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127 lines
2.9 KiB
127 lines
2.9 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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from typing import Optional, Dict, Callable, Any, Union, Tuple, List, Set, Hashable
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from mypy_extensions import TypedDict
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VarIndex = Union[str, int, Tuple[Union[str, int]]]
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Solution = Dict[str, Dict[VarIndex, Optional[float]]]
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TrainingSample = TypedDict(
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"TrainingSample",
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{
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"LP log": str,
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"LP solution": Optional[Solution],
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"LP value": Optional[float],
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"LazyStatic: All": Set[str],
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"LazyStatic: Enforced": Set[str],
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"Lower bound": Optional[float],
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"MIP log": str,
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"Solution": Optional[Solution],
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"Upper bound": Optional[float],
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"slacks": Dict,
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},
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total=False,
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)
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LPSolveStats = TypedDict(
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"LPSolveStats",
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{
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"LP log": str,
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"LP value": Optional[float],
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},
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)
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MIPSolveStats = TypedDict(
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"MIPSolveStats",
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{
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"Lower bound": Optional[float],
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"MIP log": str,
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"Nodes": Optional[int],
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"Sense": str,
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"Upper bound": Optional[float],
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"Wallclock time": float,
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"Warm start value": Optional[float],
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},
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)
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LearningSolveStats = TypedDict(
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"LearningSolveStats",
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{
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"Gap": Optional[float],
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"Instance": Union[str, int],
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"LP log": str,
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"LP value": Optional[float],
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"Lower bound": Optional[float],
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"MIP log": str,
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"Mode": str,
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"Nodes": Optional[int],
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"Objective: Predicted lower bound": float,
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"Objective: Predicted upper bound": float,
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"Primal: Free": int,
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"Primal: One": int,
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"Primal: Zero": int,
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"Sense": str,
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"Solver": str,
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"Upper bound": Optional[float],
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"Wallclock time": float,
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"Warm start value": Optional[float],
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},
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total=False,
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)
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InstanceFeatures = TypedDict(
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"InstanceFeatures",
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{
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"User features": List[float],
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},
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total=False,
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)
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VariableFeatures = TypedDict(
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"VariableFeatures",
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{
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"Category": Optional[Hashable],
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"User features": Optional[List[float]],
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},
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total=False,
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)
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ConstraintFeatures = TypedDict(
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"ConstraintFeatures",
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{
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"RHS": float,
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"LHS": Dict[str, float],
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"Sense": str,
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"Category": Optional[Hashable],
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"User features": Optional[List[float]],
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"Lazy": bool,
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},
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total=False,
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)
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Features = TypedDict(
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"Features",
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{
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"Instance": InstanceFeatures,
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"Variables": Dict[str, Dict[VarIndex, VariableFeatures]],
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"Constraints": Dict[str, ConstraintFeatures],
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},
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total=False,
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)
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IterationCallback = Callable[[], bool]
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LazyCallback = Callable[[Any, Any], None]
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SolverParams = Dict[str, Any]
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BranchPriorities = Solution
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class Constraint:
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pass
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