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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/helpers/cpu/im2col.cpp
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2026-07-13 12:47:05 +08:00

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/* ******************************************************************************
*
*
* 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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author Yurii Shyrma (iuriish@yahoo.com), created on 19.09.2018
//
#include <execution/Threads.h>
#include <ops/declarable/helpers/im2col.h>
#if NOT_EXCLUDED(OP_im2col)
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
template <typename T>
static void im2col_(sd::LaunchContext& context, NDArray& input, NDArray& output, const LongType kH,
const LongType kW, const LongType sH, const LongType sW, const LongType pH, const LongType pW,
const LongType dH, const LongType dW, NDArray& arrZeroPadVal) {
// input [bS, iC, iH, iW] is convoluted to output [bS, iC, kH, kW, oH, oW]
if(input.rankOf() != 4) {
THROW_EXCEPTION("ops::helpers::im2col: input array must have rank = 4");
}
if(output.rankOf() != 6) {
THROW_EXCEPTION("ops::helpers::im2col: output array must have rank = 6");
}
auto imBuff = static_cast<T const*>(input.buffer());
auto colBuff = static_cast<T*>(output.buffer());
auto imShapeBuffer = input.shapeInfo();
auto colShapeBuffer = output.shapeInfo();
auto colShape = shape::shapeOf(colShapeBuffer);
auto colStride = shape::stride(colShapeBuffer);
auto imShape = shape::shapeOf(imShapeBuffer);
auto imStride = shape::stride(imShapeBuffer);
const T zeroPadVal = arrZeroPadVal.e<T>(0);
const LongType bS = imShape[0];
const LongType iC = imShape[1];
const LongType iH = imShape[2];
const LongType iW = imShape[3];
const LongType oH = colShape[4];
const LongType oW = colShape[5];
const sd::LongType colStride0 = colStride[0];
const sd::LongType colStride1 = colStride[1];
const sd::LongType colStride2 = colStride[2];
const sd::LongType colStride3 = colStride[3];
const sd::LongType colStride4 = colStride[4];
const sd::LongType colStride5 = colStride[5];
const sd::LongType imStride0 = imStride[0];
const sd::LongType imStride1 = imStride[1];
const sd::LongType imStride2 = imStride[2];
const sd::LongType imStride3 = imStride[3];
auto func = PRAGMA_THREADS_FOR_2D {
sd::LongType imRow, imCol, colIndex, imIndex;
for (auto b = start_x; b < stop_x; b += inc_x) {
for (auto colH = start_y; colH < stop_y; colH += inc_y) {
for (sd::LongType colW = 0; colW < oW; ++colW) {
for (sd::LongType c = 0; c < iC; ++c) {
for (sd::LongType kRow = 0; kRow < kH; ++kRow) {
for (sd::LongType kCol = 0; kCol < kW; ++kCol) {
imRow = (-pH + kRow * dH) + colH * sH;
imCol = (-pW + kCol * dW) + colW * sW;
colIndex = b * colStride0 + c * colStride1 + kRow * colStride2 + kCol * colStride3 +
colH * colStride4 + colW * colStride5;
if (static_cast<LongType>(imRow) >= static_cast<LongType>(iH) ||
static_cast<LongType>(imRow) < 0 ||
static_cast<LongType>(imCol) >= static_cast<LongType>(iW) ||
static_cast<LongType>(imCol) < 0) {
if (colIndex < output.lengthOf()) {
colBuff[colIndex] = zeroPadVal;
}
} else {
imIndex = b * imStride0 + c * imStride1 + imRow * imStride2 + imCol * imStride3;
if (colIndex < output.lengthOf() && imIndex < input.lengthOf()) {
colBuff[colIndex] = static_cast<T>(imBuff[imIndex]);
}
}
}
}
}
}
}
}
};
samediff::Threads::parallel_for(func, 0, bS, 1, 0, oH, 1);
}
void im2col(sd::LaunchContext& context, NDArray& im, NDArray& col, const LongType kH, const LongType kW,
const LongType sH, const LongType sW, const LongType pH, const LongType pW, const LongType dH,
const LongType dW, NDArray& arrZeroPadVal) {
BUILD_SINGLE_SELECTOR(im.dataType(), im2col_, (context, im, col, kH, kW, sH, sW, pH, pW, dH, dW, arrZeroPadVal),
SD_FLOAT_TYPES);
}
} // namespace helpers
} // namespace ops
} // namespace sd
#endif