wehub-resource-sync
559 lines
17 KiB
Plaintext
559 lines
17 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,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See
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* the 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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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#include <exceptions/cuda_exception.h>
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#include <execution/LaunchContext.h>
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#include <helpers/DebugHelper.h>
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#include <loops/legacy_ops.h>
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#include <loops/reduce_bool.h>
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#include <loops/scalar.h>
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#include <system/op_boilerplate.h>
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#include <system/common.h>
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#include <types/types.h>
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using namespace simdOps;
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Z, typename OpType>
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SD_KERNEL SD_INLINE void simpleReduce(
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const void* x,
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const sd::LongType* outerXTadShapeInfo,
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const sd::LongType* innerXTadShapeInfo,
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void* extraParams,
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void* vreductionBuffer,
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void* z,
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const sd::LongType* zShapeInfo) {
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functions::reduce::ReduceBoolFunction<X, Z>::template transformCuda<OpType>(
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x,
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outerXTadShapeInfo,
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innerXTadShapeInfo,
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vreductionBuffer,
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extraParams,
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z,
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zShapeInfo);
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Z, typename OpType>
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SD_KERNEL SD_INLINE void simpleScalar(
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const void* x,
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const sd::LongType* xShapeInfo,
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void* extraParams,
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void* z,
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const sd::LongType* zShapeInfo,
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sd::LongType* dimension,
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sd::LongType dimensionLength,
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void* reductionBuffer,
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const sd::LongType* tadOnlyShapeInfo) {
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functions::reduce::ReduceBoolFunction<X, Z>::template execScalarCuda<OpType>(
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x,
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xShapeInfo,
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extraParams,
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z,
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zShapeInfo,
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reductionBuffer,
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tadOnlyShapeInfo);
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}
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namespace functions {
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namespace reduce {
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template <typename X, typename Z>
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template <typename OpType>
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SD_DEVICE SD_INLINE void ReduceBoolFunction<X, Z>::aggregatePartials(
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void* vsPartials,
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sd::LongType tid,
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sd::LongType numItems,
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void* vextraParams) {
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auto sPartials = reinterpret_cast<Z*>(vsPartials);
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auto extraParams = reinterpret_cast<X*>(vextraParams);
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sd::LongType floorPow2 = numItems;
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if (floorPow2 & (floorPow2 - 1)) {
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while (floorPow2 & (floorPow2 - 1)) {
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floorPow2 &= (floorPow2 - 1);
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}
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if (tid >= floorPow2) {
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sPartials[tid - floorPow2] =
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OpType::update(sPartials[tid - floorPow2], sPartials[tid], extraParams);
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}
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__syncthreads();
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}
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for (sd::LongType activeThreads = (floorPow2 >> 1); activeThreads; activeThreads >>= 1) {
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if (tid < activeThreads && (tid + activeThreads) < numItems) {
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sPartials[tid] = OpType::update(sPartials[tid], sPartials[tid + activeThreads], extraParams);
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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 X, typename Z>
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template <typename OpType>
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SD_DEVICE SD_INLINE void ReduceBoolFunction<X, Z>::transformCuda(
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const void* vx,
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const sd::LongType* outerXTadShapeInfo,
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const sd::LongType* innerXTadShapeInfo,
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void* vreductionBuffer,
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void* vextraParams,
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void* vz,
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const sd::LongType* zShapeInfo) {
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auto x = reinterpret_cast<const X*>(vx);
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auto z = reinterpret_cast<Z*>(vz);
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auto extraParams = reinterpret_cast<X*>(vextraParams);
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__shared__ Z sPartials[SD_CUDA_BLOCK_SIZE];
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__shared__ int tadLen;
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__shared__ int numTads;
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__shared__ bool sameOffsets;
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// Cache shape info
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__shared__ sd::LongType outerRank;
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__shared__ sd::LongType innerRank;
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__shared__ sd::LongType zRank;
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__shared__ const sd::LongType* outerShapePtr;
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__shared__ const sd::LongType* outerStridePtr;
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__shared__ const sd::LongType* innerShapePtr;
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__shared__ const sd::LongType* innerStridePtr;
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__shared__ const sd::LongType* zShapePtr;
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__shared__ const sd::LongType* zStridePtr;
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if (threadIdx.x == 0) {
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outerRank = shape::rank(outerXTadShapeInfo);
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outerShapePtr = shape::shapeOf(outerXTadShapeInfo);
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outerStridePtr = shape::stride(outerXTadShapeInfo);
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innerRank = shape::rank(innerXTadShapeInfo);
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innerShapePtr = shape::shapeOf(innerXTadShapeInfo);
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innerStridePtr = shape::stride(innerXTadShapeInfo);
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zRank = shape::rank(zShapeInfo);
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zShapePtr = shape::shapeOf(zShapeInfo);
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zStridePtr = shape::stride(zShapeInfo);
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sameOffsets = shape::haveSameShapeAndStrides(zShapeInfo, outerXTadShapeInfo);
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tadLen = shape::length(innerXTadShapeInfo);
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numTads = shape::length(outerXTadShapeInfo);
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}
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__syncthreads();
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sd::LongType coords[SD_MAX_RANK];
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for (sd::LongType r = blockIdx.x; r < numTads; r += gridDim.x) {
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INDEX2COORDS(r, outerRank, outerShapePtr, coords);
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sd::LongType outerOffset;
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COORDS2INDEX(outerRank, outerStridePtr, coords, outerOffset);
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sd::LongType zOffset;
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if (sameOffsets) {
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zOffset = outerOffset;
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} else {
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INDEX2COORDS(r, zRank, zShapePtr, coords);
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COORDS2INDEX(zRank, zStridePtr, coords, zOffset);
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}
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const X* xTad = x + outerOffset;
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sPartials[threadIdx.x] = OpType::startingValue(xTad);
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for (sd::LongType i = threadIdx.x; i < tadLen; i += blockDim.x) {
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sd::LongType iCoords[SD_MAX_RANK];
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sd::LongType innerOffset;
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INDEX2COORDS(i, innerRank, innerShapePtr, iCoords);
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COORDS2INDEX(innerRank, innerStridePtr, iCoords, innerOffset);
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sPartials[threadIdx.x] = OpType::update(
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sPartials[threadIdx.x],
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OpType::op(xTad[innerOffset], extraParams),
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extraParams);
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}
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__syncthreads();
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aggregatePartials<OpType>(
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sPartials,
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threadIdx.x,
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sd::math::sd_min<int>(blockDim.x, tadLen),
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extraParams);
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__syncthreads();
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if (threadIdx.x == 0) {
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z[zOffset] = OpType::postProcess(sPartials[0], tadLen, extraParams);
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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 X, typename Z>
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template <typename OpType>
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SD_DEVICE SD_INLINE void ReduceBoolFunction<X, Z>::execScalarCuda(
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const void* vx,
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const sd::LongType* xShapeInfo,
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void* vextraParams,
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void* vz,
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const sd::LongType* zShapeInfo,
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void* vreductionBuffer,
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const sd::LongType* tadOnlyShapeInfo) {
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auto x = reinterpret_cast<const X*>(vx);
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auto z = reinterpret_cast<Z*>(vz);
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auto extraParams = reinterpret_cast<X*>(vextraParams);
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__shared__ Z sPartials[SD_CUDA_BLOCK_SIZE];
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__shared__ sd::LongType length;
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// Cache shape info
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__shared__ sd::LongType xRank;
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__shared__ const sd::LongType* xShapePtr;
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__shared__ const sd::LongType* xStridePtr;
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auto reductionBuffer = reinterpret_cast<Z *>(vreductionBuffer);
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int tid = blockDim.x * blockIdx.x + threadIdx.x;
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if (threadIdx.x == 0) {
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length = shape::length(xShapeInfo);
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xRank = shape::rank(xShapeInfo);
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xShapePtr = shape::shapeOf(xShapeInfo);
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xStridePtr = shape::stride(xShapeInfo);
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}
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__syncthreads();
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sPartials[threadIdx.x] = OpType::startingValue(x);
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sd::LongType gridSize = gridDim.x * blockDim.x;
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for (sd::LongType i = tid; i < length; i += gridSize) {
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sd::LongType xCoords[SD_MAX_RANK];
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sd::LongType xOffset;
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INDEX2COORDS(i, xRank, xShapePtr, xCoords);
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COORDS2INDEX(xRank, xStridePtr, xCoords, xOffset);
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sPartials[threadIdx.x] = OpType::update(
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sPartials[threadIdx.x],
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OpType::op(x[xOffset], extraParams),
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extraParams);
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}
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__syncthreads();
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aggregatePartials<OpType>(
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sPartials,
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threadIdx.x,
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sd::math::sd_min<int>(blockDim.x, length),
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extraParams);
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__syncthreads();
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if (gridDim.x > 1) {
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auto tc = reinterpret_cast<unsigned int*>(vreductionBuffer);
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__shared__ bool amLast;
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if (threadIdx.x == 0) {
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reductionBuffer[blockIdx.x] = sPartials[0];
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}
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__threadfence();
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__syncthreads();
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if (threadIdx.x == 0) {
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unsigned int ticket = atomicInc(&tc[16384], gridDim.x);
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amLast = (ticket == (gridDim.x - 1));
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}
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__syncthreads();
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if (amLast) {
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tc[16384] = 0;
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sPartials[threadIdx.x] = OpType::startingValue(x);
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for (sd::LongType i = threadIdx.x; i < gridDim.x; i += blockDim.x) {
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sPartials[threadIdx.x] = OpType::update(
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sPartials[threadIdx.x],
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reinterpret_cast<Z*>(vreductionBuffer)[i],
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extraParams);
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}
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__syncthreads();
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aggregatePartials<OpType>(
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sPartials,
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threadIdx.x,
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sd::math::sd_min<int>(gridDim.x, blockDim.x),
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extraParams);
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__syncthreads();
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if (threadIdx.x == 0) {
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z[0] = OpType::postProcess(sPartials[0], length, extraParams);
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}
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}
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} else {
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if (threadIdx.x == 0) {
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auto tc = reinterpret_cast<unsigned int*>(vreductionBuffer);
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tc[16384] = 0;
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z[0] = OpType::postProcess(sPartials[0], length, extraParams);
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}
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}
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Z>
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template <typename OpType>
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SD_HOST SD_INLINE void ReduceBoolFunction<X, Z>::intermediate(
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dim3 launchDims,
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cudaStream_t* stream,
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const void* x,
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sd::LongType* dXShapeInfo,
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sd::LongType* hXShapeInfo,
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void* extraParams,
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void* vreductionBuffer,
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void* z,
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sd::LongType* dZShapeInfo,
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sd::LongType* hZShapeInfo,
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sd::LongType* dims) {
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if (shape::isEmptyConst(hXShapeInfo)) {
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if (shape::isEmptyConst(hZShapeInfo)) return;
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const auto startingVal =
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static_cast<Z>(OpType::startingValue(reinterpret_cast<const X*>(x)));
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auto res = cudaMemcpyAsync(
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sd::LaunchContext::defaultContext()->getScalarPointer(),
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&startingVal,
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sizeof(Z),
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cudaMemcpyHostToDevice,
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*stream);
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if (res != 0) {
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throw sd::cuda_exception::build(
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"ReduceBoolFunction<X,Z>::intermediate: failed to copy temporary scalar", res);
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}
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auto ptr = sd::LaunchContext::defaultContext()->getScalarPointer();
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// scalar assign
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scalar::ScalarTransform<Z,Z,Z>::executeCudaShaped(
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launchDims,
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stream,
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14,
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z,
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dZShapeInfo,
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hZShapeInfo,
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z,
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dZShapeInfo,
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hZShapeInfo,
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ptr,
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nullptr);
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sd::DebugHelper::checkErrorCode(stream, "reduceBoolDim empty(...) failed");
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} else {
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const sd::LongType zRank = shape::rank(hZShapeInfo);
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const sd::LongType tadRank = shape::rank(hXShapeInfo) - zRank;
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auto outerPack = sd::ConstantShapeHelper::getInstance()
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.createSubArrShapeInfo(hXShapeInfo, dims, zRank);
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auto innerPack = sd::ConstantShapeHelper::getInstance()
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.createSubArrShapeInfo(hXShapeInfo, dims + zRank, tadRank);
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simpleReduce<X, Z, OpType>
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<<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(
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x,
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outerPack->special(),
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innerPack->special(),
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extraParams,
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vreductionBuffer,
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z,
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dZShapeInfo);
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sd::DebugHelper::checkErrorCode(stream, "reduceBoolDim(...) failed");
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}
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Z>
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template <typename OpType>
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SD_HOST SD_INLINE void ReduceBoolFunction<X, Z>::intermediateScalar(
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dim3 launchDims,
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cudaStream_t* stream,
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const void* x,
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const sd::LongType* xShapeInfo,
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const sd::LongType* hXShapeInfo,
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void* extraParams,
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void* z,
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const sd::LongType* zShapeInfo,
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const sd::LongType* hZShapeInfo,
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sd::LongType* dimension,
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sd::LongType dimensionLength,
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void* reductionBuffer,
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const sd::LongType* tadOnlyShapeInfo) {
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if (shape::isEmptyConst(hXShapeInfo)) {
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if (shape::isEmptyConst(hZShapeInfo)) return;
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const auto startingVal =
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static_cast<Z>(OpType::startingValue(reinterpret_cast<const X*>(x)));
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auto res = cudaMemcpyAsync(
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z,
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&startingVal,
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sizeof(Z),
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cudaMemcpyHostToDevice,
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*stream);
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if (res != 0) {
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throw sd::cuda_exception::build(
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"ReduceBoolFunction<X,Z>::intermediateScalar: failed to copy resulting scalar", res);
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}
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sd::DebugHelper::checkErrorCode(stream, "reduceBoolScalar empty(...) failed");
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} else {
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simpleScalar<X, Z, OpType>
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<<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(
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x,
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xShapeInfo,
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extraParams,
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z,
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zShapeInfo,
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dimension,
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dimensionLength,
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reductionBuffer,
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tadOnlyShapeInfo);
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sd::DebugHelper::checkErrorCode(stream, "reduceBoolScalar(...) failed");
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}
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Y>
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SD_HOST SD_INLINE void ReduceBoolFunction<X, Y>::execReduceScalar(
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dim3 launchDims,
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cudaStream_t* stream,
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const int opNum,
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const void* x,
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const sd::LongType* xShapeInfo,
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const sd::LongType* hXShapeInfo,
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void* extraParams,
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void* z,
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const sd::LongType* zShapeInfo,
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const sd::LongType* hZShapeInfo,
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sd::LongType* dimension,
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sd::LongType dimensionLength,
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void* reductionBuffer,
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const sd::LongType* tadOnlyShapeInfo) {
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DISPATCH_BY_OPNUM_TT(
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intermediateScalar,
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PARAMS(
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launchDims, stream, x, xShapeInfo, hXShapeInfo, extraParams, z,
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zShapeInfo, hZShapeInfo, dimension, dimensionLength, reductionBuffer, tadOnlyShapeInfo),
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OPS_A(REDUCE_BOOL_OPS));
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sd::DebugHelper::checkErrorCode(stream, "execReduceScalarFloat(...) failed");
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X, typename Y>
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SD_HOST SD_INLINE void ReduceBoolFunction<X, Y>::execReduce(
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dim3 launchDims,
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cudaStream_t* stream,
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const int opNum,
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const void* x,
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sd::LongType* dXShapeInfo,
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sd::LongType* hXShapeInfo,
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void* extraParams,
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void* vreductionBuffer,
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void* z,
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sd::LongType* dZShapeInfo,
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sd::LongType* hZShapeInfo,
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sd::LongType* dims) {
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if (shape::length(hZShapeInfo) == 1) {
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execReduceScalar(
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launchDims, stream, opNum,
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x, dXShapeInfo, hXShapeInfo,
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extraParams, z,
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dZShapeInfo, hZShapeInfo,
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nullptr, 0,
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vreductionBuffer,
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nullptr);
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} else {
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DISPATCH_BY_OPNUM_TT(
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intermediate,
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PARAMS(
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launchDims, stream, x, dXShapeInfo, hXShapeInfo, extraParams,
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vreductionBuffer, z, dZShapeInfo, hZShapeInfo, dims),
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OPS_A(REDUCE_BOOL_OPS));
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}
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DEBUG_KERNEL(stream, opNum);
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}
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////////////////////////////////////////////////////////////////////////
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template <typename X>
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SD_DEVICE void initializeShared(X* extraParams, X** sPartials, int sMemSize) {
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int sPartialsLength = sMemSize / sizeof(X);
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X* sPartialsDeref = reinterpret_cast<X*>(*sPartials);
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for (int i = 0; i < sPartialsLength; i++) {
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sPartialsDeref[i] = extraParams[0];
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}
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}
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ITERATE_COMBINATIONS(
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(SD_COMMON_TYPES),
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(SD_BOOL_TYPES),
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INSTANT_PROCESS_COMBINATION,
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functions::reduce::ReduceBoolFunction,
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::execReduce(
|
|
dim3 launchDims,
|
|
cudaStream_t* stream,
|
|
const int opNum,
|
|
const void* x,
|
|
sd::LongType* dXShapeInfo,
|
|
sd::LongType* hXShapeInfo,
|
|
void* extraParams,
|
|
void* vreductionBuffer,
|
|
void* z,
|
|
sd::LongType* dZShapeInfo,
|
|
sd::LongType* hZShapeInfo,
|
|
sd::LongType* dims);
|
|
);
|
|
|
|
ITERATE_COMBINATIONS(
|
|
(SD_COMMON_TYPES),
|
|
(SD_BOOL_TYPES),
|
|
INSTANT_PROCESS_COMBINATION,
|
|
functions::reduce::ReduceBoolFunction,
|
|
::execReduceScalar(
|
|
dim3 launchDims,
|
|
cudaStream_t* stream,
|
|
const int opNum,
|
|
const void* x,
|
|
const sd::LongType* xShapeInfo,
|
|
const sd::LongType* hXShapeInfo,
|
|
void* extraParams,
|
|
void* z,
|
|
const sd::LongType* zShapeInfo,
|
|
const sd::LongType* hZShapeInfo,
|
|
sd::LongType* dimension,
|
|
sd::LongType dimensionLength,
|
|
void* reductionBuffer,
|
|
const sd::LongType* tadOnlyShapeInfo);
|
|
);
|
|
|
|
|
|
} // namespace reduce
|
|
} // namespace functions
|