readme and .ane()

README.md

@@ -89,7 +89,17 @@ from tinygrad.tensor import Tensor
 
 ### ANE Support?!?!
 
-So it doesn't work yet, but see the `ane` directory for code to use the Apple Neural Engine at a low level.
+If you all want to do is ReLU, you are in luck! You can do very fast ReLU (fastness not confirmed)
+
+Requires your Python to be signed with `ane/lib/sign_python.sh` to add the `com.apple.ane.iokit-user-access` entitlement.
+
+```python
+from tinygrad.tensor import Tensor
+
+a = Tensor([-2,-1,0,1,2]).ane()
+b = a.relu()
+print(b.cpu())
+```
 
 ### ImageNet inference
 

examples/use_ane.py

@@ -2,7 +2,7 @@
 import numpy as np
 from tinygrad.tensor import Tensor
 
-a = Tensor([-2,-1,0,1,2]).ane_()
+a = Tensor([-2,-1,0,1,2]).ane()
 print(a.cpu())
 b = a.relu()
 print(b.cpu())

tinygrad/tensor.py

@@ -200,14 +200,12 @@ class Tensor:
     else:
       return self
 
-  def ane_(self):
+  def ane(self):
     assert(not self.gpu)
     require_init_ane()
-    self.device = Tensor.ANE
     ndata = ane.tensor(self.shape)
     ndata.data()[:] = self.data
-    self.data = ndata
-    return self
+    return Tensor(ndata)
 
   def detach(self):
     return Tensor(self.data, self.gpu)