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/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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 <helpers/PointersManager.h>
#include <ops/declarable/helpers/convolutions.h>
#include "execution/cuda/LaunchDims.h"
#include "helpers/DebugHelper.h"
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
template <typename T>
SD_KERNEL static void upsampling2dBPCuda(const void* vx, const LongType* xShapeInfo, void* vz,
const LongType* zShapeInfo, const bool isNCHW) {
const T* x = reinterpret_cast<const T*>(vx);
T* z = reinterpret_cast<T*>(vz);
__shared__ LongType rank, dimIH;
__shared__ LongType factorH, factorW;
__shared__ LongType zLen, *sharedMem;
__shared__ LongType* xShape;
__shared__ LongType* zShape;
__shared__ LongType* xStride;
__shared__ LongType* zStride;
if (threadIdx.x == 0) {
extern __shared__ unsigned char shmem[];
sharedMem = reinterpret_cast<LongType*>(shmem);
dimIH = isNCHW ? 2 : 1;
zLen = shape::length(zShapeInfo);
rank = 4;
factorH = xShapeInfo[dimIH + 1] / zShapeInfo[dimIH + 1];
factorW = xShapeInfo[dimIH + 2] / zShapeInfo[dimIH + 2];
// Cache shape information
xShape = shape::shapeOf(xShapeInfo);
zShape = shape::shapeOf(zShapeInfo);
xStride = shape::stride(xShapeInfo);
zStride = shape::stride(zShapeInfo);
}
__syncthreads();
const auto zInd = threadIdx.x + blockIdx.x * blockDim.x;
if (zInd >= zLen) return;
auto coords = sharedMem + threadIdx.x * rank;
INDEX2COORDS(zInd, rank, zShape, coords);
LongType zOffset;
COORDS2INDEX(rank, zStride, coords, zOffset);
z[zOffset] = 0;
const LongType zCoord2 = coords[dimIH] * factorH;
const LongType zCoord3 = coords[dimIH + 1] * factorW;
for (coords[dimIH] = zCoord2; coords[dimIH] < zCoord2 + factorH; ++coords[dimIH])
for (coords[dimIH + 1] = zCoord3; coords[dimIH + 1] < zCoord3 + factorW; ++coords[dimIH + 1]) {
LongType xOffset;
COORDS2INDEX(rank, xStride, coords, xOffset);
z[zOffset] += x[xOffset];
}
}
//////////////////////////////////////////////////////////////////////////
template <typename T>
static void upsampling2dBPCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem,
const cudaStream_t* stream, const void* vx, const LongType* xShapeInfo,
void* vz, const LongType* zShapeInfo, const bool isNCHW) {
upsampling2dBPCuda<T><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vz, zShapeInfo, isNCHW);
DebugHelper::checkErrorCode(const_cast<cudaStream_t*>(stream),"upsampling2dBPCuda failed");
}
//////////////////////////////////////////////////////////////////////////
void ConvolutionUtils::upsampling2dBP(graph::Context& block, NDArray& gradO, NDArray& gradI,
const bool isNCHW) {
PointersManager manager(block.launchContext(), "upsampling2d_bp");
dim3 getUpSampling = getUpsamplingDims(gradI.lengthOf(),gradI.rankOf());
NDArray::prepareSpecialUse({&gradI}, {&gradO});
BUILD_SINGLE_SELECTOR(
gradI.dataType(), upsampling2dBPCudaLauncher,
(getUpSampling.x, getUpSampling.y, getUpSampling.z, block.launchContext()->getCudaStream(), gradO.specialBuffer(),
gradO.specialShapeInfo(), gradI.specialBuffer(), gradI.specialShapeInfo(), isNCHW),
SD_FLOAT_TYPES);
NDArray::registerSpecialUse({&gradI}, {&gradO});
manager.synchronize();
}
} // namespace ops
} // namespace sd