cavis/libnd4j/include/ops/declarable/helpers/cuda/split.cu

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/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
* Copyright (c) 2019 Konduit K.K.
*
* 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)
//
#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 splitCuda(const void* vx, const Nd4jLong* xShapeInfo, void* pVz, const Nd4jLong* zTadShapeInfo, const int axis) {
const T* x = reinterpret_cast<const T*>(vx);
__shared__ Nd4jLong xLen, totalThreads;
__shared__ int xRank, zDim;
if (threadIdx.x == 0) {
xLen = shape::length(xShapeInfo);
xRank = shape::rank(xShapeInfo);
zDim = shape::shapeOf(zTadShapeInfo)[axis]; // same for all input arrays
totalThreads = gridDim.z * blockDim.z;
}
__syncthreads();
const auto tid = blockIdx.z * blockDim.z + threadIdx.z;
Nd4jLong coords[MAX_RANK];
for (uint64_t i = tid; i < xLen; i += totalThreads) {
shape::index2coords(i, xShapeInfo, coords);
const auto xOffset = shape::getOffset(xShapeInfo, coords);
auto *z = reinterpret_cast<T*>(reinterpret_cast<void **>(pVz)[coords[axis] / zDim]);
coords[axis] %= zDim;
const auto zOffset = shape::getOffset(zTadShapeInfo, coords);
z[zOffset] = x[xOffset];
}
}
///////////////////////////////////////////////////////////////////
template<typename T>
__host__ static void splitCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream,
const void* vx, const Nd4jLong* xShapeInfo, void* pVz, const Nd4jLong* zTadShapeInfo, const int axis) {
splitCuda<T><<<blocksPerGrid, threadsPerBlock, 256, *stream>>>(vx, xShapeInfo, pVz, zTadShapeInfo, axis);
}
BUILD_SINGLE_TEMPLATE(template void splitCudaLauncher, (const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream, const void* vx, const Nd4jLong* xShapeInfo, void* pVz, const Nd4jLong* zTadShapeInfo, const int axis), LIBND4J_TYPES);
//////////////////////////////////////////////////////////////////////////
void split(nd4j::LaunchContext* context, const NDArray& input, std::vector<NDArray*>& outArrs, const int axis) {
const int numOfSubArrs = outArrs.size();
const auto sizeofT = input.sizeOfT();
for(int i = 0; i < numOfSubArrs; ++i)
outArrs[i]->syncToDevice();
input.syncToDevice();
bool luckCase1 = ((axis == 0 && input.ordering() == 'c') || (axis == input.rankOf() - 1 && input.ordering() == 'f')) && input.ews() == 1;
if(luckCase1) {
for (uint i = 0; i < numOfSubArrs; ++i) {
luckCase1 &= outArrs[i]->ordering() == input.ordering() && outArrs[i]->ews() == 1;
if(!luckCase1)
break;
}
}
if(luckCase1) { // for example {1,10} + {2,10} + {3,10} = {6, 10} order c; or {10,1} + {10,2} + {10,3} = {10, 6} order f
void* x = static_cast<int8_t*>(input.getSpecialBuffer());
for (uint i = 0; i < numOfSubArrs; ++i) {
const auto memAmountToCopy = outArrs[i]->lengthOf() * sizeofT;
cudaMemcpyAsync(static_cast<int8_t*>(outArrs[i]->getSpecialBuffer()), x, memAmountToCopy, cudaMemcpyDeviceToDevice, *context->getCudaStream());
x = static_cast<int8_t*>(x) + memAmountToCopy;
}
if(cudaStreamSynchronize(*context->getCudaStream()) != 0)
throw std::runtime_error("split cuda: luckCase1 failed!");
for(int i = 0; i < numOfSubArrs; ++i)
outArrs[i]->tickWriteDevice();
input.tickReadDevice();
return;
}
const bool isXcontin = input.strideAt(axis) == 1;
bool areOutputsContin = true;
bool allSameOrder = true;
if(isXcontin) {
for (uint i = 0; i < outArrs.size(); ++i) {
areOutputsContin &= outArrs[i]->strideAt(axis) == 1;
allSameOrder &= input.ordering() == outArrs[i]->ordering();
if(!areOutputsContin || !allSameOrder)
break;
}
}
const bool luckCase2 = isXcontin && areOutputsContin && allSameOrder;
if(luckCase2) { // for example {2,1,3} + {2,5,3} + {2,10,3} = {2,16,3}, here axis 1 shoud have stride = 1 for all inputs arrays and input array
const auto xDim = input.sizeAt(axis);
const auto zDim = outArrs[0]->sizeAt(axis); // same for all outArrs
for (uint i = 0; i < input.lengthOf() / xDim; ++i) {
const auto iShift = i * sizeofT;
void* x = static_cast<int8_t*>(input.getSpecialBuffer()) + xDim * iShift;
for (uint j = 0; j < numOfSubArrs; ++j) {
void* z = static_cast<int8_t*>(outArrs[j]->getSpecialBuffer()) + zDim * iShift;
const auto memSizeToCopy = zDim * sizeofT;
cudaMemcpyAsync(z, x, memSizeToCopy, cudaMemcpyDeviceToDevice, *context->getCudaStream());
x = static_cast<int8_t*>(x) + memSizeToCopy;
}
}
if(cudaStreamSynchronize(*context->getCudaStream()) != 0)
throw std::runtime_error("split cuda: luckCase2 failed!");
}
else { // general (slower) case
const int threadsPerBlock = MAX_NUM_THREADS / 2;
const int blocksPerGrid = (input.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
// prepare arrays of pointers on buffers and shapes
std::vector<void*> hOutBuffers(numOfSubArrs);
for(int i = 0; i < numOfSubArrs; ++i)
hOutBuffers[i] = outArrs[i]->getSpecialBuffer();
PointersManager manager(context, "helpers::split");
void* dOutBuffers = manager.replicatePointer(hOutBuffers.data(), hOutBuffers.size() * sizeof(void*));
BUILD_SINGLE_SELECTOR(input.dataType(), splitCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), input.getSpecialBuffer(), input.getSpecialShapeInfo(), dOutBuffers, outArrs[0]->specialShapeInfo(), axis), LIBND4J_TYPES);
manager.synchronize();
}
for(int i = 0; i < numOfSubArrs; ++i)
outArrs[i]->tickWriteDevice();
input.tickReadDevice();
}
}
}
}