PyomoSolver: remove duplicated docstrings

src/python/miplearn/solvers/pyomo.py

@@ -5,7 +5,7 @@
 import logging
 import re
 import sys
-from abc import ABC, abstractmethod
+from abc import abstractmethod
 from io import StringIO
 
 import pyomo
@@ -20,17 +20,6 @@ logger = logging.getLogger(__name__)
 
 
 class PyomoSolver(InternalSolver):
-    """
-    Base class for all Pyomo-based InternalSolvers.
-
-    Attributes
-    ----------
-    instance: miplearn.Instance
-        The MIPLearn instance currently loaded to the solver
-    model: pyomo.core.ConcreteModel
-        The Pyomo model currently loaded on the solver
-    """
-
     def __init__(self):
         self.instance = None
         self.model = None
@@ -42,20 +31,6 @@ class PyomoSolver(InternalSolver):
         self._varname_to_var = {}
 
     def solve_lp(self, tee=False):
-        """
-        Solves the LP relaxation of the currently loaded instance.
-
-        Parameters
-        ----------
-        tee: bool
-            If true, prints the solver log to the screen.
-
-        Returns
-        -------
-        dict
-            A dictionary of solver statistics containing the following keys:
-            "Optimal value".
-        """
         for var in self._bin_vars:
             lb, ub = var.bounds
             var.setlb(lb)
@@ -71,16 +46,6 @@ class PyomoSolver(InternalSolver):
         }
 
     def get_solution(self):
-        """
-        Returns current solution found by the solver.
-
-        If called after `solve`, returns the best primal solution found during
-        the search. If called after `solve_lp`, returns the optimal solution
-        to the LP relaxation.
-
-        The solution is a dictionary `sol`, where the optimal value of `var[idx]`
-        is given by `sol[var][idx]`.
-        """
         solution = {}
         for var in self.model.component_objects(Var):
             solution[str(var)] = {}
@@ -89,14 +54,6 @@ class PyomoSolver(InternalSolver):
         return solution
 
     def set_warm_start(self, solution):
-        """
-        Sets the warm start to be used by the solver.
-
-        The solution should be a dictionary following the same format as the
-        one produced by `get_solution`. Only one warm start is currently
-        supported. Calling this function when a warm start already exists will
-        remove the previous warm start.
-        """
         self.clear_warm_start()
         count_total, count_fixed = 0, 0
         for var_name in solution:
@@ -112,26 +69,12 @@ class PyomoSolver(InternalSolver):
                     (count_fixed, count_total))
 
     def clear_warm_start(self):
-        """
-        Removes any existing warm start from the solver.
-        """
         for var in self._all_vars:
             if not var.fixed:
                 var.value = None
         self._is_warm_start_available = False
 
     def set_instance(self, instance, model=None):
-        """
-        Loads the given instance into the solver.
-
-        Parameters
-        ----------
-        instance: miplearn.Instance
-            The instance to be loaded.
-        model: pyomo.core.ConcreteModel
-            The corresponding Pyomo model. If not provided, it will be
-            generated by calling `instance.to_model()`.
-        """
         if model is None:
             model = instance.to_model()
         assert isinstance(instance, Instance)
@@ -157,13 +100,6 @@ class PyomoSolver(InternalSolver):
                     self._bin_vars += [var[idx]]
 
     def fix(self, solution):
-        """
-        Fixes the values of a subset of decision variables.
-
-        The values should be provided in the dictionary format generated by
-        `get_solution`. Missing values in the solution indicate variables
-        that should be left free.
-        """
         count_total, count_fixed = 0, 0
         for varname in solution:
             for index in solution[varname]:
@@ -178,27 +114,9 @@ class PyomoSolver(InternalSolver):
                     (count_fixed, count_total))
 
     def add_constraint(self, constraint):
-        """
-        Adds a single constraint to the model.
-        """
         self._pyomo_solver.add_constraint(constraint)
 
     def solve(self, tee=False):
-        """
-        Solves the currently loaded instance.
-
-        Parameters
-        ----------
-        tee: bool
-            If true, prints the solver log to the screen.
-
-        Returns
-        -------
-        dict
-            A dictionary of solver statistics containing the following keys:
-            "Lower bound", "Upper bound", "Wallclock time", "Nodes", "Sense",
-             "Log" and "Warm start value".
-        """
         total_wallclock_time = 0
         streams = [StringIO()]
         if tee:
@@ -244,20 +162,12 @@ class PyomoSolver(InternalSolver):
         return value
 
     def _extract_warm_start_value(self, log):
-        """
-        Extracts and returns the objective value of the user-provided MIP start
-        from the provided solver log. If more than one value is found, returns
-        the last one. If no value is present in the logs, returns None.
-        """
         value = self.__extract(log, self._get_warm_start_regexp())
         if value is not None:
             value = float(value)
         return value
 
     def _extract_node_count(self, log):
-        """
-        Extracts and returns the number of explored branch-and-bound nodes.
-        """
         return int(self.__extract(log,
                                   self._get_node_count_regexp(),
                                   default=1))
@@ -301,6 +211,3 @@ class PyomoSolver(InternalSolver):
     @abstractmethod
     def _get_gap_tolerance_option_name(self):
         pass
-
-
-