wehub-resource-sync
112 lines
4.1 KiB
C++
112 lines
4.1 KiB
C++
/* ******************************************************************************
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*
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author Yurii Shyrma, created on 21.09.2018
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// @author raver119@gmail.com
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//
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// CPU implementation of ismax helper
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//
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#include <execution/Threads.h>
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#include <helpers/ConstantTadHelper.h>
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#include <ops/declarable/helpers/ismax.h>
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#include <system/op_boilerplate.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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template <typename T>
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static void ismax_(LaunchContext* context, NDArray* input, NDArray* output,
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const std::vector<LongType>& dimensions) {
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// Initialize output to zeros
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output->nullify();
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if (dimensions.size() == 0 || (dimensions.size() == 1 && dimensions[0] == sd::DataTypeUtils::max<int>())) {
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// Scalar case - find the single maximum in the entire array
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auto indexMax = input->applyIndexReduce(indexreduce::IndexMax, &dimensions);
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auto targetIdx = indexMax->e<LongType>(0);
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// Set the maximum position to 1
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output->p(targetIdx, static_cast<T>(1));
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delete indexMax;
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} else {
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// Dimensional case - find maximum along specified dimensions
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std::vector<LongType> copy(dimensions);
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// Get the indices of maximum values along the specified dimensions
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auto indexMaxArr = input->applyIndexReduce(indexreduce::IndexMax, &dimensions);
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// Get TAD information for the output
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auto packZ = ConstantTadHelper::getInstance().tadForDimensions(output->shapeInfo(), copy.data(), copy.size());
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auto zTadShapeInfo = packZ->primaryShapeInfo();
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auto zTadOffsets = packZ->primaryOffsets();
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auto numTads = packZ->numberOfTads();
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auto tadLen = shape::length(zTadShapeInfo);
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auto zBuffer = output->bufferAsT<T>();
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// For each TAD, set the maximum index position to 1
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auto func = PRAGMA_THREADS_FOR {
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for (auto t = start; t < stop; t++) {
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auto zTadOffset = zTadOffsets[t];
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auto maxIdx = indexMaxArr->e<LongType>(t);
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// Calculate the actual offset within this TAD
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if (maxIdx >= 0 && maxIdx < tadLen) {
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sd::LongType coords[SD_MAX_RANK];
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sd::LongType zOffset;
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const int tadRank = shape::rank(zTadShapeInfo);
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const sd::LongType* tadShape = shape::shapeOf(zTadShapeInfo);
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const sd::LongType* tadStride = shape::stride(zTadShapeInfo);
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INDEX2COORDS(maxIdx, tadRank, tadShape, coords);
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COORDS2INDEX(tadRank, tadStride, coords, zOffset);
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zBuffer[zTadOffset + zOffset] = static_cast<T>(1);
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}
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}
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};
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samediff::Threads::parallel_for(func, 0, numTads);
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delete indexMaxArr;
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}
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}
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void ismax(LaunchContext* context, NDArray* input, NDArray* output, const std::vector<LongType>& dimensions) {
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NDArray::prepareSpecialUse({output}, {input});
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BUILD_SINGLE_SELECTOR(input->dataType(), ismax_, (context, input, output, dimensions), SD_COMMON_TYPES);
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NDArray::registerSpecialUse({output}, {input});
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}
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BUILD_SINGLE_TEMPLATE(void ismax_,
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(sd::LaunchContext* context, NDArray* input, NDArray* output,
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const std::vector<sd::LongType>& dimensions),
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SD_COMMON_TYPES);
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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