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