FC preparation for int_oo in PyTorch (#3947)

Summary:
Pull Request resolved: #3947

This is needed for pytorch/pytorch#127693 . This code is written so it is compatible before and after this PR.

Reviewed By: mergennachin, clee2000

Differential Revision: D58465158

fbshipit-source-id: ca0f2a79eb07e78ff2887f78eb62ff38eeea3ede

exir/passes/sym_shape_eval_pass.py

@@ -259,6 +259,6 @@ def call(self, graph_module: GraphModule):
                                 "Please use export's constrain_as_size() or constrain_as_value() apis and set a concrete upper bound to resolve this."
                             )
 
-                        spec.shape = concrete_shape  # pyre-ignore[8]: Attribute `stride` declared in class `TensorSpec` has type `Tuple[int]` but is used as type `List[Optional[int]]`
-                        spec.stride = concrete_stride  # pyre-ignore[8]: Attribute `stride` declared in class `TensorSpec` has type `Tuple[int]` but is used as type `List[Optional[int]]`
+                        spec.shape = concrete_shape
+                        spec.stride = concrete_stride  # pyre-ignore[8]: Attribute `stride` declared in class `TensorSpec` has type `Tuple[int]` but is used as type `List[int]`
         return PassResult(graph_module, True)

exir/sym_util.py

@@ -29,7 +29,7 @@ def eval_expr(symint: Union[int, torch.SymInt]) -> Optional[int]:
     return int(output)
 
 
-def eval_upper_bound(maybe_symint: Union[int, torch.SymInt]) -> Optional[int]:
+def eval_upper_bound(maybe_symint: Union[int, torch.SymInt]) -> int:
     """
     Evaluate a symint to its uppper bound value. Returns None if symint's symoblic expr's
     upper bound can not be evaluated to valid integer according to the constraints in shape_env.
@@ -41,17 +41,24 @@ def eval_upper_bound(maybe_symint: Union[int, torch.SymInt]) -> Optional[int]:
     expr = node.expr
     var_range: ValueRanges = bound_sympy(expr, shape_env.var_to_range)
     upper_bound = var_range.upper
+    # This import is needed temporarily until we update the pinned torch version.
+
+    try:
+        from torch.utils._sympy.numbers import int_oo  # @manual  # pyre-ignore
+    except ImportError:
+        int_oo = None
+
     if isinstance(upper_bound, sympy.Integer):
         concrete_upper = int(var_range.upper)
         assert isinstance(
             concrete_upper, int
         ), f"Expect upper bound to be a concrete int but got {concrete_upper}"
         return concrete_upper
-    elif isinstance(upper_bound, sympy.oo):
-        return None
+    elif int_oo is not None and upper_bound is int_oo:  # pyre-ignore
+        return int_oo  # pyre-ignore
     else:
         raise RuntimeError(
-            f"Expect upper bound to be sympy.Integer or sympy.oo. but got {upper_bound}"
+            f"Expect upper bound to be sympy.Integer or int_oo. but got {upper_bound}"
         )