wehub-resource-sync
115 lines
4.3 KiB
Plaintext
115 lines
4.3 KiB
Plaintext
/*
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* ******************************************************************************
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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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//
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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#include <helpers/PointersManager.h>
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#include <ops/declarable/helpers/convolutions.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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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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SD_KERNEL static void upsampling2dCuda(const void* vx, const LongType* xShapeInfo, void* vz,
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const LongType* zShapeInfo, const LongType factorH, const LongType factorW,
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const bool isNCHW) {
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const T* x = reinterpret_cast<const T*>(vx);
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T* z = reinterpret_cast<T*>(vz);
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__shared__ LongType rank, dimIH;
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__shared__ LongType zLen, *sharedMem;
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__shared__ LongType* xShape;
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__shared__ LongType* zShape;
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__shared__ LongType* xStride;
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__shared__ LongType* zStride;
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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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dimIH = isNCHW ? 2 : 1;
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zLen = shape::length(zShapeInfo);
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rank = 4;
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// Cache shape information
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xShape = shape::shapeOf(xShapeInfo);
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zShape = shape::shapeOf(zShapeInfo);
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xStride = shape::stride(xShapeInfo);
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zStride = shape::stride(zShapeInfo);
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}
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__syncthreads();
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const auto zInd = threadIdx.x + blockIdx.x * blockDim.x;
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if (zInd >= zLen) return;
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auto coords = sharedMem + threadIdx.x * rank;
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INDEX2COORDS(zInd, rank, zShape, coords);
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LongType zOffset;
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COORDS2INDEX(rank, zStride, coords, zOffset);
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coords[dimIH] /= factorH;
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coords[dimIH + 1] /= factorW;
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LongType xOffset;
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COORDS2INDEX(rank, xStride, coords, xOffset);
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z[zOffset] = x[xOffset];
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}
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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static void upsampling2dCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem,
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const cudaStream_t* stream, const void* vx, const LongType* xShapeInfo,
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void* vz, const LongType* zShapeInfo, const LongType factorH, const LongType factorW,
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const bool isNCHW) {
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upsampling2dCuda<T><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vz, zShapeInfo, factorH,
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factorW, isNCHW);
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DebugHelper::checkErrorCode(const_cast<cudaStream_t*>(stream),"upsampling2dCudaLauncher failed");
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}
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//////////////////////////////////////////////////////////////////////////
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void ConvolutionUtils::upsampling2d(graph::Context& block, NDArray& input, NDArray& output, const LongType factorH,
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const LongType factorW, const bool isNCHW) {
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PointersManager manager(block.launchContext(), "upsampling2d");
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dim3 getUpSampling = getUpsamplingDims(output.lengthOf(),output.rankOf());
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NDArray::prepareSpecialUse({&output}, {&input});
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BUILD_SINGLE_SELECTOR(
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input.dataType(), upsampling2dCudaLauncher,
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(getUpSampling.x, getUpSampling.y, getUpSampling.z, block.launchContext()->getCudaStream(), input.specialBuffer(),
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input.specialShapeInfo(), output.specialBuffer(), output.specialShapeInfo(), factorH, factorW, isNCHW),
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SD_FLOAT_TYPES);
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NDArray::registerSpecialUse({&output}, {&input});
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manager.synchronize();
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}
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} // namespace ops
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} // namespace sd
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