| 1 | //===- LinearTransform.cpp - MLIR LinearTransform Class -------------------===// |
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| 2 | // |
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| 3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
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| 4 | // See https://llvm.org/LICENSE.txt for license information. |
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| 5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
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| 6 | // |
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| 7 | //===----------------------------------------------------------------------===// |
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| 8 | |
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| 9 | #include "mlir/Analysis/Presburger/LinearTransform.h" |
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| 10 | #include "mlir/Analysis/Presburger/IntegerRelation.h" |
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| 11 | #include "mlir/Analysis/Presburger/Matrix.h" |
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| 12 | #include <utility> |
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| 13 | |
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| 14 | using namespace mlir; |
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| 15 | using namespace presburger; |
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| 16 | |
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| 17 | LinearTransform::LinearTransform(IntMatrix &&oMatrix) : matrix(oMatrix) {} |
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| 18 | LinearTransform::LinearTransform(const IntMatrix &oMatrix) : matrix(oMatrix) {} |
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| 19 | |
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| 20 | std::pair<unsigned, LinearTransform> |
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| 21 | LinearTransform::makeTransformToColumnEchelon(const IntMatrix &m) { |
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| 22 | // Compute the hermite normal form of m. This, is by definition, is in column |
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| 23 | // echelon form. |
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| 24 | auto [h, u] = m.computeHermiteNormalForm(); |
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| 25 | |
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| 26 | // Since the matrix is in column ecehlon form, a zero column means the rest of |
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| 27 | // the columns are zero. Thus, once we find a zero column, we can stop. |
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| 28 | unsigned col, e; |
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| 29 | for (col = 0, e = m.getNumColumns(); col < e; ++col) { |
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| 30 | bool zeroCol = true; |
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| 31 | for (unsigned row = 0, f = m.getNumRows(); row < f; ++row) { |
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| 32 | if (h(row, col) != 0) { |
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| 33 | zeroCol = false; |
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| 34 | break; |
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| 35 | } |
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| 36 | } |
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| 37 | |
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| 38 | if (zeroCol) |
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| 39 | break; |
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| 40 | } |
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| 41 | |
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| 42 | return {col, LinearTransform(std::move(u))}; |
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| 43 | } |
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| 44 | |
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| 45 | IntegerRelation LinearTransform::applyTo(const IntegerRelation &rel) const { |
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| 46 | IntegerRelation result(rel.getSpace()); |
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| 47 | |
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| 48 | for (unsigned i = 0, e = rel.getNumEqualities(); i < e; ++i) { |
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| 49 | ArrayRef<DynamicAPInt> eq = rel.getEquality(idx: i); |
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| 50 | |
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| 51 | const DynamicAPInt &c = eq.back(); |
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| 52 | |
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| 53 | SmallVector<DynamicAPInt, 8> newEq = preMultiplyWithRow(rowVec: eq.drop_back()); |
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| 54 | newEq.emplace_back(Args: c); |
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| 55 | result.addEquality(eq: newEq); |
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| 56 | } |
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| 57 | |
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| 58 | for (unsigned i = 0, e = rel.getNumInequalities(); i < e; ++i) { |
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| 59 | ArrayRef<DynamicAPInt> ineq = rel.getInequality(idx: i); |
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| 60 | |
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| 61 | const DynamicAPInt &c = ineq.back(); |
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| 62 | |
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| 63 | SmallVector<DynamicAPInt, 8> newIneq = preMultiplyWithRow(rowVec: ineq.drop_back()); |
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| 64 | newIneq.emplace_back(Args: c); |
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| 65 | result.addInequality(inEq: newIneq); |
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| 66 | } |
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| 67 | |
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| 68 | return result; |
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| 69 | } |
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| 70 | |
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