/*******************************************************************************
* 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 George A. Shulinok <sgazeos@gmail.com>, created on 4/18/2019
//
#include <ops/declarable/helpers/BarnesHutTsne.h>
#include <execution/Threads.h>
namespace sd {
namespace ops {
namespace helpers {
Nd4jLong barnes_row_count(const NDArray* rowP, const NDArray* colP, Nd4jLong N, NDArray& rowCounts) {
int* pRowCounts = reinterpret_cast<int*>(rowCounts.buffer());
int const* pRows = reinterpret_cast<int const*>(rowP->buffer());
int const* pCols = reinterpret_cast<int const*>(colP->buffer());
for (Nd4jLong n = 0; n < N; n++) {
int begin = pRows[n];//->e<int>(n);
int end = pRows[n + 1];//rowP->e<int>(n + 1);
for (int i = begin; i < end; i++) {
bool present = false;
for (int m = pRows[pCols[i]]; m < pRows[pCols[i] + 1]; m++)
if (pCols[m] == n) {
present = true;
break;
}
++pRowCounts[n];
if (!present)
++pRowCounts[pCols[i]];
}
}
NDArray numElementsArr = rowCounts.sumNumber(); //reduceAlongDimension(reduce::Sum, {});
//rowCounts.printBuffer("Row counts");
auto numElements = numElementsArr.e<Nd4jLong>(0);
return numElements;
}
// static
// void printVector(std::vector<int> const& v) {
// for (auto x: v) {
// printf("%d ", x);
// }
// printf("\n");
// fflush(stdout);
// }
template <typename T>
static void barnes_symmetrize_(const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts) {
//auto N = rowP->lengthOf() - 1; /// 2 + rowP->lengthOf() % 2;
//auto numElements = output->lengthOf();
//std::vector<int> symRowP = rowCounts->asVectorT<int>();//NDArrayFactory::create<int>('c', {numElements});
//NDArray symValP = NDArrayFactory::create<double>('c', {numElements});
//symRowP.insert(symRowP.begin(),0);
//symRowP(1, {0}) = *rowCounts;
int const* pRows = reinterpret_cast<int const*>(rowP->buffer());
int* symRowP = reinterpret_cast<int*>(outputRows->buffer());
symRowP[0] = 0;
for (Nd4jLong n = 0; n < N; n++)
symRowP[n + 1] = symRowP[n] + rowCounts->e<int>(n);
// outputRows->printBuffer("output rows");
int* symColP = reinterpret_cast<int*>(outputCols->buffer());
// symRowP.p(n + 1, symRowP.e(n) + rowCounts.e(n))
// outputRows->printBuffer("SymRows are");
int const* pCols = reinterpret_cast<int const*>(colP->buffer());
T const* pVals = reinterpret_cast<T const*>(valP->buffer());
T* pOutput = reinterpret_cast<T*>(outputVals->buffer());
//std::vector<int> rowCountsV = rowCounts->getBufferAsVector<int>();
std::vector<int> offset(N);// = NDArrayFactory::create<int>('c', {N});
//PRAGMA_OMP_PARALLEL_FOR_SIMD_ARGS(schedule(guided) shared(offset))
for (Nd4jLong n = 0; n < N; n++) {
int begin = pRows[n];
int bound = pRows[n + 1];
for (int i = begin; i < bound; i++) {
bool present = false;
int colPI = pCols[i];
int start = pRows[colPI];
int end = pRows[colPI + 1];
//PRAGMA_OMP_PARALLEL_FOR_ARGS(schedule(guided) firstprivate(offset))
for (int m = start; m < end; m++) {
if (pCols[m] == n) {
present = true;
if (n <= colPI) {
symColP[symRowP[n] + offset[n]] = colPI;
symColP[symRowP[colPI] + offset[colPI]] = n;
pOutput[symRowP[n] + offset[n]] = pVals[i] + pVals[m];
pOutput[symRowP[colPI] + offset[colPI]] = pVals[i] + pVals[m];
}
}
}
// If (colP[i], n) is not present, there is no addition involved
if (!present) {
//int colPI = pCols[i];
//if (n <= colPI) {
symColP[symRowP[n] + offset[n]] = colPI;
symColP[symRowP[pCols[i]] + offset[colPI]] = n;
pOutput[symRowP[n] + offset[n]] = pVals[i];
pOutput[symRowP[colPI] + offset[colPI]] = pVals[i];
//}
}
// Update offsets
if (!present || (present && n <= colPI)) {
++offset[n];
if (colPI != n)
++offset[colPI];
}
// printVector(offset);
}
}
}
void barnes_symmetrize(const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts) {
// Divide the result by two
BUILD_SINGLE_SELECTOR(valP->dataType(), barnes_symmetrize_, (rowP, colP, valP, N, outputRows, outputCols, outputVals, rowCounts), NUMERIC_TYPES);
*outputVals /= 2.0;
//output->assign(symValP);
}
BUILD_SINGLE_TEMPLATE(template void barnes_symmetrize_, (const NDArray* rowP, const NDArray* colP, const NDArray* valP, Nd4jLong N, NDArray* outputRows, NDArray* outputCols, NDArray* outputVals, NDArray* rowCounts), NUMERIC_TYPES);
template <typename T>
static void barnes_edge_forces_(const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray const* data, NDArray* output) {
T const* dataP = reinterpret_cast<T const*>(data->buffer());
T const* vals = reinterpret_cast<T const*>(valP->buffer());
T* outputP = reinterpret_cast<T*>(output->buffer());
int colCount = data->columns();
// auto shift = 0;
auto rowSize = sizeof(T) * colCount;
auto func = PRAGMA_THREADS_FOR {
for (auto n = start; n < stop; n++) {
int s = rowP->e<int>(n);
int end = rowP->e<int>(n + 1);
int shift = n * colCount;
for (int i = s; i < end; i++) {
T const *thisSlice = dataP + colP->e<int>(i) * colCount;
T res = 1;
for (int k = 0; k < colCount; k++) {
auto tempVal = dataP[shift + k] - thisSlice[k];//thisSlice[k];
res += tempVal * tempVal;
}
res = vals[i] / res;
for (int k = 0; k < colCount; k++)
outputP[shift + k] += ((dataP[shift + k] - thisSlice[k]) * res);
}
//shift += colCount;
}
};
samediff::Threads::parallel_tad(func, 0, N);
}
void barnes_edge_forces(const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray* output, NDArray const& data) {
// Loop over all edges in the graph
BUILD_SINGLE_SELECTOR(output->dataType(), barnes_edge_forces_, (rowP, colP, valP, N, &data, output), FLOAT_TYPES);
}
BUILD_SINGLE_TEMPLATE(template void barnes_edge_forces_, (const NDArray* rowP, NDArray const* colP, NDArray const* valP, int N, NDArray const* data, NDArray* output), FLOAT_TYPES);
template <typename T>
static void barnes_gains_(NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output) {
// gains = gains.add(.2).muli(sign(yGrads)).neq(sign(yIncs)).castTo(Nd4j.defaultFloatingPointType())
// .addi(gains.mul(0.8).muli(sign(yGrads)).neq(sign(yIncs)));
auto gainsInternal = LAMBDA_TTT(x, grad, eps) {
// return T((x + 2.) * sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps)) + T(x * 0.8 * sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps));
//return T((x + 2.) * sd::math::nd4j_sign<T,T>(grad) == sd::math::nd4j_sign<T,T>(eps)) + T(x * 0.8 * sd::math::nd4j_sign<T,T>(grad) == sd::math::nd4j_sign<T,T>(eps));
T res = sd::math::nd4j_sign<T,T>(grad) != sd::math::nd4j_sign<T,T>(eps) ? x + T(.2) : x * T(.8);
if(res < .01) res = .01;
return res;
};
input->applyTriplewiseLambda<T>(*gradX, *epsilon, gainsInternal, *output);
}
void barnes_gains(NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output) {
// gains = gains.add(.2).muli(sign(yGrads)).neq(sign(yIncs)).castTo(Nd4j.defaultFloatingPointType())
// .addi(gains.mul(0.8).muli(sign(yGrads)).neq(sign(yIncs)));
BUILD_SINGLE_SELECTOR(input->dataType(), barnes_gains_, (input, gradX, epsilon, output), NUMERIC_TYPES);
// auto signGradX = *gradX;
// auto signEpsilon = *epsilon;
// gradX->applyTransform(transform::Sign, &signGradX, nullptr);
// epsilon->applyTransform(transform::Sign, &signEpsilon, nullptr);
// auto leftPart = (*input + 2.) * signGradX;
// auto leftPartBool = NDArrayFactory::create<bool>(leftPart.ordering(), leftPart.getShapeAsVector());
//
// leftPart.applyPairwiseTransform(pairwise::NotEqualTo, &signEpsilon, &leftPartBool, nullptr);
// auto rightPart = *input * 0.8 * signGradX;
// auto rightPartBool = NDArrayFactory::create<bool>(rightPart.ordering(), rightPart.getShapeAsVector());
// rightPart.applyPairwiseTransform(pairwise::NotEqualTo, &signEpsilon, &rightPartBool, nullptr);
// leftPart.assign(leftPartBool);
// rightPart.assign(rightPartBool);
// leftPart.applyPairwiseTransform(pairwise::Add, &rightPart, output, nullptr);
}
BUILD_SINGLE_TEMPLATE(template void barnes_gains_, (NDArray* input, NDArray* gradX, NDArray* epsilon, NDArray* output), NUMERIC_TYPES);
bool cell_contains(NDArray* corner, NDArray* width, NDArray* point, Nd4jLong dimension) {
auto cornerMinusWidth = *corner - *width;
auto cornerPlusWidth = *corner + *width;
for (Nd4jLong i = 0; i < dimension; i++) {
if (cornerMinusWidth.e<double>(i) > point->e<double>(i))
return false;
if (cornerPlusWidth.e<double>(i) < point->e<double>(i))
return false;
}
return true;
}
}
}
}