>
#include <system/selective_rendering.h>
#if NOT_EXCLUDED(OP_concat)
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
template <typename T>
static void concat_(const std::vector<NDArray*>& inArrs, NDArray& output, const int axis) {
sd::SpecialMethods<T>::concatCpuGeneric(inArrs, output, axis);
}
void concat(sd::LaunchContext* context, const std::vector<NDArray*>& inArrs, NDArray& output, const int axis) {
auto outputTYpe = output.dataType();
BUILD_SINGLE_SELECTOR(output.dataType(), concat_, (inArrs, output, axis), SD_COMMON_TYPES);
}
BUILD_SINGLE_TEMPLATE( void concat_,
(const std::vector<NDArray*>& inArrs, NDArray& output, const int axis), SD_COMMON_TYPES);
} // namespace helpers
} // namespace ops
} // namespace sd
#endif