Rename func (#95639)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95639
Approved by: https://github.com/ezyang
diff --git a/torch/_dynamo/guards.py b/torch/_dynamo/guards.py
index f36d5e8..0add0c1 100644
--- a/torch/_dynamo/guards.py
+++ b/torch/_dynamo/guards.py
@@ -36,7 +36,7 @@
     np,
     orig_code_map,
     rename_implicit,
-    tensor_shape_should_be_static,
+    tensor_always_has_static_shape,
     tensor_static_reason_to_message,
     tuple_iterator_getitem,
     tuple_iterator_len,
@@ -501,7 +501,7 @@
             # as an empty set is a safe degeneration - that is, a strictly static tensor is always valid for a frame
             # compiled with that same
             # tensor + more onerous user directives.
-            static, reason = tensor_shape_should_be_static(
+            static, reason = tensor_always_has_static_shape(
                 value, guard.source, is_tensor=True
             )
             if not static:
diff --git a/torch/_dynamo/utils.py b/torch/_dynamo/utils.py
index 0fb798a..7e28b6b 100644
--- a/torch/_dynamo/utils.py
+++ b/torch/_dynamo/utils.py
@@ -1346,7 +1346,7 @@
     raise AssertionError(f"Illegal reason {reason}")
 
 
-def tensor_shape_should_be_static(
+def tensor_always_has_static_shape(
     tensor: Union[torch.Tensor, Any], source: Optional["Source"], is_tensor: bool
 ) -> Tuple[bool, TensorStaticReason]:
     """
diff --git a/torch/_dynamo/variables/builder.py b/torch/_dynamo/variables/builder.py
index 1bee600..173d5d4 100644
--- a/torch/_dynamo/variables/builder.py
+++ b/torch/_dynamo/variables/builder.py
@@ -47,7 +47,7 @@
     np,
     odict_values,
     preserve_rng_state,
-    tensor_shape_should_be_static,
+    tensor_always_has_static_shape,
     tensor_static_reason_to_message,
     tuple_iterator,
     tuple_iterator_getitem,
@@ -1063,7 +1063,7 @@
     if type(e) in (torch.Tensor, torch.nn.Parameter) or (
         ignore_subclass and isinstance(e, torch.Tensor)
     ):
-        static_shapes, reason = tensor_shape_should_be_static(e, source, is_tensor)
+        static_shapes, reason = tensor_always_has_static_shape(e, source, is_tensor)
 
         fake_e = wrap_fake_exception(
             lambda: tx.fake_mode.from_tensor(