cavis/libnd4j/include/ops/declarable/helpers/impl/unique.cpp

110 lines
3.6 KiB
C++

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