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Rename features.variables to variables_old; update FeatureExtractor

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This commit is contained in:
Alinson S. Xavier
2021-04-15 06:54:27 -05:00
parent 08f0bedbe0
commit fec0113722
9 changed files with 150 additions and 173 deletions
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26
miplearn/components/primal.py
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@@ -104,7 +104,7 @@ class PrimalSolutionComponent(Component):
def sample_predict(self, sample: Sample) -> Solution:
assert sample.after_load is not None
assert sample.after_load.variables is not None
assert sample.after_load.variables_old is not None
# Compute y_pred
x, _ = self.sample_xy(None, sample)
@@ -125,9 +125,9 @@ class PrimalSolutionComponent(Component):
).T
# Convert y_pred into solution
solution: Solution = {v: None for v in sample.after_load.variables.keys()}
solution: Solution = {v: None for v in sample.after_load.variables_old.keys()}
category_offset: Dict[Hashable, int] = {cat: 0 for cat in x.keys()}
for (var_name, var_features) in sample.after_load.variables.items():
for (var_name, var_features) in sample.after_load.variables_old.items():
category = var_features.category
if category not in category_offset:
continue
@@ -150,8 +150,8 @@ class PrimalSolutionComponent(Component):
y: Dict = {}
assert sample.after_load is not None
assert sample.after_load.instance is not None
assert sample.after_load.variables is not None
for (var_name, var) in sample.after_load.variables.items():
assert sample.after_load.variables_old is not None
for (var_name, var) in sample.after_load.variables_old.items():
# Initialize categories
category = var.category
if category is None:
@@ -162,17 +162,17 @@ class PrimalSolutionComponent(Component):
# Features
features = list(sample.after_load.instance.to_list())
features.extend(sample.after_load.variables[var_name].to_list())
features.extend(sample.after_load.variables_old[var_name].to_list())
if sample.after_lp is not None:
assert sample.after_lp.variables is not None
features.extend(sample.after_lp.variables[var_name].to_list())
assert sample.after_lp.variables_old is not None
features.extend(sample.after_lp.variables_old[var_name].to_list())
x[category].append(features)
# Labels
if sample.after_mip is not None:
assert sample.after_mip.variables is not None
assert sample.after_mip.variables[var_name] is not None
opt_value = sample.after_mip.variables[var_name].value
assert sample.after_mip.variables_old is not None
assert sample.after_mip.variables_old[var_name] is not None
opt_value = sample.after_mip.variables_old[var_name].value
assert opt_value is not None
assert 0.0 - 1e-5 <= opt_value <= 1.0 + 1e-5, (
f"Variable {var_name} has non-binary value {opt_value} in the "
@@ -190,9 +190,9 @@ class PrimalSolutionComponent(Component):
sample: Sample,
) -> Dict[Hashable, Dict[str, float]]:
assert sample.after_mip is not None
assert sample.after_mip.variables is not None
assert sample.after_mip.variables_old is not None
solution_actual = sample.after_mip.variables
solution_actual = sample.after_mip.variables_old
solution_pred = self.sample_predict(sample)
vars_all, vars_one, vars_zero = set(), set(), set()
pred_one_positive, pred_zero_positive = set(), set()