200 lines
8.5 KiB
C++
200 lines
8.5 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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/*
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* broadcasting.h
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*
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* Created on: Dec 28, 2015
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* Author: agibsonccc
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*/
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#ifndef BROADCASTING_INT_H_
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#define BROADCASTING_INT_H_
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#include <system/dll.h>
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#include <helpers/shape.h>
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#include <math/templatemath.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 <helpers/DebugHelper.h>
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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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#ifdef __JNI__
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#include <jni.h>
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#endif
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#include <helpers/TAD.h>
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#include "legacy_ops.h"
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namespace functions {
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namespace broadcast {
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/**
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* Broadcast operation
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* for broadcasting a smaller tensor
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* along long a bigger one.
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*/
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template<typename X>
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class BroadcastInt {
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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 transformCuda(
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void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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template<typename OpType>
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static __device__ void transformCuda(const void *x, const Nd4jLong *xShapeInfo,
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const void *y, const Nd4jLong *yShapeInfo,
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void *z, const Nd4jLong *zShapeInfo);
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template <typename OpClass>
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static __host__ void intermediateBroadcast(dim3 launchDims, cudaStream_t *stream, void *x, Nd4jLong *xShapeInfo, void *y, Nd4jLong *yShapeInfo, void *result, Nd4jLong *resultShapeInfo, int *dimension, int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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template <typename OpClass>
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static __host__ void intermediateBroadcast(dim3 launchDims, cudaStream_t *stream,
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const void *x, const Nd4jLong *xShapeInfo,
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const void *y, const Nd4jLong *yShapeInfo,
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void *z, const Nd4jLong *zShapeInfo);
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static __host__ void execBroadcast(dim3 launchDims, cudaStream_t *stream, int opNum, void *x, Nd4jLong *xShapeInfo, void *y, Nd4jLong *yShapeInfo, void *result, Nd4jLong *resultShapeInfo, int *dimension, int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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static __host__ void execBroadcast(dim3 launchDims, cudaStream_t *stream, const int opNum,
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const void *x, const Nd4jLong *xShapeInfo,
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const void *y, const Nd4jLong *yShapeInfo,
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void *z, const Nd4jLong *zShapeInfo);
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template<typename OpType>
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static __device__ void transformInverseCuda(
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void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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template <typename OpClass>
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static __host__ void intermediateInverseBroadcast(dim3 launchDims, cudaStream_t *stream, void *x, Nd4jLong *xShapeInfo, void *y, Nd4jLong *yShapeInfo, void *result, Nd4jLong *resultShapeInfo, int *dimension, int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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static __host__ void execInverseBroadcast(dim3 launchDims, cudaStream_t *stream, int opNum, void *x, Nd4jLong *xShapeInfo, void *y, Nd4jLong *yShapeInfo, void *result, Nd4jLong *resultShapeInfo, int *dimension, int dimensionLength, Nd4jLong *tadOnlyShapeInfo, Nd4jLong *tadOffsets, Nd4jLong *tadOnlyShapeInfoZ, Nd4jLong *tadOffsetsZ);
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#else
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static void exec(int opNum,
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void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength,
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Nd4jLong *tadShapeInfo,
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Nd4jLong *tadOffset,
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Nd4jLong *tadShapeInfoZ,
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Nd4jLong *tadOffsetZ,
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uint64_t start,
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uint64_t stop);
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static void exec(const int opNum,
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const void *x, const Nd4jLong *xShapeInfo,
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const void *y, const Nd4jLong *yShapeInfo,
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void *z, const Nd4jLong *zShapeInfo);
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static void execInverse(int opNum,
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void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength,
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Nd4jLong *tadShapeInfo,
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Nd4jLong *tadOffset,
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Nd4jLong *tadShapeInfoZ,
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Nd4jLong *tadOffsetZ,
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uint64_t start,
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uint64_t stop);
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/**
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* CPU execution
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* @param x the input
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* @param xShapeInfo the x shape information
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* @param y the y data
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* @param yShapeInfo the y shape information
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* @param result the result
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* @param resultShapeInfo the result shape information
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* @param dimension the dimension to broadcast 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 exec(void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength,
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Nd4jLong *tadShapeInfo,
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Nd4jLong *tadOffset,
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Nd4jLong *tadShapeInfoZ,
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Nd4jLong *tadOffsetZ,
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uint64_t start,
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uint64_t stop);
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template<typename OpType>
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static void exec(const void *x, const Nd4jLong *xShapeInfo,
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const void *y, const Nd4jLong *yShapeInfo,
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void *z, const Nd4jLong *zShapeInfo);
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template<typename OpType>
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static void execInverse(void *x,
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Nd4jLong *xShapeInfo,
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void *y,
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Nd4jLong *yShapeInfo,
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void *result,
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Nd4jLong *resultShapeInfo,
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int *dimension,
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int dimensionLength,
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Nd4jLong *tadShapeInfo,
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Nd4jLong *tadOffset,
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Nd4jLong *tadShapeInfoZ,
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Nd4jLong *tadOffsetZ,
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uint64_t start,
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uint64_t stop);
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#endif
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};
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}
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}
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#endif /* BROADCASTING_H_ */
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