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Merge components more efficiently

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This commit is contained in:
Alinson S. Xavier
2020-01-31 11:06:07 -06:00
parent 46e19eed1b
commit 2679522b76
4 changed files with 28 additions and 18 deletions
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7
miplearn/branching.py
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@@ -50,9 +50,10 @@ class BranchPriorityComponent(Component):
pass pass
def merge(self, other): def merge(self, other_components):
if other.priority is not None: for comp in other_components:
self._merge(other.priority) if comp.priority is not None:
self._merge(comp.priority)
def _merge(self, priority): def _merge(self, priority):

2
miplearn/problems/tests/test_knapsack.py
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@@ -66,7 +66,7 @@ def test_knapsack_fixed_weights_jitter():
fix_w=True, fix_w=True,
w_jitter=randint(low=0, high=1001), w_jitter=randint(low=0, high=1001),
) )
instances = gen.generate(1_000) instances = gen.generate(5_000)
w = [instance.weights[0,0] for instance in instances] w = [instance.weights[0,0] for instance in instances]
assert round(np.std(w), -1) == 290. assert round(np.std(w), -1) == 290.
assert round(np.mean(w), -2) == 1500. assert round(np.mean(w), -2) == 1500.

10
miplearn/solvers.py
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@@ -94,12 +94,14 @@ class LearningSolver:
for instance in tqdm(instances, desc=label, ncols=80) for instance in tqdm(instances, desc=label, ncols=80)
) )
solvers = [p[0] for p in solver_result_pairs] subsolvers = [p[0] for p in solver_result_pairs]
results = [p[1] for p in solver_result_pairs] results = [p[1] for p in solver_result_pairs]
for (name, component) in self.components.items(): for (name, component) in self.components.items():
for subsolver in solvers: subcomponents = [subsolver.components[name]
self.components[name].merge(subsolver.components[name]) for subsolver in subsolvers
if name in subsolver.components.keys()]
self.components[name].merge(subcomponents)
return results return results
@@ -122,4 +124,4 @@ class LearningSolver:
if component_name not in self.components.keys(): if component_name not in self.components.keys():
continue continue
else: else:
self.components[component_name].merge(component) self.components[component_name].merge([component])

27
miplearn/warmstart.py
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@@ -180,13 +180,20 @@ class WarmStartComponent(Component):
self.predictors[category] = deepcopy(self.predictor_prototype) self.predictors[category] = deepcopy(self.predictor_prototype)
self.predictors[category].fit(x_train, y_train) self.predictors[category].fit(x_train, y_train)
def merge(self, other): def merge(self, other_components):
for c in other.x_train.keys(): keys = set(self.x_train.keys())
if c not in self.x_train: for comp in other_components:
self.x_train[c] = other.x_train[c] keys = keys.union(set(comp.x_train.keys()))
self.y_train[c] = other.y_train[c]
else: for key in keys:
self.x_train[c] = np.vstack([self.x_train[c], other.x_train[c]]) x_train_submatrices = [comp.x_train[key]
self.y_train[c] = np.vstack([self.y_train[c], other.y_train[c]]) for comp in other_components
if (c in other.predictors.keys()) and (c not in self.predictors.keys()): if key in comp.x_train.keys()]
self.predictors[c] = other.predictors[c] y_train_submatrices = [comp.y_train[key]
for comp in other_components
if key in comp.y_train.keys()]
if key in self.x_train.keys():
x_train_submatrices += [self.x_train[key]]
y_train_submatrices += [self.y_train[key]]
self.x_train[key] = np.vstack(x_train_submatrices)
self.y_train[key] = np.vstack(y_train_submatrices)