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MIPLearn/miplearn/types.py

103 lines
2.3 KiB

# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
from typing import Optional, Dict, Callable, Any, Union, Tuple, List
from mypy_extensions import TypedDict
VarIndex = Union[str, int, Tuple[Union[str, int]]]
Solution = Dict[str, Dict[VarIndex, Optional[float]]]
TrainingSample = TypedDict(
"TrainingSample",
{
"LP log": str,
"LP solution": Optional[Solution],
"LP value": Optional[float],
"Lower bound": Optional[float],
"MIP log": str,
"Solution": Optional[Solution],
"Upper bound": Optional[float],
"slacks": Dict,
},
total=False,
)
LPSolveStats = TypedDict(
"LPSolveStats",
{
"LP log": str,
"LP value": Optional[float],
},
)
MIPSolveStats = TypedDict(
"MIPSolveStats",
{
"Lower bound": Optional[float],
"MIP log": str,
"Nodes": Optional[int],
"Sense": str,
"Upper bound": Optional[float],
"Wallclock time": float,
"Warm start value": Optional[float],
},
)
LearningSolveStats = TypedDict(
"LearningSolveStats",
{
"Gap": Optional[float],
"Instance": Union[str, int],
"LP log": str,
"LP value": Optional[float],
"Lower bound": Optional[float],
"MIP log": str,
"Mode": str,
"Nodes": Optional[int],
"Objective: predicted LB": float,
"Objective: predicted UB": float,
"Primal: free": int,
"Primal: one": int,
"Primal: zero": int,
"Sense": str,
"Solver": str,
"Upper bound": Optional[float],
"Wallclock time": float,
"Warm start value": Optional[float],
},
total=False,
)
ConstraintFeatures = TypedDict(
"ConstraintFeatures",
{
"rhs": float,
"lhs": Dict[str, float],
"sense": str,
},
total=False,
)
ModelFeatures = TypedDict(
"ModelFeatures",
{
"constraints": Dict[str, ConstraintFeatures],
},
total=False,
)
IterationCallback = Callable[[], bool]
LazyCallback = Callable[[Any, Any], None]
SolverParams = Dict[str, Any]
BranchPriorities = Solution
class Constraint:
pass