wehub-resource-sync
151 lines
5.9 KiB
Plaintext
151 lines
5.9 KiB
Plaintext
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 Oleh Semeniv (oleg.semeniv@gmail.com)
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//
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#include <helpers/PointersManager.h>
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#include <math/platformmath.h>
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#include <math/templatemath.h>
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#include <ops/declarable/helpers/updatersHelpers.h>
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#include <system/op_boilerplate.h>
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#include "execution/cuda/LaunchDims.h"
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#include "helpers/DebugHelper.h"
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namespace sd {
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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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SD_KERNEL void nesterovsUpdaterCuda(const void* vx, const LongType* xShapeInfo, const void* vin,
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const LongType* inShapeInfo, void* vz, const LongType* zShapeInfo,
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void* vst, const LongType* stShapeInfo, const T lr, const T momentum) {
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const auto grad = reinterpret_cast<const T*>(vx);
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const auto init = reinterpret_cast<const T*>(vin);
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auto up = reinterpret_cast<T*>(vz);
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auto st = reinterpret_cast<T*>(vst);
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__shared__ LongType xLen, xRank, zRank, inRank, stRank;
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__shared__ T momentumT;
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__shared__ bool bOrdering, bXZsame, bXInSame, bXStSame;
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__shared__ LongType *sharedMem;
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__shared__ const LongType *xShape, *zShape, *inShape, *stShape;
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__shared__ const LongType *xStride, *zStride, *inStride, *stStride;
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if (threadIdx.x == 0) {
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extern __shared__ unsigned char shmem[];
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sharedMem = reinterpret_cast<LongType*>(shmem);
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xLen = shape::length(xShapeInfo);
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momentumT = (-momentum - 1);
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xRank = shape::rank(xShapeInfo);
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zRank = shape::rank(zShapeInfo);
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inRank = shape::rank(inShapeInfo);
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stRank = shape::rank(stShapeInfo);
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xShape = shape::shapeOf(xShapeInfo);
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xStride = shape::stride(xShapeInfo);
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zShape = shape::shapeOf(zShapeInfo);
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zStride = shape::stride(zShapeInfo);
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inShape = shape::shapeOf(inShapeInfo);
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inStride = shape::stride(inShapeInfo);
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stShape = shape::shapeOf(stShapeInfo);
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stStride = shape::stride(stShapeInfo);
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bOrdering = shape::order(xShapeInfo) == shape::order(zShapeInfo) &&
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shape::order(xShapeInfo) == shape::order(inShapeInfo) &&
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shape::order(xShapeInfo) == shape::order(stShapeInfo);
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bXZsame = shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo);
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bXInSame = shape::haveSameShapeAndStrides(xShapeInfo, inShapeInfo);
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bXStSame = shape::haveSameShapeAndStrides(xShapeInfo, stShapeInfo);
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}
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__syncthreads();
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LongType coords[SD_MAX_RANK];
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for (LongType i = blockIdx.x * blockDim.x + threadIdx.x; i < xLen; i += gridDim.x * blockDim.x) {
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LongType xOffset, zOffset, initOffset, stOffset;
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INDEX2COORDS(i, xRank, xShape, coords);
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COORDS2INDEX(xRank, xStride, coords, xOffset);
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if (bXZsame) {
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zOffset = xOffset;
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} else {
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COORDS2INDEX(zRank, zStride, coords, zOffset);
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}
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if (bXInSame) {
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initOffset = xOffset;
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} else {
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COORDS2INDEX(inRank, inStride, coords, initOffset);
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}
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if (bXStSame) {
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stOffset = xOffset;
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} else {
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COORDS2INDEX(stRank, stStride, coords, stOffset);
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}
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T prevState = momentum * init[initOffset];
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st[stOffset] = prevState - lr * grad[xOffset];
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up[zOffset] = prevState + momentumT * st[stOffset];
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}
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}
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///////////////////////////////////////////////////////////////////
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template <typename T>
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void nesterovsUpdaterCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMemory,
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const cudaStream_t* stream, const void* vx, const LongType* xShapeInfo,
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const void* vin, const LongType* inShapeInfo, void* vz,
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const LongType* zShapeInfo, void* vst, const LongType* stShapeInfo,
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const double dLr, const double dMomentum) {
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const T lr = static_cast<T>(dLr);
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const T momentum = static_cast<T>(dMomentum);
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nesterovsUpdaterCuda<T><<<blocksPerGrid, threadsPerBlock, sharedMemory, *stream>>>(vx, xShapeInfo, vin, inShapeInfo, vz,
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zShapeInfo, vst, stShapeInfo, lr, momentum);
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sd::DebugHelper::checkErrorCode(const_cast<cudaStream_t *>(stream), "nesterovsUpdaterCuda failed");
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}
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///////////////////////////////////////////////////////////////////
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void updaterNesterovs(LaunchContext* context, NDArray& gradient, NDArray& initState, NDArray& update,
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NDArray& stateV, const double dLr, const double dMomentum) {
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PointersManager manager(context, "nesterovsUpdater");
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dim3 launchDims = updaterDims(gradient.lengthOf());
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NDArray::prepareSpecialUse({&update, &stateV}, {&gradient, &initState});
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BUILD_SINGLE_SELECTOR(
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gradient.dataType(), nesterovsUpdaterCudaLauncher,
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(launchDims.y, launchDims.x,launchDims.z, context->getCudaStream(), gradient.specialBuffer(), gradient.specialShapeInfo(),
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initState.specialBuffer(), initState.specialShapeInfo(), update.specialBuffer(), update.specialShapeInfo(),
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stateV.specialBuffer(), stateV.specialShapeInfo(), dLr, dMomentum),
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SD_FLOAT_TYPES);
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NDArray::registerSpecialUse({&update, &stateV}, {&gradient, &initState});
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manager.synchronize();
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}
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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