wehub-resource-sync
327 lines
13 KiB
C++
327 lines
13 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 Oleh Semeniv (oleg.semeniv@gmail.com)
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// @author AbdelRauf (rauf@konduit.ai)
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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/adjust_hue.h>
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#include <ops/declarable/helpers/imagesHelpers.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 rgbToGrs_(NDArray& input, NDArray& output, const int dimC) {
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const T* x = input.bufferAsT<T>();
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T* z = output.bufferAsT<T>();
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const int rank = input.rankOf();
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if (dimC == rank - 1 && 'c' == input.ordering() && 1 == input.ews() && 'c' == output.ordering() &&
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1 == output.ews()) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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const auto xStep = i * 3;
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z[i] = 0.2989f * x[xStep] + 0.5870f * x[xStep + 1] + 0.1140f * x[xStep + 2];
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}
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};
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samediff::Threads::parallel_for(func, 0, output.lengthOf(), 1);
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return;
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}
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sd::LongType *outputShape = shape::shapeOf(output.shapeInfo());
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sd::LongType *outputStride = shape::stride(output.shapeOf());
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sd::LongType *inputStride = shape::stride(input.shapeInfo());
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auto func = PRAGMA_THREADS_FOR {
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sd::LongType coords[SD_MAX_RANK];
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for (auto i = start; i < stop; i++) {
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INDEX2COORDS(i, rank,outputShape, coords);
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sd::LongType zOffset, xOffset0, xOffset1, xOffset2;
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COORDS2INDEX(rank, outputStride, coords, zOffset);
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COORDS2INDEX(rank, inputStride, coords, xOffset0);
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coords[dimC]++;
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COORDS2INDEX(rank,inputStride, coords, xOffset1);
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coords[dimC]++;
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COORDS2INDEX(rank, inputStride, coords, xOffset2);
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z[zOffset] = 0.2989f * x[xOffset0] + 0.5870f * x[xOffset1] + 0.1140f * x[xOffset2];
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}
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};
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samediff::Threads::parallel_for(func, 0, output.lengthOf(), 1);
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return;
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}
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void transformRgbGrs(sd::LaunchContext* context, NDArray& input, NDArray& output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input.dataType(), rgbToGrs_, (input, output, dimC), SD_NUMERIC_TYPES);
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}
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template <typename T>
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SD_INLINE static void tripleTransformer(NDArray* input, NDArray* output, const int dimC, T (&tr)[3][3]) {
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const int rank = input->rankOf();
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const T* x = input->bufferAsT<T>();
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T* z = output->bufferAsT<T>();
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// TODO: Use tensordot or other optimizied helpers to see if we can get better performance.
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if (dimC == rank - 1 && input->ews() == 1 && output->ews() == 1 && input->ordering() == 'c' &&
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output->ordering() == 'c') {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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// simple M*v //tr.T*v.T // v * tr //rule: (AB)' =B'A'
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// v.shape (1,3) row vector
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T x0, x1, x2;
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x0 = x[i]; // just additional hint
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x1 = x[i + 1];
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x2 = x[i + 2];
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z[i] = x0 * tr[0][0] + x1 * tr[1][0] + x2 * tr[2][0];
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z[i + 1] = x0 * tr[0][1] + x1 * tr[1][1] + x2 * tr[2][1];
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z[i + 2] = x0 * tr[0][2] + x1 * tr[1][2] + x2 * tr[2][2];
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}
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};
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samediff::Threads::parallel_for(func, 0, input->lengthOf(), 3);
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} else {
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input->shapeInfo(), dimC);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output->shapeInfo(), dimC);
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const sd::LongType numOfTads = packX->numberOfTads();
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const sd::LongType xDimCstride = input->stridesOf()[dimC];
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const sd::LongType zDimCstride = output->stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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const T* xTad = x + packX->platformOffsets()[i];
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T* zTad = z + packZ->platformOffsets()[i];
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// simple M*v //tr.T*v
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T x0, x1, x2;
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x0 = xTad[0];
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x1 = xTad[xDimCstride];
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x2 = xTad[2 * xDimCstride];
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zTad[0] = x0 * tr[0][0] + x1 * tr[1][0] + x2 * tr[2][0];
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zTad[zDimCstride] = x0 * tr[0][1] + x1 * tr[1][1] + x2 * tr[2][1];
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zTad[2 * zDimCstride] = x0 * tr[0][2] + x1 * tr[1][2] + x2 * tr[2][2];
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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}
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}
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template <typename T>
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SD_INLINE static void rgbYiq(NDArray* input, NDArray* output, const int dimC) {
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T arr[3][3] = {{(T)0.299, (T)0.59590059, (T)0.2115},
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{(T)0.587, (T)-0.27455667, (T)-0.52273617},
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{(T)0.114, (T)-0.32134392, (T)0.31119955}};
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return tripleTransformer<T>(input, output, dimC, arr);
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}
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template <typename T>
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SD_INLINE static void yiqRgb(NDArray* input, NDArray* output, const int dimC) {
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// TODO: this operation does not use the clamp operation, so there is a possibility being out of range.
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// Justify that it will not be out of range for images data
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T arr[3][3] = {{(T)1, (T)1, (T)1},
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{(T)0.95598634, (T)-0.27201283, (T)-1.10674021},
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{(T)0.6208248, (T)-0.64720424, (T)1.70423049}};
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return tripleTransformer<T>(input, output, dimC, arr);
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}
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template <typename T>
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SD_INLINE static void hsvRgb(NDArray* input, NDArray* output, const int dimC) {
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const int rank = input->rankOf();
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const T* x = input->bufferAsT<T>();
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T* z = output->bufferAsT<T>();
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if (dimC == rank - 1 && input->ews() == 1 && output->ews() == 1 && input->ordering() == 'c' &&
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output->ordering() == 'c') {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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sd::ops::helpers::hsvToRgb<T>(x[i], x[i + 1], x[i + 2], z[i], z[i + 1], z[i + 2]);
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}
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};
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samediff::Threads::parallel_for(func, 0, input->lengthOf(), 3);
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} else {
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input->shapeInfo(), dimC);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output->shapeInfo(), dimC);
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const sd::LongType numOfTads = packX->numberOfTads();
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const sd::LongType xDimCstride = input->stridesOf()[dimC];
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const sd::LongType zDimCstride = output->stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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const T* xTad = x + packX->platformOffsets()[i];
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T* zTad = z + packZ->platformOffsets()[i];
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sd::ops::helpers::hsvToRgb<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride],
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zTad[2 * zDimCstride]);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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}
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}
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template <typename T>
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SD_INLINE static void rgbHsv(NDArray* input, NDArray* output, const int dimC) {
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const int rank = input->rankOf();
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const T* x = input->bufferAsT<T>();
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T* z = output->bufferAsT<T>();
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if (dimC == rank - 1 && input->ews() == 1 && output->ews() == 1 && input->ordering() == 'c' &&
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output->ordering() == 'c') {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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sd::ops::helpers::rgbToHsv<T>(x[i], x[i + 1], x[i + 2], z[i], z[i + 1], z[i + 2]);
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}
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};
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samediff::Threads::parallel_for(func, 0, input->lengthOf(), 3);
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} else {
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input->shapeInfo(), dimC);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output->shapeInfo(), dimC);
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const sd::LongType numOfTads = packX->numberOfTads();
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const sd::LongType xDimCstride = input->stridesOf()[dimC];
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const sd::LongType zDimCstride = output->stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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const T* xTad = x + packX->platformOffsets()[i];
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T* zTad = z + packZ->platformOffsets()[i];
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sd::ops::helpers::rgbToHsv<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride],
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zTad[2 * zDimCstride]);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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}
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}
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template <typename T>
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SD_INLINE static void rgbYuv_(NDArray& input, NDArray& output, const int dimC) {
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const T* x = input.bufferAsT<T>();
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T* z = output.bufferAsT<T>();
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const int rank = input.rankOf();
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bool bSimple = (dimC == rank - 1 && 'c' == input.ordering() && 1 == input.ews() && 'c' == output.ordering() &&
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1 == output.ews());
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if (bSimple) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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sd::ops::helpers::rgbYuv<T>(x[i], x[i + 1], x[i + 2], z[i], z[i + 1], z[i + 2]);
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}
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};
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samediff::Threads::parallel_for(func, 0, input.lengthOf(), 3);
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return;
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}
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input.shapeInfo(), dimC);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output.shapeInfo(), dimC);
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const sd::LongType numOfTads = packX->numberOfTads();
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const sd::LongType xDimCstride = input.stridesOf()[dimC];
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const sd::LongType zDimCstride = output.stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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const T* xTad = x + packX->platformOffsets()[i];
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T* zTad = z + packZ->platformOffsets()[i];
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sd::ops::helpers::rgbYuv<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride],
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zTad[2 * zDimCstride]);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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return;
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}
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template <typename T>
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SD_INLINE static void yuvRgb_(NDArray& input, NDArray& output, const int dimC) {
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const T* x = input.bufferAsT<T>();
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T* z = output.bufferAsT<T>();
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const int rank = input.rankOf();
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bool bSimple = (dimC == rank - 1 && 'c' == input.ordering() && 1 == input.ews() && 'c' == output.ordering() &&
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1 == output.ews());
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if (bSimple) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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sd::ops::helpers::yuvRgb<T>(x[i], x[i + 1], x[i + 2], z[i], z[i + 1], z[i + 2]);
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}
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};
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samediff::Threads::parallel_for(func, 0, input.lengthOf(), 3);
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return;
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}
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input.shapeInfo(), dimC);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output.shapeInfo(), dimC);
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const sd::LongType numOfTads = packX->numberOfTads();
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const sd::LongType xDimCstride = input.stridesOf()[dimC];
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const sd::LongType zDimCstride = output.stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i += increment) {
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const T* xTad = x + packX->platformOffsets()[i];
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T* zTad = z + packZ->platformOffsets()[i];
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sd::ops::helpers::yuvRgb<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride],
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zTad[2 * zDimCstride]);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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return;
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}
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void transformRgbYuv(sd::LaunchContext* context, NDArray& input, NDArray& output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input.dataType(), rgbYuv_, (input, output, dimC), SD_FLOAT_TYPES);
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}
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void transformYuvRgb(sd::LaunchContext* context, NDArray& input, NDArray& output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input.dataType(), yuvRgb_, (input, output, dimC), SD_FLOAT_TYPES);
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}
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void transformHsvRgb(sd::LaunchContext* context, NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), hsvRgb, (input, output, dimC), SD_FLOAT_TYPES);
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}
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void transformRgbHsv(sd::LaunchContext* context, NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), rgbHsv, (input, output, dimC), SD_FLOAT_TYPES);
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}
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void transformYiqRgb(sd::LaunchContext* context, NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), yiqRgb, (input, output, dimC), SD_FLOAT_TYPES);
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}
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void transformRgbYiq(sd::LaunchContext* context, NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), rgbYiq, (input, output, dimC), SD_FLOAT_TYPES);
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}
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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