Minor changes to docstrings

miplearn/components/component.py

@@ -6,6 +6,10 @@
 class Component:
     """
     A Component is an object which adds functionality to a LearningSolver.
+
+    For better code maintainability, LearningSolver simply delegates most of its
+    functionality to Components. Each Component is responsible for exactly one ML
+    strategy.
     """
 
     def before_solve(self, solver, instance, model):

miplearn/solvers/learning.py

@@ -23,7 +23,6 @@ from .pyomo.gurobi import GurobiPyomoSolver
 
 logger = logging.getLogger(__name__)
 
-
 # Global memory for multiprocessing
 SOLVER = [None]  # type: List[Optional[LearningSolver]]
 INSTANCES = [None]  # type: List[Optional[dict]]
@@ -45,18 +44,6 @@ def _parallel_solve(idx):
 
 
 class LearningSolver:
-    def __init__(
-        self,
-        components=None,
-        gap_tolerance=1e-4,
-        mode="exact",
-        solver="gurobi",
-        threads=None,
-        time_limit=None,
-        node_limit=None,
-        solve_lp_first=True,
-        use_lazy_cb=False,
-    ):
     """
     Mixed-Integer Linear Programming (MIP) solver that extracts information
     from previous runs and uses Machine Learning methods to accelerate the
@@ -75,7 +62,7 @@ class LearningSolver:
     mode
         If "exact", solves problem to optimality, keeping all optimality
         guarantees provided by the MIP solver. If "heuristic", uses machine
-            learning more agressively, and may return suboptimal solutions.
+        learning more aggressively, and may return suboptimal solutions.
     solver
         The internal MIP solver to use. Can be either "cplex", "gurobi", a
         solver class such as GurobiSolver, or a solver instance such as
@@ -97,6 +84,19 @@ class LearningSolver:
         expensive to solve and if it provides good hints for the integer
         solution.
     """
+
+    def __init__(
+        self,
+        components=None,
+        gap_tolerance=1e-4,
+        mode="exact",
+        solver="gurobi",
+        threads=None,
+        time_limit=None,
+        node_limit=None,
+        solve_lp_first=True,
+        use_lazy_cb=False,
+    ):
         self.components = {}
         self.mode = mode
         self.internal_solver = None