cavis/libnd4j/include/loops/cuda/specials/concatKernelHStack.cu

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/*******************************************************************************
* 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
******************************************************************************/
//
// @author raver119@gmail.com
// @author Yurii Shyrma, created on 15.11.2018
//
#include <loops/special_kernels.h>
namespace sd {
///////////////////////////////////////////////////////////////////////
template<typename T>
__device__ void concatKernelHStack(int numArrays,
Nd4jPointer *data, Nd4jPointer *inputShapeInfos,
void *vz, Nd4jLong *zShapeInfo) {
// we expect all data coming in as vectors, and z as 2D matrix
// the only significant difference here is the fact that input lengths might be different
auto z = reinterpret_cast<T *>(vz);
auto inputShapes = (Nd4jLong **) inputShapeInfos;
T **input = (T **) data;
__shared__ int inputEWS;
__shared__ int resultEWS;
__shared__ int inputLength;
if (threadIdx.x == 0) {
resultEWS = shape::elementWiseStride(zShapeInfo);
}
__syncthreads();
for (int r = blockIdx.x; r < numArrays; r += gridDim.x) {
__shared__ int baseIdx;
if (threadIdx.x == 0) {
baseIdx = 0;
for (int f = 0; f < r; f++) {
baseIdx += shape::length(inputShapes[f]);
}
}
__syncthreads();
T *inputData = (T *) input[r];
if (threadIdx.x == 0) {
inputEWS = shape::elementWiseStride(inputShapes[r]);
inputLength = shape::length(inputShapes[r]);
}
__syncthreads();
for (int i = threadIdx.x; i < inputLength; i += blockDim.x) {
z[baseIdx + i * resultEWS] = inputData[i * inputEWS];
}
__syncthreads();
}
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__global__ void execConcatKernelHStack(int numArrays,
Nd4jPointer *data, Nd4jPointer *inputShapeInfos,
void *vz, Nd4jLong *zShapeInfo) {
concatKernelHStack<T>(numArrays, data, inputShapeInfos, vz, zShapeInfo);
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__host__ void concatKernelHStackGeneric(dim3 &launchDims, cudaStream_t *stream,
int numArrays,
Nd4jPointer *data, Nd4jPointer *inputShapeInfos,
void *vz, Nd4jLong *zShapeInfo) {
execConcatKernelHStack<T><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(numArrays, data, inputShapeInfos, vz, zShapeInfo);
sd::DebugHelper::checkErrorCode(stream, "concatHStack(...) failed");
}
BUILD_SINGLE_TEMPLATE(template void ND4J_EXPORT concatKernelHStackGeneric, (dim3 & launchDims, cudaStream_t * stream, int numArrays, Nd4jPointer * data, Nd4jPointer * inputShapeInfos, void * vz, Nd4jLong * zShapeInfo), LIBND4J_TYPES);
}