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Minor changes

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This commit is contained in:
Alinson S. Xavier
2020-01-29 08:36:36 -06:00
parent 5f2e81322c
commit b48dfad3aa
5 changed files with 16 additions and 10 deletions
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4
miplearn/__init__.py
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@@ -6,4 +6,6 @@
from .component import Component from .component import Component
from .instance import Instance from .instance import Instance
from .solvers import LearningSolver from .solvers import LearningSolver
from .benchmark import BenchmarkRunner from .benchmark import BenchmarkRunner
from .warmstart import WarmStartComponent
from .branching import BranchPriorityComponent

12
miplearn/problems/stab.py
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@@ -14,22 +14,22 @@ from scipy.stats.distributions import rv_frozen
class MaxWeightStableSetChallengeA: class MaxWeightStableSetChallengeA:
""" """
- Fixed random graph (200 vertices, 5% density) - Fixed random graph (200 vertices, 5% density)
- Uniformly random weights in the [100., 125.] interval - Random weights ~ U(100., 150.)
- 500 training instances - 300 training instances
- 100 test instances - 50 test instances
""" """
def __init__(self): def __init__(self):
self.generator = MaxWeightStableSetGenerator(w=uniform(loc=100., scale=25.), self.generator = MaxWeightStableSetGenerator(w=uniform(loc=100., scale=50.),
n=randint(low=200, high=201), n=randint(low=200, high=201),
density=uniform(loc=0.05, scale=0.0), density=uniform(loc=0.05, scale=0.0),
fix_graph=True) fix_graph=True)
def get_training_instances(self): def get_training_instances(self):
return self.generator.generate(500) return self.generator.generate(300)
def get_test_instances(self): def get_test_instances(self):
return self.generator.generate(100) return self.generator.generate(50)
class MaxWeightStableSetGenerator: class MaxWeightStableSetGenerator:

2
miplearn/scripts/branchpriority.jl
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@@ -51,7 +51,7 @@ branch_and_bound(mip,
node_limit = 1000, node_limit = 1000,
branch_rule = full_strong_branching_track, branch_rule = full_strong_branching_track,
node_rule = best_bound, node_rule = best_bound,
print_interval = 1) print_interval = 100)
priority = [(pseudocost_count_up[v] == 0 || pseudocost_count_down[v] == 0) ? 0 : priority = [(pseudocost_count_up[v] == 0 || pseudocost_count_down[v] == 0) ? 0 :
(pseudocost_sum_up[v] / pseudocost_count_up[v]) * (pseudocost_sum_up[v] / pseudocost_count_up[v]) *

2
miplearn/solvers.py
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@@ -48,7 +48,7 @@ class LearningSolver:
if mode is not None: if mode is not None:
assert mode in ["exact", "heuristic"] assert mode in ["exact", "heuristic"]
for component in self.components: for component in self.components.values():
component.mode = mode component.mode = mode
def _create_solver(self): def _create_solver(self):

6
miplearn/warmstart.py
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@@ -50,7 +50,7 @@ class WarmStartPredictor(ABC):
class LogisticWarmStartPredictor(WarmStartPredictor): class LogisticWarmStartPredictor(WarmStartPredictor):
def __init__(self, def __init__(self,
min_samples=100, min_samples=100,
thr_fix=[0.99, 0.99], thr_fix=[0.95, 0.95],
thr_balance=[0.95, 0.95], thr_balance=[0.95, 0.95],
thr_score=[0.95, 0.95]): thr_score=[0.95, 0.95]):
super().__init__() super().__init__()
@@ -151,8 +151,12 @@ class WarmStartComponent(Component):
if self.mode == "heuristic": if self.mode == "heuristic":
if ws[i,0] == 1: if ws[i,0] == 1:
var[index].fix(0) var[index].fix(0)
if solver.is_persistent:
solver.internal_solver.update_var(var[index])
elif ws[i,1] == 1: elif ws[i,1] == 1:
var[index].fix(1) var[index].fix(1)
if solver.is_persistent:
solver.internal_solver.update_var(var[index])
else: else:
if ws[i,0] == 1: if ws[i,0] == 1:
var[index].value = 0 var[index].value = 0