78 lines
3.3 KiB
Plaintext
78 lines
3.3 KiB
Plaintext
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author Yurii Shyrma (iuriish@yahoo.com), created on 20.04.2018
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//
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#include<ops/declarable/helpers/transforms.h>
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#include <array/ResultSet.h>
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#include <helpers/ShapeUtils.h>
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#include <numeric>
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#include <NDArrayFactory.h>
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#include <helpers/TAD.h>
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#include <exceptions/cuda_exception.h>
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#include <PointersManager.h>
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#include <ConstantTadHelper.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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///////////////////////////////////////////////////////////////////
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template<typename T>
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__global__ static void concatCuda(const int numOfArrs, void* pVx, void* pxShapeInfo, void* pVz, void* pzShapeInfo) {
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__shared__ int arrIdx, blocksPerArr;
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if (threadIdx.x == 0) {
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blocksPerArr = (gridDim.x + numOfArrs - 1) / numOfArrs; // ceil
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arrIdx = blockIdx.x / blocksPerArr;
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}
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__syncthreads();
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for(int j = arrIdx; j < numOfArrs; j += gridDim.x) {
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const auto* x = reinterpret_cast<T*>(reinterpret_cast<void**>(pVx)[j]);
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auto* z = reinterpret_cast<T*>(reinterpret_cast<void**>(pVz)[j]);
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const auto* xShapeInfo = reinterpret_cast<Nd4jLong**>(pxShapeInfo)[j];
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const auto* zShapeInfo = reinterpret_cast<Nd4jLong**>(pzShapeInfo)[j];
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const auto arrLen = shape::length(xShapeInfo);
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const auto arrLenPerBlock = (arrLen + blocksPerArr - 1) / blocksPerArr; // ceil
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const auto start = (blockIdx.x % blocksPerArr) * arrLenPerBlock;
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const auto end = (start + arrLenPerBlock) > arrLen ? arrLen : (start + arrLenPerBlock);
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for (Nd4jLong i = start + threadIdx.x; i < end; i += blockDim.x)
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z[shape::getIndexOffset(i, zShapeInfo, arrLen)] = x[shape::getIndexOffset(i, xShapeInfo, arrLen)];
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}
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}
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///////////////////////////////////////////////////////////////////
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template<typename T>
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__host__ static void concatCudaLauncher(const int numOfArrs, const cudaStream_t *stream, void* pVx, void* pxShapeInfo, void* pVz, void* pzShapeInfo) {
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concatCuda<T><<<512, 512, 512, *stream>>>(numOfArrs, pVx, pxShapeInfo, pVz, pzShapeInfo);
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}
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BUILD_SINGLE_TEMPLATE(template void concatCudaLauncher, (const int numOfArrs, const cudaStream_t *stream, void* pVx, void* pxShapeInfo, void* pVz, void* pzShapeInfo), LIBND4J_TYPES);
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}
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}
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} |