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fix(linear_programming): implement __neg__, __pos__, and __abs__ for LinearExpression (fixes #2056) - #2068
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…LinearExpression (fixes NVIDIA#2056) Signed-off-by: reginaldalfret <reginaldalfret@gmail.com>
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Included review availability: This review used your included allowance. Your plan provides up to 12 included reviews per hour; 11 remain after this review. 📝 WalkthroughWalkthroughLinearExpression now supports unary negation and unary plus. Scalar multiplication copies the variable list when it creates a result. Tests check operator results, mutation isolation, and the ChangesLinearExpression Unary Operators
Priority: ➖ Normal Estimated code review effort: 2 (Simple) | ~10 minutes Change: Bug fix · Severity of issue fixed: Medium Suggested reviewers: Merge Risk: ⚪ Minimal · up to The unary operators and their tests show no remaining actionable merge risk in the reviewed changes. 🚥 Pre-merge checks | ✅ 3 | ❌ 2❌ Failed checks (2 warnings)
✅ Passed checks (3 passed)
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✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
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Review comments at @python/cuopt/cuopt/linear_programming/problem.py:
- Around line 1089-1099: Add return type annotations and API docstrings to
LinearExpression.__neg__, __pos__, and __abs__, documenting each operator’s
semantics, return value, and applicable exceptions. Specify that __abs__
evaluates the expression using current variable values; keep the changes limited
to these new public operator methods.
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| def __neg__(self): | ||
| return self * -1.0 | ||
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| def __pos__(self): | ||
| return LinearExpression( | ||
| list(self.vars), list(self.coefficients), self.constant | ||
| ) | ||
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| def __abs__(self): | ||
| val = self.getValue() | ||
| return val if val >= 0.0 else -val |
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📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win
Add type hints and API docstrings to the new operators.
These new LinearExpression operator methods are public API, but they have no annotations or docstrings. Add return annotations and document each operator’s semantics, return value, and applicable exceptions. State that __abs__ evaluates the expression using current variable values.
As per path instructions: “Type hints on NEW public functions/classes” and “Docstring CONTENT on new public APIs — params, returns, raises.”
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Review comment at @python/cuopt/cuopt/linear_programming/problem.py around lines
1089 - 1099:
Add return type annotations and API docstrings to LinearExpression.__neg__,
__pos__, and __abs__, documenting each operator’s semantics, return value, and
applicable exceptions. Specify that __abs__ evaluates the expression using
current variable values; keep the changes limited to these new public operator
methods.
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ramakrishnap-nv
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Two correctness issues found while testing against a patched copy of the module (repro below); see inline comments.
| def __len__(self): | ||
| return len(self.vars) | ||
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| def __neg__(self): |
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__mul__'s float branch does LinearExpression(self.vars, coeffs, constant) -- it doesn't copy self.vars, so -e shares the same list object as e. Any later in-place op on the negated expression corrupts the original:
neg_e = -e
neg_e += z # __iadd__ does self.vars.append(z)
# e.vars now also contains zConfirmed by running the patched code. __pos__ right below correctly avoids this with list(self.vars) -- worth doing the same here (or fixing __mul__'s float branch to copy).
| ) | ||
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| def __abs__(self): | ||
| val = self.getValue() |
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This returns a plain float (unlike __neg__/__pos__, which stay in LinearExpression), and pre-solve it's nan (Variable.Value defaults to nan). setObjective has case int() | float(): which silently accepts it as a constant objective, zeroing every variable's coefficient:
problem.setObjective(abs(2*x + 3*y))
# ObjConstant = nan, all coefficients zeroed, no errorGiven #2056's whole motivation was surfacing failures early instead of silent breakage, this seems like a regression in that direction -- previously this raised TypeError. |linear expr| isn't itself linear (PuLP/Pyomo don't overload abs() on expressions either), so maybe skip __abs__ here, or at least raise instead of returning a float that type-checks as a valid objective/constant.
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We should not support _abs on a LinearExpressions.
…e __abs__ Signed-off-by: reginaldalfret <reginaldalfret@gmail.com>
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Addressed the review feedback:
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Inline comments:
Review comments at
@python/cuopt/cuopt/tests/linear_programming/test_python_API.py:
- Line 944: Update the variable membership assertions in the expression tests to
use object identity, since Variable.__eq__ returns a Constraint. Replace
membership checks for z in neg_e.vars, pos_e.vars, and mul_e.vars with
identity-based any checks, and checks for z not in e.vars with identity-based
all checks.
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…ship checks Signed-off-by: reginaldalfret <reginaldalfret@gmail.com>
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LGTM. Thanks for the fix!
chris-maes
added
bug
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/ok to test f2e3e9e |
CI Test Summary✅ All 23 test job(s) passed. (1 skipped) |
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/merge |
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| # Ensure abs() is not supported on LinearExpression | ||
| with pytest.raises(TypeError): | ||
| abs(e) |
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This test for not supporting abs shouldn't be here.
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What's the issue with having the test here?
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If it's minor maybe we can fix this in a follow up.
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Both issues from the earlier review are fixed, and the aliasing fix is better than what I suggested:
__neg__now buildsLinearExpressiondirectly withlist(self.vars)and fresh coefficients instead of delegating toself * -1.0. More importantly, the actual root cause got fixed too --__mul__'s float branch now copiesself.varsas well, so this benefits every scalar-multiply caller, not just negation. The new test regression-tests all three paths (neg_e,pos_e, rawe * -1.0) with explicit identity (is) assertions.__abs__was removed entirely rather than kept as a numeric-eval footgun --abs(e)now correctly raisesTypeErroragain, matching PuLP/Pyomo (neither overloadsabs()on linear expressions, since|expr|isn't representable as aLinearExpression). Regression-tested directly.
CI green, mergeable. Approving.
Summary
Implements unary operator overloads (
__neg__,__pos__, and__abs__) forLinearExpressionincuopt.linear_programming.problem.Problem Statement
Variablesupports unary minus (e.g.-x), butLinearExpressiondid not implement__neg__,__pos__, or__abs__. As a result, attempting to negate a multi-term expression or a scaled expression (e.g.-(2*x)or-e) raisedTypeError: bad operand type for unary -: 'LinearExpression'. This created an asymmetry between single variables and linear expressions, and prevented standard QP objective negation patterns (e.g.setObjective(-(2*x + 3*y))). (Fixes #2056)Solution
__neg__(),__pos__(), and__abs__()onLinearExpression.test_linear_expression_unary_opsinpython/cuopt/cuopt/tests/linear_programming/test_python_API.py.Related Issues
Fixes #2056