331 lines
14 KiB
Plaintext
331 lines
14 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 raver119@gmail.com
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//
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#include <ops/declarable/helpers/roll.h>
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#include <helpers/ConstantTadHelper.h>
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#include <helpers/PointersManager.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename T>
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static void _CUDA_D rollKernelLinearStage1Dev(void *vx, Nd4jLong *xShapeInfo, void *vz, Nd4jLong *zShapeInfo, Nd4jLong fullLength, int actualShift) {
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auto x = reinterpret_cast<T*>(vx);
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auto z = reinterpret_cast<T*>(vz);
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auto xEws = shape::elementWiseStride(xShapeInfo);
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auto zEws = shape::elementWiseStride(zShapeInfo);
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auto xOrder = shape::order(xShapeInfo);
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auto zOrder = shape::order(zShapeInfo);
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auto tid = threadIdx.x + blockIdx.x * blockDim.x;
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if (xEws > 0 && zEws > 0 && xOrder == zOrder) {
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for (int i = tid; i < actualShift; i += blockDim.x * gridDim.x) {
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int sourceIndex = fullLength - actualShift + i;
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auto eA = x[sourceIndex * xEws];
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auto eB = x[i * xEws];
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z[i * zEws] = eA;
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z[sourceIndex * zEws] = eB;
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}
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} else {
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for (int i = tid; i < actualShift; i += blockDim.x * gridDim.x) {
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int sourceIndex = fullLength - actualShift + i;
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auto xOffsetA = shape::getIndexOffset(i, xShapeInfo);
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auto xOffsetB = shape::getIndexOffset(sourceIndex, xShapeInfo);
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auto zOffsetA = shape::getIndexOffset(i, zShapeInfo);
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auto zOffsetB = shape::getIndexOffset(sourceIndex, zShapeInfo);
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auto eA = x[xOffsetA];
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auto eB = x[xOffsetB];
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z[zOffsetA] = eB;
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z[zOffsetB] = eA;
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}
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}
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}
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template <typename T>
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static void _CUDA_G rollKernelLinearStage1(void *vx, Nd4jLong *xShapeInfo, void *vz, Nd4jLong *zShapeInfo, Nd4jLong fullLength, int actualShift) {
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rollKernelLinearStage1Dev<T>(vx, xShapeInfo, vz, zShapeInfo, fullLength, actualShift);
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}
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template <typename T>
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static void _CUDA_G rollKernelLinearStage2(void *vx, Nd4jLong *xShapeInfo, void *vz, Nd4jLong *zShapeInfo, Nd4jLong fullLength, int actualShift, int shiftCount) {
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auto x = reinterpret_cast<T*>(vx);
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auto z = reinterpret_cast<T*>(vz);
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auto xEws = shape::elementWiseStride(xShapeInfo);
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auto zEws = shape::elementWiseStride(zShapeInfo);
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auto xOrder = shape::order(xShapeInfo);
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auto zOrder = shape::order(zShapeInfo);
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auto tid = threadIdx.x + blockIdx.x * blockDim.x;
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if (xEws > 0 && zEws > 0 && xOrder == zOrder) {
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for (int count = 1; count < shiftCount; ++count) {
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for (int i = tid; i < actualShift; i += blockDim.x * gridDim.x) {
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int destinationIndex = fullLength - (count + 1) * actualShift + i;
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int sourceIndex = fullLength - count * actualShift + i;
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auto eA = x[sourceIndex * xEws];
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auto eB = x[destinationIndex * xEws];
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z[destinationIndex * zEws] = eA;
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z[sourceIndex * zEws] = eB;
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}
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__syncthreads();
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}
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} else {
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for (int count = 1; count < shiftCount; ++count) {
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for (int i = tid; i < actualShift; i += blockDim.x * gridDim.x) {
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int destinationIndex = fullLength - (count + 1) * actualShift + i;
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int sourceIndex = fullLength - count * actualShift + i;
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auto xOffsetA = shape::getIndexOffset(destinationIndex, xShapeInfo);
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auto xOffsetB = shape::getIndexOffset(sourceIndex, xShapeInfo);
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auto zOffsetA = shape::getIndexOffset(destinationIndex, zShapeInfo);
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auto zOffsetB = shape::getIndexOffset(sourceIndex, zShapeInfo);
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auto eA = x[xOffsetA];
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auto eB = x[xOffsetB];
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z[zOffsetA] = eB;
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z[zOffsetB] = eA;
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}
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__syncthreads();
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}
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}
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}
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template <typename T>
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static void _CUDA_G rollKernelLinearStage3(void *vx, Nd4jLong *xShapeInfo, void *vz, Nd4jLong *zShapeInfo, Nd4jLong fullLength, int actualShift, int remainShift) {
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auto x = reinterpret_cast<T*>(vx);
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auto z = reinterpret_cast<T*>(vz);
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auto xEws = shape::elementWiseStride(xShapeInfo);
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auto zEws = shape::elementWiseStride(zShapeInfo);
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auto xOrder = shape::order(xShapeInfo);
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auto zOrder = shape::order(zShapeInfo);
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auto tid = threadIdx.x + blockIdx.x * blockDim.x;
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if (xEws > 0 && zEws > 0 && xOrder == zOrder) {
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for (int i = tid ; i < actualShift; i += blockDim.x * gridDim.x) {
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int remainIdx = i + actualShift;
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int sourceIndex = remainIdx + remainShift;
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auto eA = x[sourceIndex * xEws];
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auto eB = x[remainIdx * xEws];
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z[remainIdx * zEws] = eA;
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z[sourceIndex * zEws] = eB;
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}
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} else {
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for (int i = tid; i < actualShift; i += blockDim.x * gridDim.x) {
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int remainIdx = i + actualShift;
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int sourceIndex = remainIdx + remainShift;
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auto xOffsetA = shape::getIndexOffset(remainIdx, xShapeInfo);
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auto xOffsetB = shape::getIndexOffset(sourceIndex, xShapeInfo);
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auto zOffsetA = shape::getIndexOffset(remainIdx, zShapeInfo);
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auto zOffsetB = shape::getIndexOffset(sourceIndex, zShapeInfo);
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auto eA = x[xOffsetA];
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auto eB = x[xOffsetB];
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z[zOffsetA] = eB;
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z[zOffsetB] = eA;
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}
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}
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}
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template <typename T>
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static void _CUDA_D swapTadsKernel(void *vx, void *vz, Nd4jLong *zShapeInfo, Nd4jLong tadLength) {
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auto x = reinterpret_cast<T*>(vx);
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auto z = reinterpret_cast<T*>(vz);
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auto zEws = shape::elementWiseStride(zShapeInfo);
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auto zOrder = shape::order(zShapeInfo);
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auto tid = threadIdx.x + blockIdx.x * blockDim.x;
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if (zEws > 0) {
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for (int e = threadIdx.x; e < tadLength; e += blockDim.x) {
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auto eA = x[e * zEws];
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auto eB = z[e * zEws];
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x[e * zEws] = eB;
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z[e * zEws] = eA;
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}
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} else {
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for (int e = threadIdx.x; e < tadLength; e += blockDim.x) {
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auto zOffset = shape::getIndexOffset(e, zShapeInfo);
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auto eA = x[zOffset];
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auto eB = z[zOffset];
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x[zOffset] = eB;
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z[zOffset] = eA;
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}
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}
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}
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template <typename T>
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static void _CUDA_G rollKernelFullAnyDimensionStage1(void *vx, Nd4jLong *xTadShapeInfo, Nd4jLong *xTadOffsets, void *vz, Nd4jLong *zTadShapeInfo, Nd4jLong *zTadOffsets, int numTads, Nd4jLong tadLength, int dim, Nd4jLong sizeAt, int theShift) {
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auto x = reinterpret_cast<T *>(vx);
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auto z = reinterpret_cast<T *>(vz);
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for (int e = blockIdx.x + theShift; e < sizeAt - theShift; e += gridDim.x) {
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int sourceIndex = dim * sizeAt + e - theShift;
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int targetIndex = dim * sizeAt + e;
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swapTadsKernel<T>(z + xTadOffsets[sourceIndex], z + xTadOffsets[targetIndex], zTadShapeInfo, tadLength);
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}
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}
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template <typename T>
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static void _CUDA_G rollKernelFullAnyDimensionStage2(void *vx, Nd4jLong *xTadShapeInfo, Nd4jLong *xTadOffsets, void *vz, Nd4jLong *zTadShapeInfo, Nd4jLong *zTadOffsets, int numTads, Nd4jLong tadLength, int dim, Nd4jLong sizeAt, int theShift) {
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auto x = reinterpret_cast<T *>(vx);
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auto z = reinterpret_cast<T *>(vz);
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for (int e = blockIdx.x; e < theShift; e += gridDim.x) {
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int sourceIndex = dim * sizeAt + sizeAt - theShift + e;
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int targetIndex = dim * sizeAt + e;
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swapTadsKernel<T>(z + zTadOffsets[sourceIndex], z + zTadOffsets[targetIndex], zTadShapeInfo, tadLength);
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}
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}
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template <typename T>
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static void rollFunctorFull_(NDArray* input, NDArray* output, std::vector<int> const& shifts, std::vector<int> const& axes, bool inplace){
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if (!inplace)
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output->assign(input);
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for (size_t i = 0; i < axes.size(); i++) {
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int axe = axes[i];
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if (axe == input->rankOf() - 1) { // last dimension
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ResultSet listOfTensors = output->allTensorsAlongDimension({axe});
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ResultSet listOfOutTensors = output->allTensorsAlongDimension({axe});
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int fullLen = listOfTensors.size();
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int theShift = shifts[i];
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// if (theShift > 0) {
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// theShift %= fullLen;
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// }
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// else {
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// theShift -= fullLen * (theShift / fullLen - 1);
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// }
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for (int k = 0; k < fullLen; k++) {
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rollFunctorLinear(output->getContext(), listOfTensors.at(k), listOfOutTensors.at(k), theShift, true);
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}
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} else {
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std::vector<int> dims(input->rankOf() - axe - 1);
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for (int i = 0; i < dims.size(); ++i)
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dims[i] = axe + 1 + i;
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auto packZ = ConstantTadHelper::getInstance()->tadForDimensions(output->shapeInfo(), dims);
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int numTads = packZ.numberOfTads();
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int sizeAt = input->sizeAt(axe);
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auto tadLength = shape::length(packZ.primaryShapeInfo());
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int theShift = shifts[i];
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// if (theShift > 0)
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// theShift %= sizeAt;
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// else
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// theShift -= sizeAt * (theShift / sizeAt - 1);
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if (theShift) {
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for (int dim = 0; dim < numTads / sizeAt; ++dim) {
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rollKernelFullAnyDimensionStage1<T><<<1, 256, 1024, *(output->getContext()->getCudaStream())>>>(output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), numTads, tadLength, dim, sizeAt, theShift);
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rollKernelFullAnyDimensionStage2<T><<<1, 256, 1024, *(output->getContext()->getCudaStream())>>>(output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), numTads, tadLength, dim, sizeAt, theShift);
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}
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}
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}
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}
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}
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template <typename T>
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static void rollFunctorLinear_(NDArray* input, NDArray* output, int shift, bool inplace){
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if (!inplace)
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output->assign(input);
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auto fullLen = input->lengthOf();
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int actualShift = shift; // % fullLen; // shift already non-negative then
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if (actualShift < 0) {
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actualShift -= fullLen * (actualShift / fullLen - 1);
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}
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else
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actualShift %= fullLen;
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if (actualShift) {
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int shiftCount = fullLen / actualShift - 1;
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int remainShift = fullLen % actualShift;
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// stage 1) swap last actualShift elements with first ones.
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rollKernelLinearStage1<T><<<1, 1, 1024, *(output->getContext()->getCudaStream())>>>(output->specialBuffer(), output->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), fullLen, actualShift);
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// stage 2) swap swapped actualShift elements with rest remainShiftCount times.
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rollKernelLinearStage2<T><<<1, 1, 1024, *(output->getContext()->getCudaStream())>>>(output->specialBuffer(), output->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), fullLen, actualShift, shiftCount);
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// FIXME: no parallelism here :(
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// stage 3) swap remainer of items.
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if (remainShift && shiftCount)
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rollKernelLinearStage3<T><<<1, 1, 1024, *(output->getContext()->getCudaStream())>>>(output->specialBuffer(), output->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), fullLen, actualShift, remainShift);
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}
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}
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void rollFunctorFull(nd4j::LaunchContext * context, NDArray* input, NDArray* output, std::vector<int> const& shifts, std::vector<int> const& axes, bool inplace){
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input->syncToDevice();
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BUILD_SINGLE_SELECTOR(input->dataType(), rollFunctorFull_, (input, output, shifts, axes, inplace), LIBND4J_TYPES);
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output->tickWriteDevice();
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}
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void rollFunctorLinear(nd4j::LaunchContext * context, NDArray* input, NDArray* output, int shift, bool inplace){
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input->syncToDevice();
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BUILD_SINGLE_SELECTOR(input->dataType(), rollFunctorLinear_, (input, output, shift, inplace), LIBND4J_TYPES);
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output->tickWriteDevice();
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}
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BUILD_SINGLE_TEMPLATE(template void rollFunctorLinear_, (NDArray* input, NDArray* output, int shift, bool inplace), LIBND4J_TYPES);
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BUILD_SINGLE_TEMPLATE(template void rollFunctorFull_, (NDArray* input, NDArray* output, std::vector<int> const& shifts, std::vector<int> const& axes, bool inplace), LIBND4J_TYPES);
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}
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}
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} |