cavis/libnd4j/include/loops/scalar.h

127 lines
5.0 KiB
C++
Executable File

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
/*
* scalar.h
*
* Created on: Dec 28, 2015
* Author: agibsonccc
*/
#ifndef SCALAR_H_
#define SCALAR_H_
#include <OmpLaunchHelper.h>
#include <dll.h>
#include <helpers/DebugHelper.h>
#ifdef __JNI__
#include <jni.h>
#endif
#include <templatemath.h>
#include <ops/ops.h>
#include <op_boilerplate.h>
#include "helpers/logger.h"
#ifdef __CUDACC__
#include <cuda.h>
#include <cuda_runtime.h>
#include <types/float16.h>
#endif
#include "legacy_ops.h"
namespace functions {
namespace scalar {
/**
* Apply a scalar
* operation to an array
*/
template<typename X, typename Y, typename Z>
class ScalarTransform {
public:
#ifdef __CUDACC__
template <typename OpType>
__host__
static void intermediateShaped(dim3& launchDims, cudaStream_t *stream, void *vx, Nd4jLong *xShapeInfo, Nd4jLong *hxShapeInfo, void *vz, Nd4jLong *zShapeInfo, Nd4jLong *hzShapeInfo, void* vscalar, void *vextraParams, int *allocPointer);
template <typename OpType>
__host__
static void intermediateAlongDimension(dim3& launchDims, cudaStream_t *stream, void *x, Nd4jLong *xShapeInfo, void *z, Nd4jLong *zShapeInfo, void *scalars, void *extraParams, int *dimension, int dimensionLength, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadShapeInfoZ, Nd4jLong *tadOffsetsZ);
__host__
static void executeCudaShaped(dim3& launchDims, cudaStream_t *stream, int opNum, void *x, Nd4jLong *xShapeInfo, Nd4jLong *hxShapeInfo, void *result, Nd4jLong *resultShapeInfo, Nd4jLong *hzShapeInfo, void* scalar, void *extraParams);
__host__
static void executeCudaAlongDimension(dim3& launchDims, cudaStream_t *stream, int opNum, void *x, Nd4jLong *xShapeInfo, void *z, Nd4jLong *zShapeInfo, void *scalars, void *extraParams, int *dimension, int dimensionLength, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadShapeInfoZ, Nd4jLong *tadOffsetsZ);
#endif
template <typename OpType>
static void transform(void *x, Nd4jLong *xShapeInfo, void *extraParams, void *z, Nd4jLong *zShapeInfo, void *scalars, int *dimension, int dimensionLength, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadShapeInfoZ, Nd4jLong *tadOffsetsZ);
static void transform(int opNum, void *x, Nd4jLong *xShapeInfo, void *extraParams, void *z, Nd4jLong *zShapeInfo, void *scalars, int *dimension, int dimensionLength, Nd4jLong *tadShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadShapeInfoZ, Nd4jLong *tadOffsetsZ);
static void transform(const int opNum, void *x, Nd4jLong *xShapeInfo, void *result, Nd4jLong *resultShapeInfo, void *scalar, void *extraParams);
static void transform(const int opNum, void *x, Nd4jLong xStride, void *result, Nd4jLong resultStride, void *scalar, void *extraParams, const Nd4jLong len);
/*
* ScalarOp along dimension
*/
/**
* CPU implementation of scalar operation
* @param x the input
* @param xStride the stride for the input
* @param result the result buffer
* @param resultStride the stride for the result
* @param scalar the scalar to apply
* @param extraParams the extra parameters where
* neccssary
* @param len the number of elements to loop over
*/
template<typename OpType>
static void transform(void *x, Nd4jLong *xShapeInfo, void *result, Nd4jLong *resultShapeInfo, void *scalar, void *extraParams);
/**
* CPU implementation of scalar operation
* @param x the input
* @param xStride the stride for the input
* @param result the result buffer
* @param resultStride the stride for the result
* @param scalar the scalar to apply
* @param extraParams the extra parameters where
* neccssary
* @param len the number of elements to loop over
*/
template<typename OpType>
static void transform(void *x, Nd4jLong xStride, void *result, Nd4jLong resultStride, void *scalar, void *extraParams, const Nd4jLong len);
};
}
}
#endif /* SCALAR_H_ */