cavis/libnd4j/include/ops/declarable/helpers/cuda/dilation2d.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 Yurii Shyrma (iuriish@yahoo.com)
//
#include <ops/declarable/helpers/dilation2d.h>
#include <array/DataTypeUtils.h>
#include <PointersManager.h>
namespace nd4j {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
template <typename X, typename Z>
__global__ static void dilation2dCuda(const void* vx, const Nd4jLong* xShapeInfo,
const void* vy, const Nd4jLong* yShapeInfo,
void* vz, const Nd4jLong* zShapeInfo,
const int sH, const int sW,
const int pH, const int pW,
const int dH, const int dW) {
// x [bS, iH, iW, iC]
// y [kH, kW, iC]
// z [bS, oH, oW, iC]
const X* x = reinterpret_cast<const X*>(vx);
const X* y = reinterpret_cast<const X*>(vy);
Z* z = reinterpret_cast<Z*>(vz);
__shared__ int xzRank, yRank;
__shared__ uint iH, iW, kH, kW;
__shared__ Nd4jLong *sharedMem, zLen;
if (threadIdx.x == 0) {
extern __shared__ unsigned char shmem[];
sharedMem = reinterpret_cast<Nd4jLong*>(shmem);
zLen = shape::length(zShapeInfo);
xzRank = shape::rank(xShapeInfo);
yRank = shape::rank(yShapeInfo);
iH = xShapeInfo[2];
iW = xShapeInfo[3];
kH = yShapeInfo[1];
kW = yShapeInfo[2];
}
__syncthreads();
const auto zInd = threadIdx.x + blockIdx.x * blockDim.x;
if(zInd >= zLen)
return;
auto xzCoords = sharedMem + threadIdx.x * (xzRank + yRank);
auto yCoords = xzCoords + xzRank;
shape::index2coords(zInd, zShapeInfo, xzCoords);
const auto zOffset = shape::getOffset(zShapeInfo, xzCoords);
yCoords[2] = xzCoords[3]; // iC coordinate is same for x, y and z
const auto oh = xzCoords[1];
const auto ow = xzCoords[2];
X max = -DataTypeUtils::max<X>();
for (yCoords[0] = 0; yCoords[0] < kH; ++yCoords[0]) {
xzCoords[1] = oh * sH - pH + yCoords[0] * dH;
if (xzCoords[1] < 0 || xzCoords[1] >= iH) continue;
for (yCoords[1] = 0; yCoords[1] < kW; ++yCoords[1]) {
xzCoords[2] = ow * sW - pW + yCoords[1] * dW;
if(xzCoords[2] < 0 || xzCoords[2] >= iW) continue;
const X val = x[shape::getOffset(xShapeInfo, xzCoords)] + y[shape::getOffset(yShapeInfo, yCoords)];
if (val > max)
max = val;
}
}
z[zOffset] = static_cast<Z>(max);
}
//////////////////////////////////////////////////////////////////////////
template <typename X, typename Z>
static void dilation2dCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem, const cudaStream_t *stream,
const void* vx, const Nd4jLong* xShapeInfo,
const void* vy, const Nd4jLong* yShapeInfo,
void* vz, const Nd4jLong* zShapeInfo,
const int sH, const int sW,
const int pH, const int pW,
const int dH, const int dW) {
dilation2dCuda<X,Z><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vy, yShapeInfo, vz, zShapeInfo, sH, sW, pH, pW, dH, dW);
}
void dilation2d(nd4j::LaunchContext* context, NDArray *input, NDArray *weights, NDArray *output, const int sH, const int sW, const int pH, const int pW, const int dH, const int dW) {
PointersManager manager(context, "dilation2d");
const int threadsPerBlock = MAX_NUM_THREADS / 2;
const int blocksPerGrid = (output->lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
const int sharedMem = (weights->rankOf() + output->rankOf()) * sizeof(Nd4jLong) * threadsPerBlock + 128;
NDArray::prepareSpecialUse({output}, {input, weights});
BUILD_SINGLE_SELECTOR_TWICE(input->dataType(), dilation2dCudaLauncher, (blocksPerGrid, threadsPerBlock, sharedMem, context->getCudaStream(), input->getSpecialBuffer(), input->getSpecialShapeInfo(), weights->getSpecialBuffer(), weights->getSpecialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), sH, sW, pH, pW, dH, dW), FLOAT_TYPES);
NDArray::registerSpecialUse({output}, {input, weights});
manager.synchronize();
}
}
}
}