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//===- LinearTransform.cpp - MLIR LinearTransform Class -------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "mlir/Analysis/Presburger/LinearTransform.h"
#include "mlir/Analysis/Presburger/IntegerRelation.h"
using namespace mlir;
using namespace presburger;
LinearTransform::LinearTransform(Matrix &&oMatrix) : matrix(oMatrix) {}
LinearTransform::LinearTransform(const Matrix &oMatrix) : matrix(oMatrix) {}
std::pair<unsigned, LinearTransform>
LinearTransform::makeTransformToColumnEchelon(const Matrix &m) {
// Compute the hermite normal form of m. This, is by definition, is in column
// echelon form.
auto [h, u] = m.computeHermiteNormalForm();
// Since the matrix is in column ecehlon form, a zero column means the rest of
// the columns are zero. Thus, once we find a zero column, we can stop.
unsigned col, e;
for (col = 0, e = m.getNumColumns(); col < e; ++col) {
bool zeroCol = true;
for (unsigned row = 0, f = m.getNumRows(); row < f; ++row) {
if (h(row, col) != 0) {
zeroCol = false;
break;
}
}
if (zeroCol)
break;
}
return {col, LinearTransform(std::move(u))};
}
IntegerRelation LinearTransform::applyTo(const IntegerRelation &rel) const {
IntegerRelation result(rel.getSpace());
for (unsigned i = 0, e = rel.getNumEqualities(); i < e; ++i) {
ArrayRef<MPInt> eq = rel.getEquality(i);
const MPInt &c = eq.back();
SmallVector<MPInt, 8> newEq = preMultiplyWithRow(eq.drop_back());
newEq.push_back(c);
result.addEquality(newEq);
}
for (unsigned i = 0, e = rel.getNumInequalities(); i < e; ++i) {
ArrayRef<MPInt> ineq = rel.getInequality(i);
const MPInt &c = ineq.back();
SmallVector<MPInt, 8> newIneq = preMultiplyWithRow(ineq.drop_back());
newIneq.push_back(c);
result.addInequality(newIneq);
}
return result;
}
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