/* ******************************************************************************
*
*
* 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.
*
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership.
* 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.
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* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author Yurii Shyrma (iuriish@yahoo.com), created on 18.09.2018
//
#include <ops/declarable/helpers/convolutions.h>
#include <execution/Threads.h>
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
// [bS, iC, iD, iH, iW] is convoluted to [bS, iC, kD, kH, kW, oD, oH, oW]
template <typename T>
static void vol2col_(const NDArray& volume, NDArray& columns, const int sD, const int sH, const int sW, const int pD, const int pH, const int pW, const int dD, const int dH, const int dW) {
const int bS = volume.sizeAt(0);
const int iC = volume.sizeAt(1);
const int iD = volume.sizeAt(2);
const int iH = volume.sizeAt(3);
const int iW = volume.sizeAt(4);
const int kD = columns.sizeAt(2);
const int kH = columns.sizeAt(3);
const int kW = columns.sizeAt(4);
const int oD = columns.sizeAt(5);
const int oH = columns.sizeAt(6);
const int oW = columns.sizeAt(7);
const Nd4jLong colStride0 = columns.stridesOf()[0];
const Nd4jLong colStride1 = columns.stridesOf()[1];
const Nd4jLong colStride2 = columns.stridesOf()[2];
const Nd4jLong colStride3 = columns.stridesOf()[3];
const Nd4jLong colStride4 = columns.stridesOf()[4];
const Nd4jLong colStride5 = columns.stridesOf()[5];
const Nd4jLong colStride6 = columns.stridesOf()[6];
const Nd4jLong colStride7 = columns.stridesOf()[7];
const Nd4jLong volStride0 = volume.stridesOf()[0];
const Nd4jLong volStride1 = volume.stridesOf()[1];
const Nd4jLong volStride2 = volume.stridesOf()[2];
const Nd4jLong volStride3 = volume.stridesOf()[3];
const Nd4jLong volStride4 = volume.stridesOf()[4];
T* colBuff = columns.bufferAsT<T>();
T* volBuff = const_cast<NDArray&>(volume).bufferAsT<T>();
if (volume.ordering() == 'c' && columns.ordering() == 'c' && shape::strideDescendingCAscendingF(volume.shapeInfo()) && shape::strideDescendingCAscendingF(columns.shapeInfo())) {
auto func = PRAGMA_THREADS_FOR_3D {
T *col, *vol;
int volDep, volRow, volCol;
for (int b = start_x; b < stop_x; b += inc_x) {
for (int c = start_y; c < stop_y; c += inc_y) {
for (int kDep = start_z; kDep < stop_z; kDep += inc_z) {
for (int kRow = 0; kRow < kH; ++kRow) {
for (int kCol = 0; kCol < kW; ++kCol) {
for (int colD = 0; colD < oD; ++colD) {
for (int colH = 0; colH < oH; ++colH) {
for (int colW = 0; colW < oW; ++colW) {
volDep = (-pD + kDep * dD) + colD * sD;
volRow = (-pH + kRow * dH) + colH * sH;
volCol = (-pW + kCol * dW) + colW * sW;
col = colBuff + b * colStride0 + c * colStride1 + kDep * colStride2 + kRow * colStride3 + kCol * colStride4 + colD * colStride5 + colH * colStride6 + colW * colStride7;
if (static_cast<unsigned>(volDep) >= static_cast<unsigned>(iD) || static_cast<unsigned>(volRow) >= static_cast<unsigned>(iH) || static_cast<unsigned>(volCol) >= static_cast<unsigned>(iW))
*col = static_cast<T>(0.);
else {
vol = volBuff + b * volStride0 + c * volStride1 + volDep * volStride2 + volRow * volStride3 + volCol * volStride4;
*col = *vol;
}
}
}
}
}
}
}
}
}
};
samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1, 0, kD, 1);
} else {
auto func = PRAGMA_THREADS_FOR_2D {
T *col, *vol;
int volDep, volRow, volCol;
for (int b = start_x; b < stop_x; b++) {
for (int colD = start_y; colD < stop_y; colD++) {
for (int colH = 0; colH < oH; ++colH) {
for (int colW = 0; colW < oW; ++colW) {
for (int c = 0; c < iC; ++c) {
for (int kDep = 0; kDep < kD; ++kDep) {
for (int kRow = 0; kRow < kH; ++kRow) {
for (int kCol = 0; kCol < kW; ++kCol) {
volDep = (-pD + kDep * dD) + colD * sD;
volRow = (-pH + kRow * dH) + colH * sH;
volCol = (-pW + kCol * dW) + colW * sW;
col = colBuff + b * colStride0 + c * colStride1 + kDep * colStride2 + kRow * colStride3 + kCol * colStride4 + colD * colStride5 + colH * colStride6 + colW * colStride7;
if (static_cast<unsigned>(volDep) >= static_cast<unsigned>(iD) || static_cast<unsigned>(volRow) >= static_cast<unsigned>(iH) || static_cast<unsigned>(volCol) >= static_cast<unsigned>(iW))
*col = static_cast<T>(0.f);
else {
vol = volBuff + b * volStride0 + c * volStride1 + volDep * volStride2 + volRow * volStride3 + volCol * volStride4;
*col = *vol;
}
}
}
}
}
}
}
}
}
};
samediff::Threads::parallel_for(func, 0, bS, 1, 0, oD, 1);
//func(0, 0, bS, 1, 0, oD, 1);
}
}
void ConvolutionUtils::vol2col(sd::graph::Context& block, const NDArray& volume, NDArray& columns, const int sD, const int sH, const int sW, const int pD, const int pH, const int pW, const int dD, const int dH, const int dW) {
BUILD_SINGLE_SELECTOR(volume.dataType(), vol2col_, (volume, columns, sD, sH, sW, pD, pH, pW, dD, dH, dW), FLOAT_TYPES);
}
}
}