Fixed U-PCFGs prediction

Author: Theomat

examples/pbe/model_prediction.py

@@ -20,6 +20,7 @@
 from synth.filter import add_dfta_constraints
 from synth.syntax import CFG, UCFG, ProbDetGrammar, ProbUGrammar, DSL, Type
 from synth.utils import load_object, save_object
+from synth.utils.data_storage import legacy_save_object
 
 
 parser = argparse.ArgumentParser(
@@ -187,7 +188,10 @@ def produce_pcfgs(
     # ================================
     def save_pcfgs() -> None:
         print("Saving PCFGs...", end="")
-        save_object(file, pcfgs)
+        if constrained:
+            legacy_save_object(file, pcfgs)
+        else:
+            save_object(file, pcfgs, compress_level=9)
         print("done!")
 
     atexit.register(save_pcfgs)

examples/pbe/solve.py

@@ -34,6 +34,7 @@
 from synth.syntax.program import Program
 from synth.task import Task
 from synth.utils import load_object
+from synth.utils.data_storage import legacy_load_object
 from synth.utils.import_utils import import_file_function
 from synth.pbe.solvers import (
     NaivePBESolver,
@@ -296,7 +297,10 @@ def load_pcfgs(
     pcfg_file: Optional[str],
 ) -> Union[List[ProbDetGrammar], List[ProbUGrammar]]:
     if pcfg_file is not None:
-        return load_object(pcfg_file)
+        if constrained:
+            return legacy_load_object(pcfg_file)
+        else:
+            return load_object(pcfg_file)
     pcfgs = []
     for task in full_dataset:
         constant_types = set()

synth/utils/data_storage.py

@@ -29,3 +29,26 @@ def save_object(
         if optimize:
             content = pickletools.optimize(content)
         fd.write(content)
+
+
+
+def legacy_load_object(
+    path: str, **kwargs: Any
+) -> Any:
+    """
+    DEPRECATED
+    Load an arbitrary object from the specified file.
+    """
+    with open(path, "rb") as fd:
+        return pickle.load(fd)
+
+
+def legacy_save_object(
+    path: str, obj: Any, **kwargs: Any
+) -> None:
+    """
+    DEPRECATED
+    Save an arbitrary object to the specified path.
+    """
+    with open(path, "wb") as fd:
+        pickle.dump(obj, fd)