122 lines
4.6 KiB
Plaintext
122 lines
4.6 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 Yurii Shyrma, created on 10.06.2019
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//
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#include <ops/declarable/helpers/cross.h>
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#include <helpers/PointersManager.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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__global__ static void crossCuda(const void* vx, const Nd4jLong* xShapeInfo,
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const void* vy, const Nd4jLong* yShapeInfo,
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void* vz, const Nd4jLong* zShapeInfo) {
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__shared__ const T* x;
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__shared__ const T* y;
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__shared__ T* z;
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__shared__ int rank, *sharedMem;
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__shared__ Nd4jLong lenWithoutLastDim, totalThreads;
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if (threadIdx.x == 0) {
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x = reinterpret_cast<const T*>(vx);
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y = reinterpret_cast<const T*>(vy);
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z = reinterpret_cast<T*>(vz);
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extern __shared__ unsigned char shmem[];
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sharedMem = reinterpret_cast<int*>(shmem);
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totalThreads = gridDim.x * blockDim.x;
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rank = shape::rank(xShapeInfo);
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lenWithoutLastDim = shape::length(xShapeInfo) / xShapeInfo[rank]; // shape::length(xShapeInfo) / 3;
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}
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__syncthreads();
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auto coords = sharedMem + threadIdx.x * rank;
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const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
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for (uint i = tid; i < lenWithoutLastDim; i += totalThreads) {
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shape::index2coords(i, rank - 1, xShapeInfo + 1, coords);
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coords[rank - 1] = 0;
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auto xOffset = shape::getOffset(xShapeInfo, coords);
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auto yOffset = shape::getOffset(yShapeInfo, coords);
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const auto x0 = x[xOffset];
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const auto y0 = y[yOffset];
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xOffset += shape::stride(const_cast<Nd4jLong*>(xShapeInfo))[rank - 1];
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yOffset += shape::stride(const_cast<Nd4jLong*>(yShapeInfo))[rank - 1];
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const auto x1 = x[xOffset];
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const auto y1 = y[yOffset];
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xOffset += shape::stride(const_cast<Nd4jLong*>(xShapeInfo))[rank - 1];
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yOffset += shape::stride(const_cast<Nd4jLong*>(yShapeInfo))[rank - 1];
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const auto x2 = x[xOffset];
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const auto y2 = y[yOffset];
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auto zOffset = shape::getOffset(zShapeInfo, coords);
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z[zOffset] = x1 * y2 - x2 * y1;
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zOffset += shape::stride(const_cast<Nd4jLong*>(zShapeInfo))[rank - 1];
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z[zOffset] = x2 * y0 - x0 * y2;
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zOffset += shape::stride(const_cast<Nd4jLong*>(zShapeInfo))[rank - 1];
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z[zOffset] = x0 * y1 - x1 * y0;
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}
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}
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template<typename T>
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__host__ static void crossCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem, const cudaStream_t *stream,
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const void* vx, const Nd4jLong* xShapeInfo,
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const void* vy, const Nd4jLong* yShapeInfo,
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void* vz, const Nd4jLong* zShapeInfo) {
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crossCuda<T><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vy, yShapeInfo, vz, zShapeInfo);
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}
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BUILD_SINGLE_TEMPLATE(template void crossCudaLauncher, (const int blocksPerGrid, const int threadsPerBlock, const int sharedMem, const cudaStream_t *stream, const void* vx, const Nd4jLong* xShapeInfo, const void* vy, const Nd4jLong* yShapeInfo, void* vz, const Nd4jLong* zShapeInfo), NUMERIC_TYPES);
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void crossBatched(sd::LaunchContext* context, NDArray *x, NDArray *y, NDArray *z) {
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const int threadsPerBlock = MAX_NUM_THREADS / 4;
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const int blocksPerGrid = (x->lengthOf() / x->sizeAt(-1) + threadsPerBlock - 1) / threadsPerBlock;
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const int sharedMem = sizeof(int) * threadsPerBlock * x->rankOf() + 128;
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PointersManager manager(context, "cross");
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NDArray::prepareSpecialUse({z}, {x, y});
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BUILD_SINGLE_SELECTOR(x->dataType(), crossCudaLauncher, (blocksPerGrid, threadsPerBlock, sharedMem, context->getCudaStream(), x->getSpecialBuffer(), x->getSpecialShapeInfo(), y->getSpecialBuffer(), y->getSpecialShapeInfo(), z->specialBuffer(), z->specialShapeInfo()), NUMERIC_TYPES);
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NDArray::registerSpecialUse({z}, {x, y});
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manager.synchronize();
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}
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}
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}
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} |