124 lines
4.9 KiB
Plaintext
124 lines
4.9 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 raver119@gmail.com
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//
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#include <Environment.h>
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#include <loops/transform_same.h>
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#include <types/types.h>
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#include <op_boilerplate.h>
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#include <loops/legacy_ops.h>
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#include <helpers/DebugHelper.h>
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using namespace simdOps;
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template <typename X, typename OpType>
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__global__ void transformSameSimple(void *x, Nd4jLong *xShapeInfo, int xRank,
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void *params,
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void *z, Nd4jLong *zShapeInfo, int zRank,
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int *allocationPointer,
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void *reductionPointer,
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Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets) {
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functions::transform::TransformSame<X>::template transformCuda<OpType>(x,xShapeInfo,params,z,zShapeInfo,allocationPointer,reductionPointer, tadShapeInfo, tadOffsets);
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}
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namespace functions {
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namespace transform {
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template<typename X>
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_CUDA_H void TransformSame<X>::executeTransformShaped(dim3 launchDims, cudaStream_t *stream, int opNum, void *x, Nd4jLong *xShape, int xRank, void *extraParams, void *z, Nd4jLong *zShape, int zRank, int *allocationPointer, void *reductionPointer, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets) {
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DISPATCH_BY_OPNUM_T(intermediateShaped, PARAMS(launchDims, stream, x, xShape, xRank, extraParams, z, zShape, zRank, allocationPointer, reductionPointer, tadShapeInfo, tadOffsets), TRANSFORM_SAME_OPS);
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DEBUG_KERNEL(stream, opNum);
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}
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template<typename X>
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template <typename OpType>
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__device__ void TransformSame<X>::transformCuda(void *vx, Nd4jLong *xShapeInfo,
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void *vparams,
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void *vz, Nd4jLong *zShapeInfo,
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int *allocationPointer, void *vreductionPointer,
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Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets) {
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auto x = static_cast<X*>(vx);
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auto z = static_cast<X*>(vz);
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auto params = static_cast<X*>(vparams);
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auto reductionPointer = static_cast<X*>(vreductionPointer);
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if(OpType::requiresSpecial) {
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OpType::execSpecialCuda(x,xShapeInfo,z,zShapeInfo,params, allocationPointer, reductionPointer, tadShapeInfo, tadOffsets);
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return;
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} else {
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__shared__ Nd4jLong xEws;
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__shared__ Nd4jLong zEws;
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__shared__ char xOrder;
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__shared__ char zOrder;
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__shared__ Nd4jLong length;
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if (threadIdx.x == 0) {
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xEws = shape::elementWiseStride(xShapeInfo);
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zEws = shape::elementWiseStride(zShapeInfo);
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xOrder = shape::order(xShapeInfo);
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zOrder = shape::order(zShapeInfo);
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length = shape::length(xShapeInfo);
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}
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__syncthreads();
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auto tid = blockIdx.x * blockDim.x + threadIdx.x;
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int totalThreads = gridDim.x * blockDim.x;
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if(xEws > 0 && zEws > 0 && xOrder == zOrder) {
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for (int i = tid; i < length; i += totalThreads)
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z[i * zEws] = OpType::op(x[i * xEws], params);
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}
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else {
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if(vx == vz) {
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for (Nd4jLong i = tid; i < length; i+= gridDim.x * blockDim.x) {
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auto xOffset = shape::getIndexOffset(i, xShapeInfo, length);
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z[xOffset] = OpType::op(x[xOffset], params);
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}
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}
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else {
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for (Nd4jLong i = tid; i < length; i+= gridDim.x * blockDim.x) {
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auto xOffset = shape::getIndexOffset(i, xShapeInfo, length);
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auto zOffset = shape::getIndexOffset(i, zShapeInfo, length);
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z[zOffset] = OpType::op(x[xOffset], params);
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}
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}
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}
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}
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};
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template<typename X>
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template <typename OpType>
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_CUDA_H void TransformSame<X>::intermediateShaped(dim3 launchDims, cudaStream_t *stream, void *x, Nd4jLong *xShape, int xRank, void *extraParams, void *z, Nd4jLong *zShape, int zRank, int *allocationPointer, void *reductionPointer, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets) {
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transformSameSimple<X, OpType><<<launchDims.x, launchDims.x, launchDims.z, *stream>>>(x, xShape, xRank, extraParams, z, zShape, zRank, allocationPointer, reductionPointer, tadShapeInfo, tadOffsets);
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nd4j::DebugHelper::checkErrorCode(stream, "transformSame(...) failed");
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}
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BUILD_SINGLE_TEMPLATE(template class ND4J_EXPORT TransformSame, , LIBND4J_TYPES);
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}
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}
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