185 lines
9.1 KiB
C++
185 lines
9.1 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 raver119@gmail.com
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//
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#include <ops/declarable/helpers/top_k.h>
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#include <ops/declarable/headers/parity_ops.h>
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#include <NDArrayFactory.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 int topKFunctor_(const NDArray* input, NDArray* values, NDArray* indices, const uint k, bool needSort) {
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Nd4jLong width = input->sizeAt(-1);
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int lastDim = input->rankOf() - 1;
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// ----------------------------------------------------------------------------------------------- //
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// this assumption is right:
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// if (values->lengthOf() != k * lastDimList->size()) {
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// nd4j_printf("top_k: something is wrong. %i expected, but %i given.\n",
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// values->lengthOf(), k * lastDimList->size());
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// }
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// ----------------------------------------------------------------------------------------------- //
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std::vector<int> dimsToExclude(input->rankOf() - 1);
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for (int d = 0; d < dimsToExclude.size(); ++d)
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dimsToExclude[d] = d;
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const Nd4jLong numOfSubArrs = ShapeUtils::getNumOfSubArrs(input->getShapeInfo(), dimsToExclude);
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if (k == 1) {
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for (Nd4jLong e = 0; e < numOfSubArrs; ++e) {
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auto trial = (*input)(e, dimsToExclude);
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//int maxPos = //lastDimList->at(e)->argMax();
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Nd4jLong maxPos = 0;
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//trial.printIndexedBuffer("TRIAL:");
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T maxVal = trial.e<T>(0);
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for (Nd4jLong pos = 1; pos < trial.lengthOf(); pos++)
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if (maxVal < trial.e<T>(pos)) {
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maxPos = pos;
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maxVal = trial.e<T>(pos);
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}
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if (indices)
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indices->p(e, maxPos); //topIndex;
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if (values)
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values->p(e, maxVal);
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}
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}
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else {
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int nextPos = 0;
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for (Nd4jLong e = 0; e < numOfSubArrs; ++e) {
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auto trial = (*input)(e, dimsToExclude);
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// fill up the first k elements
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NDArray topValues = NDArrayFactory::create<T>('c', {k});
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NDArray sortedVals = NDArrayFactory::create<T>('c', {k});
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NDArray topIndices = NDArrayFactory::create<Nd4jLong>('c', {k});
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for (Nd4jLong pos = 0; pos < k; ++pos) {
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topIndices.t<Nd4jLong>(pos) = pos;
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topValues.t<T>(pos) = trial.t<T>(pos);
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}
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//std::vector<T> sortedVals(topValues);
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sortedVals.assign(topValues);// = NDArrayFactory::create<T>('c', {k});
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//std::sort(sortedVals.begin(), sortedVals.end()); // sorted in ascending order
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SpecialMethods<T>::sortGeneric(sortedVals.buffer(), sortedVals.shapeInfo(), false);
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for (int i = k; i < width; ++i) {
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T val = trial.e<T>(i);
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T minTopVal = sortedVals.t<T>(0);
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if (minTopVal < val) { // value should be inserted to top k
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// only if it is not contained in
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T* begin = reinterpret_cast<T*>(sortedVals.buffer());
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T* end = begin + k;
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bool exists = std::binary_search(begin, end, val);
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if (!exists) {
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//exchangePos - a distance between begin and minimal existed to be suppressed by val
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T* topBegin = reinterpret_cast<T*>(topValues.buffer());
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T* topEnd = topBegin + k;
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auto exchangePos = std::distance(topBegin, std::find(topBegin, topEnd, sortedVals.t<T>(0)));
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topValues.t<T>(exchangePos) = val; //*exchangeIt = val;
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topIndices.t<Nd4jLong>(exchangePos) = i;
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sortedVals.t<T>(0) = val; // suppress in sorted
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//std::sort(sortedVals.begin(), sortedVals.end()); // sorted in ascending order
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SpecialMethods<T>::sortGeneric(sortedVals.buffer(), sortedVals.shapeInfo(), false);
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}
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}
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}
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if (needSort) {
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SpecialMethods<T>::sortGeneric(topValues.buffer(), topValues.shapeInfo(), true);
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for (int j = 0; j < width; j++)
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for (int pos = 0; pos < k; ++pos)
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if (topValues.t<T>(pos) == trial.t<T>(j))
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topIndices.t<Nd4jLong>(pos) = j;
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}
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else { // else sort by indices
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std::map<Nd4jLong, T> sortValsMap;
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//std::vector<std::pair<int, T>> data(topValues.lengthOf());
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for (size_t e = 0; e < topValues.lengthOf(); ++e) {
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sortValsMap[topIndices.t<Nd4jLong>(e)] = topValues.t<T>(e);
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}
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//std::sort(data.begin(), data.end(), [](std::pair<int, T> const& a, std::pair<int, T> const& b) {
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// return a.first < b.first;
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//});
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Nd4jLong e = 0;
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for (auto it = sortValsMap.begin(); it != sortValsMap.end(); ++it, e++) {
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topIndices.t<Nd4jLong>(e) = it->first;
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topValues.t<T>(e) = it->second;
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}
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}
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if (values)
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(*values)(e, dimsToExclude).assign(topValues);
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if (indices)
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(*indices)(e, dimsToExclude).assign(topIndices);
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}
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//indices->printIndexedBuffer("Indices as is");
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}
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return Status::OK();
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}
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// ----------------------------------------------------------------------------------------------- //
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template <typename T>
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static int inTopKFunctor_(nd4j::LaunchContext* context, const NDArray* input, const NDArray* target, NDArray* result, const uint k) {
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std::vector<Nd4jLong> shapeI(input->rankOf());
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for (int i = 0; i < input->rankOf() - 1; i++)
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shapeI[i] = input->sizeAt(i);
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shapeI[input->rankOf() - 1] = k;
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std::unique_ptr<NDArray> indices(NDArrayFactory::create_<Nd4jLong>(input->ordering(), shapeI));
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NDArray* values = nullptr;
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int status = topKFunctor(context, input, values, indices.get(), k, true);
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result->assign(0);
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if (status == ND4J_STATUS_OK) {
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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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bool found = false;
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for (int j = 0; j < k; j++) {
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if (target->e<Nd4jLong>(e) == indices->e<Nd4jLong>(e * k + j)) {
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found = true;
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break;
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}
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}
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if (found)
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result->p<bool>(e, true);
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}
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};
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samediff::Threads::parallel_tad(func, 0, target->lengthOf());
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}
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return status;
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}
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int topKFunctor(nd4j::LaunchContext * context, const NDArray* input, NDArray* values, NDArray* indices, const uint k, bool needSort) {
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BUILD_SINGLE_SELECTOR(input->dataType(), return topKFunctor_, (input, values, indices, k, needSort), NUMERIC_TYPES);
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}
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int inTopKFunctor(nd4j::LaunchContext * context, const NDArray* input, const NDArray* target, NDArray* result, const uint k) {
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BUILD_SINGLE_SELECTOR(input->dataType(), return inTopKFunctor_, (context, input, target, result, k), NUMERIC_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template int topKFunctor_, (const NDArray* input, NDArray* values, NDArray* indices, const uint k, bool needSort), NUMERIC_TYPES);
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BUILD_SINGLE_TEMPLATE(template int inTopKFunctor_, (nd4j::LaunchContext * context, const NDArray* input, const NDArray* target, NDArray* result, const uint k), NUMERIC_TYPES);
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}
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}
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}
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