Update on "Evaluate symexprs on load path of cache not write"

When caching is enabled, an internal model fails with
```
assert_size_stride(bmm_9, (17, s0, 512), (54784, 512, 1))
AssertionError: expected size 17==17, stride 57344==54784 at dim=0
```
looking at this model, the exact problem is when the cache is hit on the forward graph, the generated code for backward fails since the strides of the outputs of forward, passed to backward as inputs, are not what we expected.

This PR changes the evaluation logic so that we defer evaluation of output stride exprs to load path as opposed to eagerly doing it on save path.

I have not been able to come up with a unit test repro for this problem.

cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx peterbell10 ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang

[ghstack-poisoned]

torch/_inductor/compile_fx.py

@@ -567,14 +567,12 @@ def compile_fx_inner(
     if context is not None and context.output_strides is not None:
         assert len(context.output_strides) == 0
         shape_env = _shape_env_from_inputs(example_inputs)
-        V.graph.sizevars = SizeVarAllocator(shape_env)
+        sizevars = SizeVarAllocator(shape_env)
         for exprs in compiled_graph.output_strides:
             if exprs is None:
                 context.output_strides.append(None)
             else:
-                context.output_strides.append(
-                    tuple(V.graph.sizevars.size_hint(s) for s in exprs)
-                )
+                context.output_strides.append([sizevars.size_hint(s) for s in exprs])
 
     if aot_mode:
         return compiled_graph