Reorganize instance package

miplearn/__init__.py

@@ -3,15 +3,9 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 from .benchmark import BenchmarkRunner
-from .classifiers import (
-    Classifier,
-    Regressor,
-)
+from .classifiers import Classifier, Regressor
 from .classifiers.adaptive import AdaptiveClassifier
-from .classifiers.sklearn import (
-    ScikitLearnRegressor,
-    ScikitLearnClassifier,
-)
+from .classifiers.sklearn import ScikitLearnRegressor, ScikitLearnClassifier
 from .classifiers.threshold import MinPrecisionThreshold
 from .components.component import Component
 from .components.dynamic_lazy import DynamicLazyConstraintsComponent
@@ -22,12 +16,12 @@ from .components.static_lazy import StaticLazyConstraintsComponent
 from .components.steps.convert_tight import ConvertTightIneqsIntoEqsStep
 from .components.steps.drop_redundant import DropRedundantInequalitiesStep
 from .components.steps.relax_integrality import RelaxIntegralityStep
-from .instance import (
-    Instance,
+from .instance.base import Instance
+from .instance.picklegz import (
     PickleGzInstance,
     write_pickle_gz,
-    write_pickle_gz_multiple,
     read_pickle_gz,
+    write_pickle_gz_multiple,
 )
 from .log import setup_logger
 from .solvers.gurobi import GurobiSolver

miplearn/benchmark.py

@@ -8,7 +8,7 @@ from typing import Dict, List
 
 import pandas as pd
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.solvers.learning import LearningSolver
 
 logger = logging.getLogger(__name__)

miplearn/components/component.py

@@ -7,7 +7,7 @@ from typing import Any, List, TYPE_CHECKING, Tuple, Dict, Hashable
 import numpy as np
 
 from miplearn.features import TrainingSample, Features
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.types import LearningSolveStats
 
 if TYPE_CHECKING:

miplearn/components/objective.py

@@ -12,7 +12,7 @@ from miplearn.classifiers import Regressor
 from miplearn.classifiers.sklearn import ScikitLearnRegressor
 from miplearn.components.component import Component
 from miplearn.features import TrainingSample, Features
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.types import LearningSolveStats
 
 if TYPE_CHECKING:

miplearn/components/primal.py

@@ -21,7 +21,7 @@ from miplearn.classifiers.threshold import MinPrecisionThreshold, Threshold
 from miplearn.components import classifier_evaluation_dict
 from miplearn.components.component import Component
 from miplearn.features import TrainingSample, Features
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.types import (
     Solution,
     LearningSolveStats,

miplearn/features.py

@@ -11,7 +11,7 @@ from miplearn.types import VarIndex, Solution
 
 if TYPE_CHECKING:
     from miplearn.solvers.internal import InternalSolver
-    from miplearn.instance import Instance
+    from miplearn.instance.base import Instance
 
 
 @dataclass

miplearn/instance/__init__.py

@@ -0,0 +1,3 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.

miplearn/instance/base.py

@@ -2,12 +2,9 @@
 #  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-import gzip
 import logging
-import os
-import pickle
 from abc import ABC, abstractmethod
-from typing import Any, List, Optional, Hashable, IO, cast
+from typing import Any, List, Optional, Hashable
 
 from miplearn.features import TrainingSample, Features
 from miplearn.types import VarIndex
@@ -15,29 +12,11 @@ from miplearn.types import VarIndex
 logger = logging.getLogger(__name__)
 
 
-def write_pickle_gz(obj: Any, filename: str) -> None:
-    logger.info(f"Writing: {filename}")
-    os.makedirs(os.path.dirname(filename), exist_ok=True)
-    with gzip.GzipFile(filename, "wb") as file:
-        pickle.dump(obj, cast(IO[bytes], file))
-
-
-def read_pickle_gz(filename: str) -> Any:
-    logger.info(f"Reading: {filename}")
-    with gzip.GzipFile(filename, "rb") as file:
-        return pickle.load(cast(IO[bytes], file))
-
-
-def write_pickle_gz_multiple(objs: List[Any], dirname: str) -> None:
-    for (i, obj) in enumerate(objs):
-        write_pickle_gz(obj, f"{dirname}/{i:05d}.pkl.gz")
-
-
 # noinspection PyMethodMayBeStatic
 class Instance(ABC):
     """
     Abstract class holding all the data necessary to generate a concrete model of the
-    problem.
+    proble.
 
     In the knapsack problem, for example, this class could hold the number of items,
     their weights and costs, as well as the size of the knapsack. Objects
@@ -184,111 +163,3 @@ class Instance(ABC):
         Save any pending changes made to the instance to the underlying data store.
         """
         pass
-
-
-def lazy_load(func):
-    def inner(self, *args):
-        if self.instance is None:
-            self.instance = self._load()
-            self.features = self.instance.features
-            self.training_data = self.instance.training_data
-        return func(self, *args)
-
-    return inner
-
-
-class PickleGzInstance(Instance):
-    """
-    An instance backed by a gzipped pickle file.
-
-    The instance is only loaded to memory after an operation is called (for example,
-    `to_model`).
-
-    Parameters
-    ----------
-    filename: str
-        Path of the gzipped pickle file that should be loaded.
-    """
-
-    # noinspection PyMissingConstructor
-    def __init__(self, filename: str) -> None:
-        assert os.path.exists(filename), f"File not found: {filename}"
-        self.instance: Optional[Instance] = None
-        self.filename: str = filename
-
-    @lazy_load
-    def to_model(self) -> Any:
-        assert self.instance is not None
-        return self.instance.to_model()
-
-    @lazy_load
-    def get_instance_features(self) -> List[float]:
-        assert self.instance is not None
-        return self.instance.get_instance_features()
-
-    @lazy_load
-    def get_variable_features(self, var_name: str, index: VarIndex) -> List[float]:
-        assert self.instance is not None
-        return self.instance.get_variable_features(var_name, index)
-
-    @lazy_load
-    def get_variable_category(
-        self,
-        var_name: str,
-        index: VarIndex,
-    ) -> Optional[Hashable]:
-        assert self.instance is not None
-        return self.instance.get_variable_category(var_name, index)
-
-    @lazy_load
-    def get_constraint_features(self, cid: str) -> Optional[List[float]]:
-        assert self.instance is not None
-        return self.instance.get_constraint_features(cid)
-
-    @lazy_load
-    def get_constraint_category(self, cid: str) -> Optional[Hashable]:
-        assert self.instance is not None
-        return self.instance.get_constraint_category(cid)
-
-    @lazy_load
-    def has_static_lazy_constraints(self) -> bool:
-        assert self.instance is not None
-        return self.instance.has_static_lazy_constraints()
-
-    @lazy_load
-    def has_dynamic_lazy_constraints(self):
-        assert self.instance is not None
-        return self.instance.has_dynamic_lazy_constraints()
-
-    @lazy_load
-    def is_constraint_lazy(self, cid: str) -> bool:
-        assert self.instance is not None
-        return self.instance.is_constraint_lazy(cid)
-
-    @lazy_load
-    def find_violated_lazy_constraints(self, model):
-        assert self.instance is not None
-        return self.instance.find_violated_lazy_constraints(model)
-
-    @lazy_load
-    def build_lazy_constraint(self, model, violation):
-        assert self.instance is not None
-        return self.instance.build_lazy_constraint(model, violation)
-
-    @lazy_load
-    def find_violated_user_cuts(self, model):
-        assert self.instance is not None
-        return self.instance.find_violated_user_cuts(model)
-
-    @lazy_load
-    def build_user_cut(self, model, violation):
-        assert self.instance is not None
-        return self.instance.build_user_cut(model, violation)
-
-    def _load(self) -> Instance:
-        obj = read_pickle_gz(self.filename)
-        assert isinstance(obj, Instance)
-        return obj
-
-    def flush(self) -> None:
-        write_pickle_gz(self.instance, self.filename)

miplearn/instance/picklegz.py

@@ -0,0 +1,137 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+import gzip
+import os
+import pickle
+from typing import Optional, Any, List, Hashable, cast, IO
+
+from miplearn.instance.base import logger, Instance
+from miplearn.types import VarIndex
+
+
+def lazy_load(func):
+    def inner(self, *args):
+        if self.instance is None:
+            self.instance = self._load()
+            self.features = self.instance.features
+            self.training_data = self.instance.training_data
+        return func(self, *args)
+
+    return inner
+
+
+class PickleGzInstance(Instance):
+    """
+    An instance backed by a gzipped pickle file.
+
+    The instance is only loaded to memory after an operation is called (for example,
+    `to_model`).
+
+    Parameters
+    ----------
+    filename: str
+        Path of the gzipped pickle file that should be loaded.
+    """
+
+    # noinspection PyMissingConstructor
+    def __init__(self, filename: str) -> None:
+        assert os.path.exists(filename), f"File not found: {filename}"
+        self.instance: Optional[Instance] = None
+        self.filename: str = filename
+
+    @lazy_load
+    def to_model(self) -> Any:
+        assert self.instance is not None
+        return self.instance.to_model()
+
+    @lazy_load
+    def get_instance_features(self) -> List[float]:
+        assert self.instance is not None
+        return self.instance.get_instance_features()
+
+    @lazy_load
+    def get_variable_features(self, var_name: str, index: VarIndex) -> List[float]:
+        assert self.instance is not None
+        return self.instance.get_variable_features(var_name, index)
+
+    @lazy_load
+    def get_variable_category(
+        self,
+        var_name: str,
+        index: VarIndex,
+    ) -> Optional[Hashable]:
+        assert self.instance is not None
+        return self.instance.get_variable_category(var_name, index)
+
+    @lazy_load
+    def get_constraint_features(self, cid: str) -> Optional[List[float]]:
+        assert self.instance is not None
+        return self.instance.get_constraint_features(cid)
+
+    @lazy_load
+    def get_constraint_category(self, cid: str) -> Optional[Hashable]:
+        assert self.instance is not None
+        return self.instance.get_constraint_category(cid)
+
+    @lazy_load
+    def has_static_lazy_constraints(self) -> bool:
+        assert self.instance is not None
+        return self.instance.has_static_lazy_constraints()
+
+    @lazy_load
+    def has_dynamic_lazy_constraints(self):
+        assert self.instance is not None
+        return self.instance.has_dynamic_lazy_constraints()
+
+    @lazy_load
+    def is_constraint_lazy(self, cid: str) -> bool:
+        assert self.instance is not None
+        return self.instance.is_constraint_lazy(cid)
+
+    @lazy_load
+    def find_violated_lazy_constraints(self, model):
+        assert self.instance is not None
+        return self.instance.find_violated_lazy_constraints(model)
+
+    @lazy_load
+    def build_lazy_constraint(self, model, violation):
+        assert self.instance is not None
+        return self.instance.build_lazy_constraint(model, violation)
+
+    @lazy_load
+    def find_violated_user_cuts(self, model):
+        assert self.instance is not None
+        return self.instance.find_violated_user_cuts(model)
+
+    @lazy_load
+    def build_user_cut(self, model, violation):
+        assert self.instance is not None
+        return self.instance.build_user_cut(model, violation)
+
+    def _load(self) -> Instance:
+        obj = read_pickle_gz(self.filename)
+        assert isinstance(obj, Instance)
+        return obj
+
+    def flush(self) -> None:
+        write_pickle_gz(self.instance, self.filename)
+
+
+def write_pickle_gz(obj: Any, filename: str) -> None:
+    logger.info(f"Writing: {filename}")
+    os.makedirs(os.path.dirname(filename), exist_ok=True)
+    with gzip.GzipFile(filename, "wb") as file:
+        pickle.dump(obj, cast(IO[bytes], file))
+
+
+def read_pickle_gz(filename: str) -> Any:
+    logger.info(f"Reading: {filename}")
+    with gzip.GzipFile(filename, "rb") as file:
+        return pickle.load(cast(IO[bytes], file))
+
+
+def write_pickle_gz_multiple(objs: List[Any], dirname: str) -> None:
+    for (i, obj) in enumerate(objs):
+        write_pickle_gz(obj, f"{dirname}/{i:05d}.pkl.gz")

miplearn/problems/knapsack.py

@@ -8,7 +8,7 @@ import pyomo.environ as pe
 from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 
 
 class ChallengeA:

miplearn/problems/stab.py

@@ -8,7 +8,7 @@ import pyomo.environ as pe
 from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 
 
 class ChallengeA:

miplearn/problems/tsp.py

@@ -9,7 +9,7 @@ from scipy.spatial.distance import pdist, squareform
 from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 
 
 class ChallengeA:

miplearn/solvers/gurobi.py

@@ -8,7 +8,7 @@ from io import StringIO
 from random import randint
 from typing import List, Any, Dict, Optional, cast, Tuple, Union
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.solvers import _RedirectOutput
 from miplearn.solvers.internal import (
     InternalSolver,

miplearn/solvers/internal.py

@@ -6,7 +6,7 @@ import logging
 from abc import ABC, abstractmethod
 from typing import Any, Dict, List, Optional
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.types import (
     LPSolveStats,
     IterationCallback,

miplearn/solvers/learning.py

@@ -14,7 +14,8 @@ from miplearn.components.dynamic_user_cuts import UserCutsComponent
 from miplearn.components.objective import ObjectiveValueComponent
 from miplearn.components.primal import PrimalSolutionComponent
 from miplearn.features import FeaturesExtractor, TrainingSample
-from miplearn.instance import Instance, PickleGzInstance
+from miplearn.instance.base import Instance
+from miplearn.instance.picklegz import PickleGzInstance
 from miplearn.solvers import _RedirectOutput
 from miplearn.solvers.internal import InternalSolver
 from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver

miplearn/solvers/pyomo/base.py

@@ -14,7 +14,7 @@ from pyomo.core import Var, Constraint
 from pyomo.opt import TerminationCondition
 from pyomo.opt.base.solvers import SolverFactory
 
-from miplearn.instance import Instance
+from miplearn.instance.base import Instance
 from miplearn.solvers import _RedirectOutput
 from miplearn.solvers.internal import (
     InternalSolver,