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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
******************************************************************************/
#include <exceptions/cuda_exception.h>
#include <execution/cuda/LaunchDims.h>
#include <helpers/PointersManager.h>
#include <ops/declarable/helpers/assign.h>
#include "helpers/DebugHelper.h"
#include "helpers/ShapeUtils.h"
namespace sd {
namespace ops {
namespace helpers {
template <typename X, typename Z>
SD_KERNEL static void assignKernel(const void* vx, const LongType* xShapeInfo, void* vz, const LongType* zShapeInfo,
const LongType xOffset, const LongType zOffset) {
const auto x = reinterpret_cast<const X*>(vx);
auto z = reinterpret_cast<Z*>(vz);
__shared__ LongType len, totalThreads;
__shared__ int rank;
__shared__ const LongType *xShape;
__shared__ const LongType *zShape;
__shared__ const LongType *xStride;
__shared__ const LongType *zStride;
if (threadIdx.x == 0) {
len = shape::length(zShapeInfo);
totalThreads = gridDim.x * blockDim.x;
rank = shape::rank(zShapeInfo);
// Cache shapes and strides
xShape = shape::shapeOf(xShapeInfo);
zShape = shape::shapeOf(zShapeInfo);
xStride = shape::stride(xShapeInfo);
zStride = shape::stride(zShapeInfo);
}
__syncthreads();
const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
LongType xCoords[SD_MAX_RANK], zCoords[SD_MAX_RANK];
for (LongType i = tid; i < len; i += totalThreads) {
INDEX2COORDS(i, rank, zShape, zCoords);
INDEX2COORDS(i, rank, xShape, xCoords);
LongType xIndex, zIndex;
COORDS2INDEX(rank, xStride, xCoords, xIndex);
COORDS2INDEX(rank, zStride, zCoords, zIndex);
z[zIndex] = static_cast<Z>(x[xIndex]);
}
}
template <typename X, typename Z>
SD_HOST static void assignCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const int sharedMem,
const cudaStream_t* stream, const void* vx, const LongType* xShapeInfo,
void* vz, const LongType* zShapeInfo, const LongType xOffset, const LongType zOffset) {
assignKernel<X, Z><<<blocksPerGrid, threadsPerBlock, sharedMem, *stream>>>(vx, xShapeInfo, vz, zShapeInfo, xOffset, zOffset);
DebugHelper::checkGlobalErrorCode("assignKernel(...) failed");
}
void assign(sd::LaunchContext* context, sd::NDArray* target, sd::NDArray* source) {
if (target->lengthOf() != source->lengthOf()) {
std::string errorMsg = "assign helper: Source and target arrays must have the same length. ";
errorMsg += "Source shape: " + ShapeUtils::shapeAsString(source) + ", ";
errorMsg += "Target shape: " + ShapeUtils::shapeAsString(target) + ", ";
errorMsg += "Source datatype: " + DataTypeUtils::asString(source->dataType()) + ", ";
errorMsg += "Target datatype: " + DataTypeUtils::asString(target->dataType());
THROW_EXCEPTION(errorMsg.c_str());
}
NDArray::prepareSpecialUse({target}, {source});
auto xType = source->dataType();
auto zType = target->dataType();
dim3 launchDims = traceDims(target->lengthOf());
PointersManager manager(context, "helpers::assign");
BUILD_DOUBLE_SELECTOR(xType, zType, assignCudaLauncher,
(launchDims.x, launchDims.y, launchDims.z, context->getCudaStream(),
source->specialBuffer(), source->specialShapeInfo(),
target->specialBuffer(), target->specialShapeInfo(),
source->offset(), target->offset()),
SD_COMMON_TYPES, SD_COMMON_TYPES);
manager.synchronize();
NDArray::registerSpecialUse({target}, {source});
}
} // namespace helpers
} // namespace ops
} // namespace sd