cavis/libnd4j/include/ops/declarable/helpers/cuda/concat.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 Yurii Shyrma (iuriish@yahoo.com), created on 20.04.2018
//
#include<ops/declarable/helpers/transforms.h>
#include <array/ResultSet.h>
#include <helpers/ShapeUtils.h>
#include <numeric>
#include <NDArrayFactory.h>
#include <helpers/TAD.h>
#include <exceptions/cuda_exception.h>
#include <PointersManager.h>
#include <ConstantTadHelper.h>
namespace nd4j {
namespace ops {
namespace helpers {
///////////////////////////////////////////////////////////////////
template<typename T>
__global__ static void concatCuda(void* pVx, void* pxShapeInfo, void* vz, Nd4jLong* zShapeInfo, const int axis) {
T* z = reinterpret_cast<T*>(vz);
__shared__ Nd4jLong zLen, totalThreads, *sharedMem;
__shared__ int rank;
if (threadIdx.x == 0) {
extern __shared__ unsigned char shmem[];
sharedMem = reinterpret_cast<Nd4jLong*>(shmem);
zLen = shape::length(zShapeInfo);
rank = shape::rank(zShapeInfo);
totalThreads = gridDim.x * blockDim.x;
}
__syncthreads();
const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
if(tid >= zLen)
return;
auto coords = sharedMem + threadIdx.x * rank;
shape::index2coords(tid, zShapeInfo, coords);
const auto zOffset = shape::getOffset(zShapeInfo, coords);
int inArrIdx = 0;
Nd4jLong *xShapeInfo = reinterpret_cast<Nd4jLong**>(pxShapeInfo)[inArrIdx];
while(coords[axis] >= xShapeInfo[axis + 1]) {
coords[axis] -= xShapeInfo[axis + 1];
xShapeInfo = reinterpret_cast<Nd4jLong**>(pxShapeInfo)[++inArrIdx];
}
const auto* x = reinterpret_cast<T*>(reinterpret_cast<void**>(pVx)[inArrIdx]);
const auto xOffset = shape::getOffset(xShapeInfo, coords);
z[zOffset] = x[xOffset];
}
///////////////////////////////////////////////////////////////////
template<typename T>
__host__ static void concatCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem, const cudaStream_t *stream,
void* pVx, void* pxShapeInfo, void* vz, Nd4jLong* zShapeInfo, const int axis) {
concatCuda<T><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(pVx, pxShapeInfo, vz, zShapeInfo, axis);
}
BUILD_SINGLE_TEMPLATE(template void concatCudaLauncher, (const int blocksPerGrid, const int threadsPerBlock, const int sharedMem, const cudaStream_t *stream, void* pVx, void* pxShapeInfo, void* vz, Nd4jLong* zShapeInfo, const int axis), LIBND4J_TYPES);
//////////////////////////////////////////////////////////////////////////
void concat(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output, const int axis) {
const int threadsPerBlock = MAX_NUM_THREADS / 4;
const int blocksPerGrid = (output.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
const int sharedMem = threadsPerBlock * sizeof(Nd4jLong) * output.rankOf() + 128;
const int numOfArrs = inArrs.size();
for(int i = 0; i < numOfArrs; ++i)
inArrs[i]->syncToDevice();
output.syncToDevice();
// prepare arrays of pointers on buffers and shapes
std::vector<void*> hInBuffers(numOfArrs);
std::vector<Nd4jLong*> hInShapeInfo(numOfArrs);
for(int i = 0; i < numOfArrs; ++i) {
hInBuffers[i] = inArrs[i]->getSpecialBuffer();
hInShapeInfo[i] = inArrs[i]->getSpecialShapeInfo();
}
PointersManager manager(context, "helpers::concat");
void* dInBuffers = manager.replicatePointer(hInBuffers.data(), hInBuffers.size() * sizeof(void*));
void* dInShapeInfo = manager.replicatePointer(hInShapeInfo.data(), hInShapeInfo.size() * sizeof(Nd4jLong*));
BUILD_SINGLE_SELECTOR(inArrs[0]->dataType(), concatCudaLauncher, (blocksPerGrid, threadsPerBlock, sharedMem, context->getCudaStream(), dInBuffers, dInShapeInfo, output.specialBuffer(), output.specialShapeInfo(), axis), LIBND4J_TYPES);
manager.synchronize();
for(int i = 0; i < numOfArrs; ++i)
inArrs[i]->tickReadDevice();
output.tickWriteDevice();
}
}
}
}