114 lines
3.7 KiB
C++
114 lines
3.7 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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// Created by Yurii Shyrma on 02.01.2018
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//
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#include <helpers/hhSequence.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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HHsequence::HHsequence(const NDArray& vectors, const NDArray& coeffs, const char type): _vectors(vectors), _coeffs(coeffs) {
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_diagSize = sd::math::nd4j_min(_vectors.sizeAt(0), _vectors.sizeAt(1));
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_shift = 0;
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_type = type;
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}
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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void HHsequence::mulLeft_(NDArray& matrix) {
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const int rows = _vectors.sizeAt(0);
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const int cols = _vectors.sizeAt(1);
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const int inRows = matrix.sizeAt(0);
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for(int i = _diagSize - 1; i >= 0; --i) {
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if(_type == 'u') {
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NDArray block = matrix({inRows-rows+_shift+ i,inRows, 0,0}, true);
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Householder<T>::mulLeft(block, _vectors({i + 1 + _shift, rows, i, i+1}, true), _coeffs.t<T>(i));
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}
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else {
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NDArray block = matrix({inRows-cols+_shift+i,inRows, 0,0}, true);
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Householder<T>::mulLeft(block, _vectors({i, i+1, i + 1 + _shift, cols}, true), _coeffs.t<T>(i));
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}
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}
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}
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//////////////////////////////////////////////////////////////////////////
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NDArray HHsequence::getTail(const int idx) const {
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int first = idx + 1 + _shift;
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if(_type == 'u')
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return _vectors({first, -1, idx, idx+1}, true);
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else
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return _vectors({idx, idx+1, first, -1}, true);
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}
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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void HHsequence::applyTo_(NDArray& dest) {
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int size = _type == 'u' ? _vectors.sizeAt(0) : _vectors.sizeAt(1);
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if(dest.rankOf() != 2 || (dest.sizeAt(0) != size && dest.sizeAt(1) != size))
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dest = NDArray(dest.ordering(), {size, size}, dest.dataType(), dest.getContext());
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dest.setIdentity();
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for(int k = _diagSize - 1; k >= 0; --k) {
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int curNum = size - k - _shift;
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if(curNum < 1 || (k + 1 + _shift) >= size )
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continue;
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auto block = dest({dest.sizeAt(0)-curNum,dest.sizeAt(0), dest.sizeAt(1)-curNum,dest.sizeAt(1)}, true);
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Householder<T>::mulLeft(block, getTail(k), _coeffs.t<T>(k));
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}
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}
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//////////////////////////////////////////////////////////////////////////
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void HHsequence::applyTo(NDArray& dest) {
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auto xType = _coeffs.dataType();
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BUILD_SINGLE_SELECTOR(xType, applyTo_, (dest), FLOAT_TYPES);
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}
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//////////////////////////////////////////////////////////////////////////
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void HHsequence::mulLeft(NDArray& matrix) {
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auto xType = _coeffs.dataType();
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BUILD_SINGLE_SELECTOR(xType, mulLeft_, (matrix), FLOAT_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void HHsequence::applyTo_, (sd::NDArray &dest), FLOAT_TYPES);
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BUILD_SINGLE_TEMPLATE(template void HHsequence::mulLeft_, (NDArray& matrix), FLOAT_TYPES);
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}
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}
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}
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