cavis/libnd4j/include/loops/cuda/specials/concatKernelScalar.cu

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/*******************************************************************************
* 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 raver119@gmail.com
// @author Yurii Shyrma, created on 15.11.2018
//
#include <loops/special_kernels.h>
namespace nd4j {
///////////////////////////////////////////////////////////////////////
template<typename T>
__device__ void concatKernelScalar(int numArrays, Nd4jPointer *data, void *vz) {
auto z = static_cast<T *>(vz);
Nd4jLong tid = blockIdx.x * blockDim.x + threadIdx.x;
auto input = reinterpret_cast<T **>(data);
for (int i = tid; i < numArrays; i += blockDim.x * gridDim.x)
z[i] = input[i][0];
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__global__ void execConcatKernelScalar(int numArrays, Nd4jPointer *data, void *vz) {
concatKernelScalar<T>(numArrays, data, vz);
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__host__ void
concatKernelScalarGeneric(dim3 &launchDims, cudaStream_t *stream, int numArrays, Nd4jPointer *data, void *vz) {
execConcatKernelScalar<T><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(numArrays, data, vz);
nd4j::DebugHelper::checkErrorCode(stream, "concatScalar(...) failed");
}
BUILD_SINGLE_TEMPLATE(template void ND4J_EXPORT concatKernelScalarGeneric, (dim3 & launchDims, cudaStream_t * stream, int numArrays, Nd4jPointer * data, void * vz), LIBND4J_TYPES);
}