[Dynamo] Handle extracted unbound tensor methods (#137227)

fixes2

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137227
Approved by: https://github.com/williamwen42, https://github.com/anijain2305
ghstack dependencies: #137114, #137115, #137116, #137117, #137120

test/dynamo/test_functions.py

@@ -938,6 +938,16 @@ class FunctionTests(torch._dynamo.test_case.TestCase):
         else:
             return x - 1
 
+    @make_test
+    def test_tensor_size(x):
+        fn = torch.Tensor.size
+        return fn(x + 1)
+
+    @make_test
+    def test_tensor_dim(x):
+        fn = torch.Tensor.dim
+        return fn(x + 1)
+
     @make_test
     def test_tensor_is_inference(x):
         if x.is_inference():

torch/_dynamo/variables/tensor.py

@@ -772,7 +772,7 @@ class TensorVariable(VariableTracker):
             self._warn_capture_scalar_outputs()
             unimplemented("Tensor.item")
 
-    def method_getitem(self, *args, **kwargs):
+    def method___getitem__(self, *args, **kwargs):
         from ..symbolic_convert import InstructionTranslator
         from .builder import wrap_fx_proxy
 

torch/_dynamo/variables/torch.py

@@ -871,10 +871,6 @@ class TorchInGraphFunctionVariable(BaseTorchVariable):
 
             return ConstantVariable.create(None)
 
-        @register(torch._C.TensorBase.__getitem__)
-        def handle_getitem(self, tx: "InstructionTranslator", *args, **kwargs):
-            return args[0].call_method(tx, "getitem", args[1:], kwargs)
-
         return handlers
 
     def call_function(
@@ -904,6 +900,9 @@ class TorchInGraphFunctionVariable(BaseTorchVariable):
                 ),
             )
 
+        if self.is_tensor_method():
+            return self.call_tensor_method(tx, args, kwargs)
+
         special_handler = self._get_handlers().get(self.value)
         if special_handler:
             result = special_handler(self, tx, *args, **kwargs)
@@ -1176,6 +1175,16 @@ Either create the tensor outside the compiled region, or do not set the tensor t
         )
         return result
 
+    def call_tensor_method(self, tx, args, kwargs):
+        return args[0].call_method(tx, self.get_function().__name__, args[1:], kwargs)
+
+    def is_tensor_method(self):
+        return (
+            inspect.ismethoddescriptor(self.get_function())
+            and hasattr(self.get_function(), "__objclass__")
+            and self.get_function().__objclass__ == torch._C.TensorBase
+        )
+
     def torch_function_override_enabled(self, tx, args, kwargs):
         return (
             self.get_function() in get_overridable_functions()