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