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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/helpers/cpu/matrixSetDiag.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)
//
#include <array/ResultSet.h>
#include <execution/Threads.h>
#include <ops/declarable/helpers/matrixSetDiag.h>
#if NOT_EXCLUDED(OP_matrix_set_diag)
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
template <typename T>
void matrixSetDiag_(NDArray& input, NDArray& diagonal, NDArray& output, const bool zeroPad) {
// input and output are the same array (x == z) when zeroPad = true
// xRank = zRank, xRank = yRank + 1
// xLen = zLen
const T* x = input.bufferAsT<T>();
const T* y = diagonal.bufferAsT<T>();
T* z = output.bufferAsT<T>();
// Cache all shape information upfront
const sd::LongType* xShapeInfo = input.shapeInfo();
const sd::LongType* yShapeInfo = diagonal.shapeInfo();
const sd::LongType* zShapeInfo = output.shapeInfo();
// Cache shape-related values
const int xRank = input.rankOf();
const auto xLen = input.lengthOf();
// Cache shape and stride pointers
const sd::LongType* xShape = shape::shapeOf(xShapeInfo);
const sd::LongType* xStride = shape::stride(xShapeInfo);
const sd::LongType* yStride = shape::stride(yShapeInfo);
const sd::LongType* zStride = shape::stride(zShapeInfo);
// Check if input and output have same offsets
const bool areSameOffsets = shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo);
auto func = PRAGMA_THREADS_FOR {
// Pre-allocate coords array outside the loop
sd::LongType coords[SD_MAX_RANK];
for (sd::LongType i = 0; i < xLen; ++i) {
// Use cached shape data for coordinate transforms
INDEX2COORDS(i, xRank, xShape, coords);
sd::LongType xOffset;
COORDS2INDEX(xRank, xStride, coords, xOffset);
sd::LongType zOffset;
if (areSameOffsets) {
zOffset = xOffset;
} else {
COORDS2INDEX(xRank, zStride, coords, zOffset);
}
// Check diagonal condition using cached rank
if (coords[xRank - 2] == coords[xRank - 1]) {
sd::LongType yOffset;
COORDS2INDEX(xRank - 1, yStride, coords, yOffset);
z[zOffset] = y[yOffset];
} else {
z[zOffset] = zeroPad ? static_cast<T>(0) : x[xOffset];
}
}
};
samediff::Threads::parallel_for(func, 0, xLen);
}
//////////////////////////////////////////////////////////////////////////
void matrixSetDiag(sd::LaunchContext* context, NDArray& input, NDArray& diagonal, NDArray& output,
const bool zeroPad) {
BUILD_SINGLE_SELECTOR(input.dataType(), matrixSetDiag_, (input, diagonal, output, zeroPad), SD_COMMON_TYPES);
}
} // namespace helpers
} // namespace ops
} // namespace sd
#endif