ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 01:18:52 -06:00
Code Issues Packages Projects Releases Wiki Activity

Remove sample.after_mip

Browse Source
This commit is contained in:
Alinson S. Xavier
2021-07-01 11:45:19 -05:00
parent 7c4c301611
commit 4093ac62fd
8 changed files with 45 additions and 73 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
miplearn/components/objective.py
View File

@@ -95,13 +95,12 @@ class ObjectiveValueComponent(Component):
# Labels
y: Dict[Hashable, List[List[float]]] = {}
if sample.after_mip is not None:
mip_stats = sample.after_mip.mip_solve
assert mip_stats is not None
if mip_stats.mip_lower_bound is not None:
y["Lower bound"] = [[mip_stats.mip_lower_bound]]
if mip_stats.mip_upper_bound is not None:
y["Upper bound"] = [[mip_stats.mip_upper_bound]]
mip_lower_bound = sample.get("mip_lower_bound")
mip_upper_bound = sample.get("mip_upper_bound")
if mip_lower_bound is not None:
y["Lower bound"] = [[mip_lower_bound]]
if mip_upper_bound is not None:
y["Upper bound"] = [[mip_upper_bound]]
return x, y
@@ -111,9 +110,6 @@ class ObjectiveValueComponent(Component):
instance: Instance,
sample: Sample,
) -> Dict[Hashable, Dict[str, float]]:
assert sample.after_mip is not None
assert sample.after_mip.mip_solve is not None
def compare(y_pred: float, y_actual: float) -> Dict[str, float]:
err = np.round(abs(y_pred - y_actual), 8)
return {
@@ -125,8 +121,8 @@ class ObjectiveValueComponent(Component):
result: Dict[Hashable, Dict[str, float]] = {}
pred = self.sample_predict(sample)
actual_ub = sample.after_mip.mip_solve.mip_upper_bound
actual_lb = sample.after_mip.mip_solve.mip_lower_bound
actual_ub = sample.get("mip_upper_bound")
actual_lb = sample.get("mip_lower_bound")
if actual_ub is not None:
result["Upper bound"] = compare(pred["Upper bound"], actual_ub)
if actual_lb is not None:

18
miplearn/components/primal.py
View File

@@ -155,6 +155,7 @@ class PrimalSolutionComponent(Component):
assert sample.after_load.variables is not None
assert sample.after_load.variables.names is not None
assert sample.after_load.variables.categories is not None
mip_var_values = sample.get("mip_var_values")
for (i, var_name) in enumerate(sample.after_load.variables.names):
# Initialize categories
@@ -174,10 +175,8 @@ class PrimalSolutionComponent(Component):
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.values is not None
opt_value = sample.after_mip.variables.values[i]
if mip_var_values is not None:
opt_value = mip_var_values[i]
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 "
@@ -194,14 +193,13 @@ class PrimalSolutionComponent(Component):
_: Optional[Instance],
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.values is not None
assert sample.after_mip.variables.names is not None
mip_var_values = sample.get("mip_var_values")
var_names = sample.get("var_names")
assert mip_var_values is not None
assert var_names is not None
solution_actual = {
var_name: sample.after_mip.variables.values[i]
for (i, var_name) in enumerate(sample.after_mip.variables.names)
var_name: mip_var_values[i] for (i, var_name) in enumerate(var_names)
}
solution_pred = self.sample_predict(sample)
vars_all, vars_one, vars_zero = set(), set(), set()