Re-enable half-precision; minor changes to FeaturesExtractor benchmark

miplearn/features/sample.py

@@ -174,6 +174,8 @@ class Hdf5Sample(Sample):
         if value is None:
             return
         self._assert_is_array(value)
+        if len(value.shape) > 1 and value.dtype.kind == "f":
+            value = value.astype("float16")
         if key in self.file:
             del self.file[key]
         return self.file.create_dataset(key, data=value, compression="gzip")

tests/features/test_extractor.py

@@ -11,7 +11,7 @@ import numpy as np
 import gurobipy as gp
 
 from miplearn.features.extractor import FeaturesExtractor
-from miplearn.features.sample import MemorySample, Hdf5Sample
+from miplearn.features.sample import Hdf5Sample
 from miplearn.instance.base import Instance
 from miplearn.solvers.gurobi import GurobiSolver
 from miplearn.solvers.internal import Variables, Constraints
@@ -382,17 +382,17 @@ class MpsInstance(Instance):
         return gp.read(self.filename)
 
 
-if __name__ == "__main__":
+def main() -> None:
     solver = GurobiSolver()
     instance = MpsInstance(sys.argv[1])
     solver.set_instance(instance)
-    lp_stats = solver.solve_lp(tee=True)
     extractor = FeaturesExtractor(with_lhs=False)
     sample = Hdf5Sample("tmp/prof.h5", mode="w")
-
-    def run() -> None:
     extractor.extract_after_load_features(instance, solver, sample)
+    lp_stats = solver.solve_lp(tee=True)
     extractor.extract_after_lp_features(solver, sample, lp_stats)
 
-    cProfile.run("run()", filename="tmp/prof")
+
+if __name__ == "__main__":
+    cProfile.run("main()", filename="tmp/prof")
     os.system("flameprof tmp/prof > tmp/prof.svg")