diff --git a/tinygrad/ops/ops_gpu.py b/tinygrad/ops/ops_gpu.py
index 9fb52b2f83..c3cf5ed06b 100644
--- a/tinygrad/ops/ops_gpu.py
+++ b/tinygrad/ops/ops_gpu.py
@@ -1,2 +1,2 @@
 from ..mlops import *
-#Buffer = select_llops("opencl")
+Buffer = select_llops("opencl")
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index bbf7da116c..601c2602fb 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -370,6 +370,16 @@ class Function:
     self.requires_grad = any(t.requires_grad for t in tensors)
     self.saved_tensors = []
 
+  @property
+  def op(f):
+    # uhhh, obviously stupid
+    if f.device == 0:
+      return importlib.import_module(f".cpu", f"tinygrad.llops")
+    elif f.device == 1:
+      return importlib.import_module(f".opencl", f"tinygrad.llops")
+    elif f.device == 2:
+      return importlib.import_module(f".torch", f"tinygrad.llops")
+
   def save_for_backward(self, *x):
     if self.requires_grad:
       self.saved_tensors.extend(x)
@@ -400,7 +410,6 @@ def register(name, fxn, device=Device.CPU):
     x = [Tensor(np.array([arg], dtype=tt.dtype), device=tt.device, requires_grad=False) if not isinstance(arg, Tensor) else arg for arg in x]
     f = Tensor.ops[tt.device][name]
     f.device = tt.device
-    f.op = importlib.import_module(f".cpu", f"tinygrad.llops")
     return f.apply(f, *x, **kwargs)
   if getattr(Tensor, name, None) is not None:
     setattr(Tensor, "_"+name, dispatch)