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Convert TrainingSample to dataclass

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This commit is contained in:
Alinson S. Xavier
2021-04-05 20:36:04 -05:00
parent aeed338837
commit b11779817a
15 changed files with 122 additions and 129 deletions
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8
miplearn/components/steps/convert_tight.py
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@@ -95,8 +95,8 @@ class ConvertTightIneqsIntoEqsStep(Component):
features,
training_data,
):
if "slacks" not in training_data.keys():
training_data["slacks"] = solver.internal_solver.get_inequality_slacks()
if training_data.slacks is None:
training_data.slacks = solver.internal_solver.get_inequality_slacks()
stats["ConvertTight: Restored"] = self.n_restored
stats["ConvertTight: Inf iterations"] = self.n_infeasible_iterations
stats["ConvertTight: Subopt iterations"] = self.n_suboptimal_iterations
@@ -120,7 +120,7 @@ class ConvertTightIneqsIntoEqsStep(Component):
disable=len(instances) < 5,
):
for training_data in instance.training_data:
cids = training_data["slacks"].keys()
cids = training_data.slacks.keys()
for cid in cids:
category = instance.get_constraint_category(cid)
if category is None:
@@ -142,7 +142,7 @@ class ConvertTightIneqsIntoEqsStep(Component):
desc="Extract (rlx:conv_ineqs:y)",
disable=len(instances) < 5,
):
for (cid, slack) in instance.training_data[0]["slacks"].items():
for (cid, slack) in instance.training_data[0].slacks.items():
category = instance.get_constraint_category(cid)
if category is None:
continue

6
miplearn/components/steps/drop_redundant.py
View File

@@ -96,8 +96,8 @@ class DropRedundantInequalitiesStep(Component):
features,
training_data,
):
if "slacks" not in training_data.keys():
training_data["slacks"] = solver.internal_solver.get_inequality_slacks()
if training_data.slacks is None:
training_data.slacks = solver.internal_solver.get_inequality_slacks()
stats["DropRedundant: Iterations"] = self.n_iterations
stats["DropRedundant: Restored"] = self.n_restored
@@ -131,7 +131,7 @@ class DropRedundantInequalitiesStep(Component):
x = {}
y = {}
for training_data in instance.training_data:
for (cid, slack) in training_data["slacks"].items():
for (cid, slack) in training_data.slacks.items():
category = instance.get_constraint_category(cid)
if category is None:
continue