diff --git a/pyproject.toml b/pyproject.toml
index 9e1d84a..04cde8e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "finch-tensor"
-version = "0.2.0"
+version = "0.2.1"
 description = ""
 authors = ["Willow Ahrens <willow.marie.ahrens@gmail.com>"]
 readme = "README.md"
diff --git a/src/finch/__init__.py b/src/finch/__init__.py
index 1cff467..8ebf847 100644
--- a/src/finch/__init__.py
+++ b/src/finch/__init__.py
@@ -156,6 +156,8 @@
     "SparseHash",
     "Storage",
     "DenseStorage",
+    "DefaultScheduler",
+    "GalleyScheduler",
     "asarray",
     "astype",
     "random",
@@ -269,6 +271,7 @@
     "empty_like",
     "arange",
     "linspace",
+    "set_optimizer",
 ]
 
 __array_api_version__: str = "2023.12"
diff --git a/src/finch/compiled.py b/src/finch/compiled.py
index 2b7eb6b..6c757dd 100644
--- a/src/finch/compiled.py
+++ b/src/finch/compiled.py
@@ -4,23 +4,23 @@
 from .tensor import Tensor
 
 
-def compiled(opt=""):
-    def inner(func):  
-        @wraps(func)  
-        def wrapper_func(*args, **kwargs):  
-            new_args = []  
-            for arg in args:  
-                if isinstance(arg, Tensor) and not jl.isa(arg._obj, jl.Finch.LazyTensor):  
-                    new_args.append(Tensor(jl.Finch.LazyTensor(arg._obj)))  
+def compiled(opt=None):
+    def inner(func):
+        @wraps(func)
+        def wrapper_func(*args, **kwargs):
+            new_args = []
+            for arg in args:
+                if isinstance(arg, Tensor) and not jl.isa(arg._obj, jl.Finch.LazyTensor):
+                    new_args.append(Tensor(jl.Finch.LazyTensor(arg._obj)))
                 else:  
-                    new_args.append(arg)  
-            result = func(*new_args, **kwargs)  
-            kwargs = {"ctx": get_scheduler(name=opt)} if opt != "" else {}  
-            result_tensor = Tensor(jl.Finch.compute(result._obj, **kwargs))  
-            return result_tensor  
-        return wrapper_func  
-
-    return inner  
+                    new_args.append(arg)
+            result = func(*new_args, **kwargs)
+            kwargs = {"ctx": opt.get_julia_scheduler()} if opt is not None else {}
+            result_tensor = Tensor(jl.Finch.compute(result._obj, **kwargs))
+            return result_tensor
+        return wrapper_func
+
+    return inner
 
 def lazy(tensor: Tensor):
     if tensor.is_computed():