cavis/libnd4j/include/helpers/impl/biDiagonalUp.cpp

160 lines
5.0 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
******************************************************************************/
//
// Created by Yurii Shyrma on 18.12.2017
//
#include <helpers/householder.h>
#include <helpers/biDiagonalUp.h>
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
BiDiagonalUp::BiDiagonalUp(const NDArray& matrix): _HHmatrix(NDArray(matrix.ordering(), {matrix.sizeAt(0), matrix.sizeAt(1)}, matrix.dataType(), matrix.getContext())),
_HHbidiag(NDArray(matrix.ordering(), {matrix.sizeAt(1), matrix.sizeAt(1)}, matrix.dataType(), matrix.getContext())) {
// input validation
if(matrix.rankOf() != 2 || matrix.isScalar())
throw std::runtime_error("ops::helpers::biDiagonalizeUp constructor: input array must be 2D matrix !");
_HHmatrix.assign(&matrix);
_HHbidiag.assign(0.);
evalData();
}
template <typename T>
void BiDiagonalUp::_evalData() {
const auto rows = _HHmatrix.sizeAt(0);
const auto cols = _HHmatrix.sizeAt(1);
if(rows < cols)
throw std::runtime_error("ops::helpers::BiDiagonalizeUp::evalData method: this procedure is applicable only for input matrix with rows >= cols !");
T coeff, normX;
T x, y;
for(Nd4jLong i = 0; i < cols-1; ++i ) {
// evaluate Householder matrix nullifying columns
NDArray column1 = _HHmatrix({i,rows, i,i+1});
x = _HHmatrix.t<T>(i,i);
y = _HHbidiag.t<T>(i,i);
Householder<T>::evalHHmatrixDataI(column1, x, y);
_HHmatrix.r<T>(i, i) = x;
_HHbidiag.r<T>(i, i) = y;
// multiply corresponding matrix block on householder matrix from the left: P * bottomRightCorner
NDArray bottomRightCorner1 = _HHmatrix({i,rows, i+1,cols}, true); // {i, cols}
Householder<T>::mulLeft(bottomRightCorner1, _HHmatrix({i+1,rows, i,i+1}, true), _HHmatrix.t<T>(i,i));
if(i == cols-2)
continue; // do not apply right multiplying at last iteration
// evaluate Householder matrix nullifying rows
NDArray row1 = _HHmatrix({i,i+1, i+1,cols});
x = _HHmatrix.t<T>(i,i+1);
y = _HHbidiag.t<T>(i,i+1);
Householder<T>::evalHHmatrixDataI(row1, x, y);
_HHmatrix.r<T>(i, i+1) = x;
_HHbidiag.r<T>(i, i+1) = y;
// multiply corresponding matrix block on householder matrix from the right: bottomRightCorner * P
NDArray bottomRightCorner2 = _HHmatrix({i+1,rows, i+1,cols}, true); // {i, rows}
Householder<T>::mulRight(bottomRightCorner2, _HHmatrix({i,i+1, i+2,cols}, true), _HHmatrix.t<T>(i,i+1));
}
NDArray row2 =_HHmatrix({cols-2,cols-1, cols-1,cols});
x = _HHmatrix.t<T>(cols-2,cols-1);
y = _HHbidiag.t<T>(cols-2,cols-1);
Householder<T>::evalHHmatrixDataI(row2, x, y);
_HHmatrix.r<T>(cols-2,cols-1) = x;
_HHbidiag.r<T>(cols-2,cols-1) = y;
NDArray column2 = _HHmatrix({cols-1,rows, cols-1,cols});
x = _HHmatrix.t<T>(cols-1,cols-1);
y = _HHbidiag.t<T>(cols-1,cols-1);
Householder<T>::evalHHmatrixDataI(column2, x, y);
_HHmatrix.r<T>(cols-1, cols-1) = x;
_HHbidiag.r<T>(cols-1, cols-1) = y;
}
//////////////////////////////////////////////////////////////////////////
void BiDiagonalUp::evalData() {
auto xType = _HHmatrix.dataType();
BUILD_SINGLE_SELECTOR(xType, _evalData, ();, FLOAT_TYPES);
}
//////////////////////////////////////////////////////////////////////////
template <typename T>
HHsequence BiDiagonalUp::makeHHsequence_(const char type) {
const int diagSize = type == 'u' ? _HHbidiag.sizeAt(0) : _HHbidiag.sizeAt(0) - 1;
_hhCoeffs = NDArray(_HHmatrix.ordering(), {diagSize}, _HHmatrix.dataType(), _HHmatrix.getContext());
if(type == 'u')
for(int i = 0; i < diagSize; ++i)
_hhCoeffs.r<T>(i) = _HHmatrix.t<T>(i,i);
else
for(int i = 0; i < diagSize; ++i)
_hhCoeffs.r<T>(i) = _HHmatrix.t<T>(i,i+1);
HHsequence result(_HHmatrix, _hhCoeffs, type);
if(type != 'u') {
result._diagSize = diagSize;
result._shift = 1;
}
return result;
}
//////////////////////////////////////////////////////////////////////////
HHsequence BiDiagonalUp::makeHHsequence(const char type) {
auto xType = _HHmatrix.dataType();
BUILD_SINGLE_SELECTOR(xType, return makeHHsequence_, (type);, FLOAT_TYPES);
}
BUILD_SINGLE_TEMPLATE(template void BiDiagonalUp::_evalData, (), FLOAT_TYPES);
BUILD_SINGLE_TEMPLATE(template HHsequence BiDiagonalUp::makeHHsequence_, (const char type), FLOAT_TYPES);
}
}
}