265 lines
7.9 KiB
Python
265 lines
7.9 KiB
Python
# Copyright 2010-2022 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Patch to the python wrapper of ../linear_solver.h providing an algebraic API.
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This is directly imported, and use exclusively in ./linear_solver.swig. See that
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file.
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For examples leveraging the code defined here, see ./pywraplp_test.py and
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../../../python/linear_programming.py.
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"""
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import collections
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import numbers
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# The classes below allow linear expressions to be expressed naturally with the
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# usual arithmetic operators +-*/ and with constant numbers, which makes the
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# python API very intuitive. See the top-level comment for examples.
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inf = float('inf')
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class _FakeMPVariableRepresentingTheConstantOffset(object):
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"""A dummy class for a singleton instance used to represent the constant.
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To represent linear expressions, we store a dictionary
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MPVariable->coefficient. To represent the constant offset of the expression,
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we use this class as a substitute: its coefficient will be the offset. To
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properly be evaluated, its solution_value() needs to be 1.
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"""
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def solution_value(self): # pylint: disable=invalid-name
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return 1
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def __repr__(self):
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return 'OFFSET_KEY'
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OFFSET_KEY = _FakeMPVariableRepresentingTheConstantOffset()
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def CastToLinExp(v):
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if isinstance(v, numbers.Number):
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return Constant(v)
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else:
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return v
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class LinearExpr(object):
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"""Holds linear expressions.
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A linear expression is essentially an offset (floating-point value), and a
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dictionary mapping MPVariable objects to their coefficient (which is also a
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floating-point value).
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"""
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OVERRIDDEN_OPERATOR_METHODS = [
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'__%s__' % opname
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for opname in ['add', 'radd', 'sub', 'rsub', 'mul', 'rmul', 'div',
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'truediv', 'neg', 'eq', 'ge', 'le', 'gt', 'lt', 'ne']
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]
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def solution_value(self): # pylint: disable=invalid-name
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"""Value of this linear expr, using the solution_value of its vars."""
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coeffs = self.GetCoeffs()
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return sum(var.solution_value() * coeff for var, coeff in coeffs.items())
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def AddSelfToCoeffMapOrStack(self, coeffs, multiplier, stack):
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"""Private function used by GetCoeffs() to delegate processing.
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Implementation must either update coeffs or push to the stack a
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sub-expression and the accumulated multiplier that applies to it.
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Args:
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coeffs: A dictionary of variables' coefficients. It is a defaultdict that
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initializes the new values to 0 by default.
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multiplier: The current accumulated multiplier to apply to this
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expression.
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stack: A list to append to if the current expression is composed of
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sub-expressions. The elements of the stack are pair tuples
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(multiplier, linear_expression).
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"""
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raise NotImplementedError
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def GetCoeffs(self):
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coeffs = collections.defaultdict(float)
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stack = [(1.0, self)]
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while stack:
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current_multiplier, current_expression = stack.pop()
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current_expression.AddSelfToCoeffMapOrStack(coeffs, current_multiplier,
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stack)
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return coeffs
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def __add__(self, expr):
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return Sum(self, expr)
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def __radd__(self, cst):
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return Sum(self, cst)
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def __sub__(self, expr):
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return Sum(self, -expr)
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def __rsub__(self, cst):
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return Sum(-self, cst)
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def __mul__(self, cst):
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return ProductCst(self, cst)
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def __rmul__(self, cst):
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return ProductCst(self, cst)
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def __div__(self, cst):
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return ProductCst(self, 1.0 / cst)
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def __truediv__(self, cst):
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return ProductCst(self, 1.0 / cst)
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def __neg__(self):
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return ProductCst(self, -1)
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def __eq__(self, arg):
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if isinstance(arg, numbers.Number):
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return LinearConstraint(self, arg, arg)
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else:
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return LinearConstraint(self - arg, 0.0, 0.0)
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def __ge__(self, arg):
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if isinstance(arg, numbers.Number):
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return LinearConstraint(self, arg, inf)
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else:
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return LinearConstraint(self - arg, 0.0, inf)
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def __le__(self, arg):
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if isinstance(arg, numbers.Number):
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return LinearConstraint(self, -inf, arg)
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else:
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return LinearConstraint(self - arg, -inf, 0.0)
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def __lt__(self, arg):
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raise ValueError(
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'Operators "<" and ">" not supported with the linear solver')
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def __gt__(self, arg):
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raise ValueError(
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'Operators "<" and ">" not supported with the linear solver')
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def __ne__(self, arg):
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raise ValueError('Operator "!=" not supported with the linear solver')
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class VariableExpr(LinearExpr):
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"""Represents a LinearExpr containing only a single variable."""
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def __init__(self, mpvar):
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self.__var = mpvar
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def AddSelfToCoeffMapOrStack(self, coeffs, multiplier, stack):
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coeffs[self.__var] += multiplier
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class ProductCst(LinearExpr):
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"""Represents the product of a LinearExpr by a constant."""
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def __init__(self, expr, coef):
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self.__expr = CastToLinExp(expr)
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if isinstance(coef, numbers.Number):
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self.__coef = coef
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else:
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raise TypeError
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def __str__(self):
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if self.__coef == -1:
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return '-' + str(self.__expr)
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else:
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return '(' + str(self.__coef) + ' * ' + str(self.__expr) + ')'
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def AddSelfToCoeffMapOrStack(self, coeffs, multiplier, stack):
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current_multiplier = multiplier * self.__coef
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if current_multiplier:
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stack.append((current_multiplier, self.__expr))
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class Constant(LinearExpr):
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def __init__(self, val):
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self.__val = val
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def __str__(self):
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return str(self.__val)
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def AddSelfToCoeffMapOrStack(self, coeffs, multiplier, stack):
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coeffs[OFFSET_KEY] += self.__val * multiplier
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class SumArray(LinearExpr):
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"""Represents the sum of a list of LinearExpr."""
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def __init__(self, array):
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self.__array = [CastToLinExp(elem) for elem in array]
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def __str__(self):
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return '({})'.format(' + '.join(map(str, self.__array)))
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def AddSelfToCoeffMapOrStack(self, coeffs, multiplier, stack):
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# Append elements in reversed order so that the first popped from the stack
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# in the next iteration of the evaluation loop will be the first item of the
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# array. This keeps the end result of the floating point computation
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# predictable from user perspective.
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for arg in reversed(self.__array):
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stack.append((multiplier, arg))
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def Sum(*args):
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return SumArray(args)
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SumCst = Sum # pylint: disable=invalid-name
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class LinearConstraint(object):
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"""Represents a linear constraint: LowerBound <= LinearExpr <= UpperBound."""
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def __init__(self, expr, lb, ub):
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self.__expr = expr
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self.__lb = lb
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self.__ub = ub
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def __str__(self):
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if self.__lb > -inf and self.__ub < inf:
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if self.__lb == self.__ub:
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return str(self.__expr) + ' == ' + str(self.__lb)
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else:
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return (str(self.__lb) + ' <= ' + str(self.__expr) +
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' <= ' + str(self.__ub))
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elif self.__lb > -inf:
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return str(self.__expr) + ' >= ' + str(self.__lb)
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elif self.__ub < inf:
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return str(self.__expr) + ' <= ' + str(self.__ub)
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else:
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return 'Trivial inequality (always true)'
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def Extract(self, solver, name=''):
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"""Performs the actual creation of the constraint object."""
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coeffs = self.__expr.GetCoeffs()
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constant = coeffs.pop(OFFSET_KEY, 0.0)
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lb = -solver.infinity()
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ub = solver.infinity()
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if self.__lb > -inf:
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lb = self.__lb - constant
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if self.__ub < inf:
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ub = self.__ub - constant
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constraint = solver.RowConstraint(lb, ub, name)
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for v, c, in coeffs.items():
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constraint.SetCoefficient(v, float(c))
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return constraint
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