shugeo 330a69d4e2
Shugeo solve ls (#203)
* lstsq op. Initial commit.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Least squares linear problem solve op (lstsq). Cpu draft implementation.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Fixed shape routine and tests.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added test for lstsq op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Rectification for lstsq op implementation.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Corrected test to avoid numerical inconsistensy.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added prints for check computing.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Corrected tests to use evalueate facility instead.

Signed-off-by: shugeo <sgazeos@gmail.com>

* CPU implementation of MatrixSolveLs op and tests.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added cuda implementation for helpers with lstsq op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Refactored tests for lstsq op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added processing for empty inputs.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Merged tests.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Refactored lstsq op for fast case.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Fixed test.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Refactored lstsq op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Fixed some issues with solve.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Fixed lstsq op to avoid erros.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added kernel for giagonal factor

Signed-off-by: shugeo <sgazeos@gmail.com>

* lstsq wrapper and triangular_solve fixed

* Added proper processing empty inputs and test.

Signed-off-by: shugeo <sgazeos@gmail.com>

* SequenceMask test

* Build fixed

* Added proper processing of empty inputs with solve op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Mapping added

* Added check of input shapes with solve op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Added a couple of tests for lstsq op and minor changes with cuda helper for one.'

Signed-off-by: shugeo <sgazeos@gmail.com>

* Tests on

* Refactored test for lstsq op.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Fixed test

* Added another approach for lstsq op aka solve_ls.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Finished cpu part for solve_ls op helpers.

* Added helper for low triangular matrix inversion.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Refactored alternate solve_ls cpu implementation.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Removed alternate approach for solve_ls op. Added multithreading with matrix inversion.

Signed-off-by: shugeo <sgazeos@gmail.com>

* Assert fixed

* Refactored multithreading for inverse matricies.

Signed-off-by: shugeo <sgazeos@gmail.com>

Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
2020-02-28 11:37:26 +03:00

90 lines
4.3 KiB
C++

/*******************************************************************************
* Copyright (c) 2019-2020 Konduit K.K.
*
* 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 GS <sgazeos@gmail.com> at 12/20/2019
//
#include <op_boilerplate.h>
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/qr.h>
#if NOT_EXCLUDED(OP_qr)
namespace nd4j {
namespace ops {
CUSTOM_OP_IMPL(qr, 1, 2, false, 0, 0) {
auto input = INPUT_VARIABLE(0);
auto outputQ = OUTPUT_VARIABLE(0);
auto outputR = OUTPUT_VARIABLE(1);
auto fullMatricies = false;
if (block.getBArguments()->size())
fullMatricies = B_ARG(0);
REQUIRE_TRUE(input->rankOf() >=2, 0, "qr: The rank of input array should not be less than 2, but %i is given", input->rankOf());
REQUIRE_TRUE((fullMatricies && outputQ->sizeAt(-1) == input->sizeAt(-2)) || (!fullMatricies && outputQ->isSameShape(input)), 0, "qr: The last dimmensions should be equal to result Q, but %i and %i are given", outputQ->sizeAt(-1), input->sizeAt(-2));
REQUIRE_TRUE((fullMatricies && outputR->sizeAt(-1) == input->sizeAt(-1)) || (!fullMatricies && outputR->sizeAt(-1) == outputR->sizeAt(-2)), 0, "qr: The last dimmensions should be equal to result R, but %i and %i are given", outputR->sizeAt(-1), input->sizeAt(-1));
if (!input->isEmpty() && !outputQ->isEmpty() && !outputR->isEmpty())
helpers::qr(block.launchContext(), input, outputQ, outputR, fullMatricies);
return Status::OK();
}
DECLARE_SHAPE_FN(qr) {
auto inShape = inputShape->at(0);
Nd4jLong* shapeQ;
Nd4jLong* shapeR;
int targetRank = shape::rank(inShape); // last two dimensions will be reduced to scalar
auto fullMatricies = false;
if (block.getBArguments()->size())
fullMatricies = B_ARG(0);
auto shape = ShapeUtils::shapeAsVector(inShape);
if (!fullMatricies) { // outputs are: Q is MxN and R is NxN
shape[targetRank - 1] = shape::sizeAt(inShape, -1);
shape[targetRank - 2] = shape[targetRank - 1];
shapeQ = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape),
shape::order(inShape), targetRank,
shape::shapeOf(inShape));
shapeR = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape),
shape::order(inShape), shape);
}
else {// otherwise outputs are Q is MxM and R is MxN with zero filled rows
shape[targetRank - 1] = shape::sizeAt(inShape, -2);
shape[targetRank - 2] = shape[targetRank - 1];
shapeR = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape),
shape::order(inShape), targetRank,
shape::shapeOf(inShape));
shapeQ = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape),
shape::order(inShape), shape);
}
return SHAPELIST(shapeQ, shapeR);
}
DECLARE_TYPES(qr) {
getOpDescriptor()
->setAllowedInputTypes({ALL_FLOATS})
->setAllowedOutputTypes({ALL_FLOATS});
}
}
}
#endif