182 lines
7.3 KiB
C++
182 lines
7.3 KiB
C++
/*******************************************************************************
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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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#ifndef REDUCE_SAME_H
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#define REDUCE_SAME_H
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#include <system/dll.h>
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//#include <string>
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#include <stdio.h>
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#include <helpers/shape.h>
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#include <math/templatemath.h>
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#include <system/nd4jmalloc.h>
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#include <system/pairwise_util.h>
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#include <ops/ops.h>
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#include <system/op_boilerplate.h>
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#include <memory/Workspace.h>
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#pragma once
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#ifdef __CUDACC__
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#include <cuda.h>
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#include <cuda_runtime.h>
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#endif
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#include "legacy_ops.h"
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//an op for the kernel
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namespace functions {
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namespace reduce {
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/**
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* A reduce function
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* reduces a vector down to
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* a subset of itself
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* via aggregating member
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* elements.
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*/
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template<typename X>
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class ReduceSameFunction {
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public:
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#ifdef __CUDACC__
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template<typename OpType>
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static __device__ void aggregatePartials(void *sPartials, Nd4jLong tid, Nd4jLong numItems, void *extraParams);
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template<typename OpType>
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static __device__ void execScalarCuda( void const* vx, Nd4jLong const *xShapeInfo, void *extraParams, void *vz, Nd4jLong const* zShapeInfo, void *reductionBuffer, Nd4jLong const* tadOnlyShapeInfo);
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static __device__ void execScalarCudaLegacy(int opNum, void const* vx, Nd4jLong const* xShapeInfo, void *extraParams, void *vz, Nd4jLong const* zShapeInfo, void *reductionBuffer, Nd4jLong const* tadOnlyShapeInfo);
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template<typename OpType>
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static __device__ void transformCudaXD(const void *vx, const Nd4jLong *outerXTadShapeInfo, const Nd4jLong *innerXTadShapeInfo, void *extraParams, void* reductionBuffer, void *vz, const Nd4jLong *zShapeInfo);
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template<typename OpType>
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static __host__ void intermediateScalar(dim3 launchDims, cudaStream_t *stream, void const* vx, Nd4jLong const* xShapeInfo, Nd4jLong const* hXShapeInfo, void *extraParams, void *vz, Nd4jLong const* zShapeInfo, Nd4jLong const* hZShapeInfo, int *dimension, int dimensionLength, void *reductionBuffer, Nd4jLong const* tadOnlyShapeInfo);
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template<typename OpType>
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static __host__ void intermediateXD(dim3 launchDims, cudaStream_t *stream, const void *vx, const Nd4jLong *dXShapeInfo, const Nd4jLong *hXShapeInfo, void *extraParams, void* reductionBuffer, void *vz, const Nd4jLong *dZShapeInfo, const Nd4jLong *hZShapeInfo, const int* dims);
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static __host__ void execReduceScalar(dim3 launchDims, cudaStream_t *stream, int opNum, void const* vx, Nd4jLong const* xShapeInfo, Nd4jLong const* hXShapeInfo, void *extraParams, void *vz, Nd4jLong const* zShapeInfo, Nd4jLong const* hZShapeInfo, int *dimension, int dimensionLength, void *reductionBuffer, Nd4jLong const* tadOnlyShapeInfo);
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static __host__ void execReduceXD(dim3 launchDims, cudaStream_t *stream, int opNum, const void *vx, const Nd4jLong *dXShapeInfo, const Nd4jLong *hXShapeInfo, void *extraParams, void* reductionBuffer, void *vz, const Nd4jLong *dZShapeInfo, const Nd4jLong *hZShapeInfo, const int *dims);
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#else
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/**
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* Reduce down to 1 number
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* @param x the input
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* @param xShapeInfo the shape information
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* for the input
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* @param extraParams the extra params
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* @return
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*/
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template<typename OpType>
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static _CUDA_H X execScalar(const void *x, const Nd4jLong *xShapeInfo,
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void *extraParams);
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template<typename OpType>
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static _CUDA_H void execScalar(const void *x, const Nd4jLong *xShapeInfo,
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void *extraParams,
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void *z, const Nd4jLong *zShapeInfo);
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static X execScalar(int opNum,
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const void *x, const Nd4jLong *xShapeInfo,
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void *extraParams);
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static void execScalar(int opNum,
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const void *x, const Nd4jLong *xShapeInfo,
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void *extraParams,
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void *z, const Nd4jLong *zShapeInfo);
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static void exec(int opNum, sd::memory::Workspace* workspace,
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const void *vx, const Nd4jLong *xShapeInfo,
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void *vextraParams,
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void *vz, const Nd4jLong *zShapeInfo,
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const int *dims);
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/**
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* Execute on the cpu
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* @param x the input data
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* @param xShapeInfo the shape information for x
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* @param extraParams the extra parameters
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* @param result the result buffer
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* @param resultShapeInfoBuffer the shape information
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* @param dimension the dimension to perform
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* the reduce along long
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* @param dimensionLength the length of the dimension buffer
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*/
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template<typename OpType>
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static void _CUDA_H exec(sd::memory::Workspace* workspace,
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const void *vx, const Nd4jLong *xShapeInfo,
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void *vextraParams,
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void *vz, const Nd4jLong *zShapeInfo,
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const int *dims);
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/**
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* CPU implementation
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* @param x the input data
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* @param xShapeInfo the shape information for
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* the input data
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* @param extraParams the extra parameters for the problem
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* @param result the result buffer
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* @param resultShapeInfo the shape information
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*/
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template<typename OpType>
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static void _CUDA_H exec(const void *x, const Nd4jLong *xShapeInfo,
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void *extraParams,
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void *result, const Nd4jLong *resultShapeInfo);
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/**
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* Reduce down to 1 number
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* @param x the input
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* @param xShapeInfo the shape information
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* for the input
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* @param extraParams the extra params
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* @return
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*/
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template<typename OpType>
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static X _CUDA_H execScalar(const void *x, Nd4jLong xElementWiseStride,
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Nd4jLong length,
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void *extraParams);
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#endif
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};
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#ifdef __CUDACC__
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/**
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*
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* @param extraParams
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* @param sPartials
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* @param sMemSize
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*/
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template<typename T>
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__device__ void initializeShared(T *extraParams, T **sPartials, int sMemSize);
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#endif
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}
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}
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#endif
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