Re-add sample.{get,put}_bytes

miplearn/features/sample.py

@@ -70,7 +70,9 @@ class Sample(ABC):
         assert False, f"scalar expected; found instead: {value} ({value.__class__})"
 
     def _assert_is_array(self, value: np.ndarray) -> None:
-        assert isinstance(value, np.ndarray)
+        assert isinstance(
+            value, np.ndarray
+        ), f"np.ndarray expected; found instead: {value.__class__}"
         assert value.dtype.kind in "biufS", f"Unsupported dtype: {value.dtype}"
 
     def _assert_is_sparse(self, value: Any) -> None:
@@ -205,3 +207,18 @@ class Hdf5Sample(Sample):
         assert col is not None
         assert data is not None
         return coo_matrix((data, (row, col)))
+
+    def get_bytes(self, key: str) -> Optional[Bytes]:
+        if key not in self.file:
+            return None
+        ds = self.file[key]
+        assert (
+            len(ds.shape) == 1
+        ), f"1-dimensional array expected; found shape {ds.shape}"
+        return ds[()].tobytes()
+
+    def put_bytes(self, key: str, value: Bytes) -> None:
+        assert isinstance(
+            value, (bytes, bytearray)
+        ), f"bytes expected; found: {value.__class__}"  # type: ignore
+        self.put_array(key, np.frombuffer(value, dtype="uint8"))

miplearn/instance/file.py

@@ -111,14 +111,16 @@ class FileInstance(Instance):
     def load(self) -> None:
         if self.instance is not None:
             return
-        self.instance = pickle.loads(self.h5.get_array("pickled").tobytes())
+        pkl = self.h5.get_bytes("pickled")
+        assert pkl is not None
+        self.instance = pickle.loads(pkl)
         assert isinstance(self.instance, Instance)
 
     @classmethod
     def save(cls, instance: Instance, filename: str) -> None:
         h5 = Hdf5Sample(filename, mode="w")
-        instance_pkl = np.frombuffer(pickle.dumps(instance), dtype=np.int8)
+        instance_pkl = pickle.dumps(instance)
-        h5.put_array("pickled", instance_pkl)
+        h5.put_bytes("pickled", instance_pkl)
 
     @overrides
     def create_sample(self) -> Sample:

miplearn/solvers/tests/__init__.py

@@ -275,7 +275,7 @@ def _equals_preprocess(obj: Any) -> Any:
             return np.round(obj, decimals=6).tolist()
         else:
             return obj.tolist()
-    elif isinstance(obj, (int, str, bool, np.bool_, np.bytes_, bytes)):
+    elif isinstance(obj, (int, str, bool, np.bool_, np.bytes_, bytes, bytearray)):
         return obj
     elif isinstance(obj, float):
         return round(obj, 6)

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 Hdf5Sample
+from miplearn.features.sample import Hdf5Sample, MemorySample
 from miplearn.instance.base import Instance
 from miplearn.solvers.gurobi import GurobiSolver
 from miplearn.solvers.internal import Variables, Constraints