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deeplearning4j--deeplearning4j/libnd4j/include/loops/cpu/random.hpp
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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 raver119@gmail.com, created on 15.12.17.
// @author Yurii Shyrma (iuriish@yahoo.com)
//
#include <helpers/OmpLaunchHelper.h>
#include <loops/random.h>
#include <system/op_boilerplate.h>
#include <types/types.h>
using namespace randomOps;
namespace functions {
namespace random {
template <typename X>
template <typename OpClass>
void RandomFunction<X>::execTransform(sd::Pointer state, const void *vx, const sd::LongType *xShapeInfo, const void *vy,
const sd::LongType *yShapeInfo, void *vz, const sd::LongType *zShapeInfo,
void *vextraArguments) {
auto x = reinterpret_cast<const X *>(vx);
auto y = reinterpret_cast<const X *>(vy);
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
if (OpClass::requiresSpecial) {
OpClass::specialOp(state, x, xShapeInfo, y, yShapeInfo, z, zShapeInfo, extraArguments);
return;
}
// Cache shape-related values
sd::LongType xRank = shape::rank(xShapeInfo);
sd::LongType yRank = shape::rank(yShapeInfo);
sd::LongType zRank = shape::rank(zShapeInfo);
sd::LongType *xShape = shape::shapeOf(xShapeInfo);
sd::LongType *yShape = shape::shapeOf(yShapeInfo);
sd::LongType *zShape = shape::shapeOf(zShapeInfo);
sd::LongType *xStride = shape::stride(xShapeInfo);
sd::LongType *yStride = shape::stride(yShapeInfo);
sd::LongType *zStride = shape::stride(zShapeInfo);
auto length = shape::length(zShapeInfo);
sd::graph::RandomGenerator *rng = reinterpret_cast<sd::graph::RandomGenerator *>(state);
if (shape::haveSameShapeAndStrides(xShapeInfo, yShapeInfo) &&
shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo)) {
auto func = PRAGMA_THREADS_FOR {
PRAGMA_OMP_SIMD
for (auto i = start; i < stop; i++) {
z[i] = OpClass::op(x[i], y[i], i, length, rng, extraArguments);
}
};
samediff::Threads::parallel_for(func, 0, length, 1);
} else {
sd::LongType coords[SD_MAX_RANK];
auto func = PRAGMA_THREADS_FOR {
PRAGMA_OMP_SIMD
for (auto i = start; i < stop; i++) {
INDEX2COORDS(i, xRank, xShape, coords);
sd::LongType xOffset, yOffset, zOffset;
COORDS2INDEX(xRank, xStride, coords, xOffset);
COORDS2INDEX(yRank, yStride, coords, yOffset);
COORDS2INDEX(zRank, zStride, coords, zOffset);
z[zOffset] = OpClass::op(x[xOffset], y[yOffset], i, length, rng, extraArguments);
}
};
samediff::Threads::parallel_for(func, 0, length, 1);
}
}
template <typename X>
template <typename OpClass>
void RandomFunction<X>::execTransform(sd::Pointer state, const void *vx, const sd::LongType *xShapeInfo, void *vz,
const sd::LongType *zShapeInfo, void *vextraArguments) {
auto x = reinterpret_cast<const X *>(vx);
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
// Cache shape-related values
sd::LongType xRank = shape::rank(xShapeInfo);
sd::LongType zRank = shape::rank(zShapeInfo);
sd::LongType *xShape = shape::shapeOf(xShapeInfo);
sd::LongType *zShape = shape::shapeOf(zShapeInfo);
sd::LongType *xStride = shape::stride(xShapeInfo);
sd::LongType *zStride = shape::stride(zShapeInfo);
auto length = shape::length(zShapeInfo);
sd::graph::RandomGenerator *rng = reinterpret_cast<sd::graph::RandomGenerator *>(state);
if (shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo)) {
sd::LongType coords[SD_MAX_RANK];
auto func = PRAGMA_THREADS_FOR {
PRAGMA_OMP_SIMD
for (auto i = start; i < stop; i++) {
INDEX2COORDS(i, xRank, xShape, coords);
sd::LongType offset;
COORDS2INDEX(xRank, xStride, coords, offset);
z[offset] = OpClass::op(x[offset], i, length, rng, extraArguments);
}
};
samediff::Threads::parallel_for(func, 0, length, 1);
} else {
sd::LongType coords[SD_MAX_RANK];
auto func = PRAGMA_THREADS_FOR {
PRAGMA_OMP_SIMD
for (auto i = start; i < stop; i++) {
INDEX2COORDS(i, xRank, xShape, coords);
sd::LongType xOffset, zOffset;
COORDS2INDEX(xRank, xStride, coords, xOffset);
COORDS2INDEX(zRank, zStride, coords, zOffset);
z[zOffset] = OpClass::op(x[xOffset], i, length, rng, extraArguments);
}
};
samediff::Threads::parallel_for(func, 0, length, 1);
}
}
template <typename X>
template <typename OpClass>
void RandomFunction<X>::execTransform(sd::Pointer state, void *vz, const sd::LongType *zShapeInfo,
void *vextraArguments) {
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
// Cache shape-related values
sd::LongType zRank = shape::rank(zShapeInfo);
sd::LongType *zShape = shape::shapeOf(zShapeInfo);
sd::LongType *zStride = shape::stride(zShapeInfo);
auto length = shape::length(zShapeInfo);
sd::graph::RandomGenerator *rng = reinterpret_cast<sd::graph::RandomGenerator *>(state);
sd::LongType coords[SD_MAX_RANK];
auto func = PRAGMA_THREADS_FOR {
PRAGMA_OMP_SIMD
for (auto i = start; i < stop; i++) {
INDEX2COORDS(i, zRank, zShape, coords);
sd::LongType offset;
COORDS2INDEX(zRank, zStride, coords, offset);
z[offset] = OpClass::op(i, length, rng, extraArguments);
}
};
samediff::Threads::parallel_for(func, 0, length, 1);
}
// Dispatch functions remain unchanged as they just route to the optimized implementations
template <typename X>
void RandomFunction<X>::execTransform(int opNum, sd::Pointer state, const void *x, const sd::LongType *xShapeInfo,
void *z, const sd::LongType *zShapeInfo, void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, x, xShapeInfo, z, zShapeInfo, extraArguments), RANDOM_OPS)
}
template <typename X>
void RandomFunction<X>::execTransform(int opNum, sd::Pointer state, const void *x, const sd::LongType *xShapeInfo,
const void *y, const sd::LongType *yShapeInfo, void *z,
const sd::LongType *zShapeInfo, void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, x, xShapeInfo, y, yShapeInfo, z, zShapeInfo, extraArguments),
RANDOM_OPS)
}
template <typename X>
void RandomFunction<X>::execTransform(int opNum, sd::Pointer state, void *z, const sd::LongType *zShapeInfo,
void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, z, zShapeInfo, extraArguments), RANDOM_OPS)
}
} // namespace random
} // namespace functions