chore: import upstream snapshot with attribution
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wehub-resource-sync
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/* ******************************************************************************
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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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// Created by Yurii Shyrma on 18.12.2017
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//
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#include <helpers/biDiagonalUp.h>
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#include <helpers/householder.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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//////////////////////////////////////////////////////////////////////////
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BiDiagonalUp::BiDiagonalUp(NDArray& matrix)
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: _HHmatrix(matrix.dataType(), matrix.getContext(), true),
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_HHbidiag(matrix.dataType(), matrix.getContext(), true),
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_hhCoeffs(matrix.dataType(), matrix.getContext(), true) {
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// input validation
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if (matrix.rankOf() != 2 || matrix.isScalar())
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THROW_EXCEPTION("ops::helpers::biDiagonalizeUp constructor: input array must be 2D matrix !");
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std::vector<LongType> shape = {matrix.sizeAt(0), matrix.sizeAt(1)};
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_HHmatrix = NDArray(matrix.ordering(), shape, matrix.dataType(), matrix.getContext());
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std::vector<sd::LongType> shape2 = {matrix.sizeAt(1), matrix.sizeAt(1)};
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_HHbidiag = NDArray(matrix.ordering(),shape2, matrix.dataType(), matrix.getContext());
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_HHmatrix.assign(&matrix);
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double zeroAssign = 0.;
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_HHbidiag.assign(zeroAssign);
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evalData();
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}
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template <typename T>
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void BiDiagonalUp::_evalData() {
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const auto rows = _HHmatrix.sizeAt(0);
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const auto cols = _HHmatrix.sizeAt(1);
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if (rows < cols)
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THROW_EXCEPTION(
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"ops::helpers::BiDiagonalizeUp::evalData method: this procedure is applicable only for input matrix with rows "
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">= cols !");
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T coeff, normX;
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T x, y;
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for (LongType i = 0; i < cols - 1; ++i) {
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// evaluate Householder matrix nullifying columns
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NDArray *column1Ptr = _HHmatrix({i, rows, i, i + 1});
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NDArray column1 = *column1Ptr;
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delete column1Ptr;
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x = _HHmatrix.t<T>(i, i);
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y = _HHbidiag.t<T>(i, i);
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Householder<T>::evalHHmatrixDataI(column1, x, y);
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_HHmatrix.r<T>(i, i) = x;
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_HHbidiag.r<T>(i, i) = y;
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// multiply corresponding matrix block on householder matrix from the left: P * bottomRightCorner
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NDArray *bottomRightCorner1Ptr = _HHmatrix({i, rows, i + 1, cols}, true); // {i, cols}
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NDArray bottomRightCorner1 = *bottomRightCorner1Ptr;
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delete bottomRightCorner1Ptr;
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NDArray *hhViewPtr = _HHmatrix({i + 1, rows, i, i + 1}, true);
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Householder<T>::mulLeft(bottomRightCorner1, *hhViewPtr, _HHmatrix.t<T>(i, i));
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delete hhViewPtr;
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if (i == cols - 2) continue; // do not apply right multiplying at last iteration
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// evaluate Householder matrix nullifying rows
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NDArray *row1Ptr = _HHmatrix({i, i + 1, i + 1, cols});
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NDArray row1 = *row1Ptr;
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delete row1Ptr;
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x = _HHmatrix.t<T>(i, i + 1);
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y = _HHbidiag.t<T>(i, i + 1);
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Householder<T>::evalHHmatrixDataI(row1, x, y);
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_HHmatrix.r<T>(i, i + 1) = x;
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_HHbidiag.r<T>(i, i + 1) = y;
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// multiply corresponding matrix block on householder matrix from the right: bottomRightCorner * P
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NDArray *bottomRightCorner2Ptr = _HHmatrix({i + 1, rows, i + 1, cols}, true); // {i, rows}
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NDArray bottomRightCorner2 = *bottomRightCorner2Ptr;
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delete bottomRightCorner2Ptr;
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NDArray *hhView2Ptr = _HHmatrix({i, i + 1, i + 2, cols}, true);
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Householder<T>::mulRight(bottomRightCorner2, *hhView2Ptr, _HHmatrix.t<T>(i, i + 1));
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delete hhView2Ptr;
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}
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NDArray *row2Ptr = _HHmatrix({cols - 2, cols - 1, cols - 1, cols});
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NDArray row2 = *row2Ptr;
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delete row2Ptr;
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x = _HHmatrix.t<T>(cols - 2, cols - 1);
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y = _HHbidiag.t<T>(cols - 2, cols - 1);
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Householder<T>::evalHHmatrixDataI(row2, x, y);
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_HHmatrix.r<T>(cols - 2, cols - 1) = x;
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_HHbidiag.r<T>(cols - 2, cols - 1) = y;
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NDArray *column2Ptr = _HHmatrix({cols - 1, rows, cols - 1, cols});
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NDArray column2 = *column2Ptr;
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delete column2Ptr;
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x = _HHmatrix.t<T>(cols - 1, cols - 1);
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y = _HHbidiag.t<T>(cols - 1, cols - 1);
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Householder<T>::evalHHmatrixDataI(column2, x, y);
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_HHmatrix.r<T>(cols - 1, cols - 1) = x;
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_HHbidiag.r<T>(cols - 1, cols - 1) = y;
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}
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//////////////////////////////////////////////////////////////////////////
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void BiDiagonalUp::evalData() {
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auto xType = _HHmatrix.dataType();
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BUILD_SINGLE_SELECTOR(xType, _evalData, ();, SD_FLOAT_TYPES);
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}
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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HHsequence BiDiagonalUp::makeHHsequence_(const char type) {
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const int diagSize = type == 'u' ? _HHbidiag.sizeAt(0) : _HHbidiag.sizeAt(0) - 1;
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std::vector<LongType> shape = {diagSize};
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_hhCoeffs = NDArray(_HHmatrix.ordering(),shape, _HHmatrix.dataType(), _HHmatrix.getContext());
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if (type == 'u')
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for (int i = 0; i < diagSize; ++i) _hhCoeffs.r<T>(i) = _HHmatrix.t<T>(i, i);
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else
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for (int i = 0; i < diagSize; ++i) _hhCoeffs.r<T>(i) = _HHmatrix.t<T>(i, i + 1);
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HHsequence result(&_HHmatrix, &_hhCoeffs, type);
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if (type != 'u') {
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result._diagSize = diagSize;
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result._shift = 1;
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}
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return result;
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}
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//////////////////////////////////////////////////////////////////////////
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HHsequence BiDiagonalUp::makeHHsequence(const char type) {
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auto xType = _HHmatrix.dataType();
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BUILD_SINGLE_SELECTOR(xType, return makeHHsequence_, (type);, SD_FLOAT_TYPES);
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// This should never be reached - BUILD_SINGLE_SELECTOR covers all SD_FLOAT_TYPES
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THROW_EXCEPTION("BiDiagonalUp::makeHHsequence: unsupported data type");
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}
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BUILD_SINGLE_TEMPLATE( void BiDiagonalUp::_evalData, (), SD_FLOAT_TYPES);
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BUILD_SINGLE_TEMPLATE( HHsequence BiDiagonalUp::makeHHsequence_, (const char type), SD_FLOAT_TYPES);
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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