110 lines
3.6 KiB
C++
110 lines
3.6 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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 sgazeos@gmail.com
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//
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#include <ops/declarable/helpers/unique.h>
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#include <Status.h>
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#include <execution/Threads.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename T>
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static Nd4jLong uniqueCount_(NDArray* input) {
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Nd4jLong count = 0;
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std::vector<T> values;
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for (int e = 0; e < input->lengthOf(); e++) {
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T v = input->e<T>(e);
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if (std::find(values.begin(), values.end(), v) == values.end()) {
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values.push_back(v);
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count++;
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}
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}
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return count;
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}
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Nd4jLong uniqueCount(nd4j::LaunchContext * context, NDArray* input) {
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BUILD_SINGLE_SELECTOR(input->dataType(), return uniqueCount_, (input), LIBND4J_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template Nd4jLong uniqueCount_, (NDArray* input), LIBND4J_TYPES);
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template <typename T>
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static Nd4jStatus uniqueFunctor_(NDArray* input, NDArray* values, NDArray* indices, NDArray* counts) {
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std::vector<T> valuesVector;
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std::map<T, int> indicesMap;
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std::map<T, int> countsMap;
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for (int e = 0; e < input->lengthOf(); e++) {
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T v = input->e<T>(e);
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if (std::find(valuesVector.begin(), valuesVector.end(), v) == valuesVector.end()) {
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valuesVector.push_back(v);
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indicesMap[v] = e;
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countsMap[v] = 1;
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}
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else {
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countsMap[v]++;
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}
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}
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auto func = PRAGMA_THREADS_FOR {
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for (auto e = start; e < stop; e += increment) {
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values->p(e, static_cast<T>(valuesVector[e]));
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if (counts != nullptr)
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counts->p(e, countsMap[valuesVector[e]]);
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}
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};
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samediff::Threads::parallel_for(func, 0, values->lengthOf());
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for (int e = 0; e < indices->lengthOf(); e++) {
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auto posI = std::find(valuesVector.begin(), valuesVector.end(), input->e<T>(e));
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auto dist = std::distance(valuesVector.begin(), posI);
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indices->p(e, Nd4jLong(dist));//indicesMap[(*input)(e)];
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}
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return Status::OK();
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}
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Nd4jStatus uniqueFunctor(nd4j::LaunchContext * context, NDArray* input, NDArray* values, NDArray* indices, NDArray* counts) {
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input->syncToHost();
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values->syncToHost();
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indices->syncToHost();
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if (counts != nullptr)
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counts->syncToHost();
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BUILD_SINGLE_SELECTOR(input->dataType(), return uniqueFunctor_,(input, values, indices, counts), LIBND4J_TYPES);
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input->syncToDevice();
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values->syncToDevice();
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indices->syncToDevice();
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if (counts != nullptr)
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counts->syncToDevice();
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}
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BUILD_SINGLE_TEMPLATE(template Nd4jStatus uniqueFunctor_, (NDArray* input, NDArray* values, NDArray* indices, NDArray* counts), LIBND4J_TYPES);
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}
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}
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} |