Add SymIntToTensorPass in to_edge

Summary:
JacobSzwejbka ran into some issues when lowering to executorch where we
have the following graph:
```
%symfloat_1 = executorch_prim::mul(%symfloat_a, %symfloat_b)
%mul_out = aten::mul.out(%tensor, %symfloat_1, %mul_out, %mul_out)
```
Which errors because mul.out is being passed a symfloat, but mul.out only
accepts 2 tensors. So if we add this pass, the symfloats will be converted to
tensors.

Apparently I wrote this pass back in April but never put it somewhere where it
gets run by default.

Reviewed By: JacobSzwejbka

Differential Revision: D48415403

fbshipit-source-id: 1ce9db145feb8b54a666e38e4f7aefdb1e314a48

Author: angelayi

exir/passes/TARGETS

@@ -25,6 +25,7 @@ python_library(
         ":scalar_to_tensor_pass",
         ":spec_prop_pass",
         ":sym_shape_eval_pass",
+        ":sym_to_tensor_pass",
         "//caffe2:torch",
         "//executorch/exir:common",
         "//executorch/exir:control_flow",
@@ -87,9 +88,9 @@ python_library(
 )
 
 python_library(
-    name = "symint_to_tensor_pass",
+    name = "sym_to_tensor_pass",
     srcs = [
-        "symint_to_tensor_pass.py",
+        "sym_to_tensor_pass.py",
     ],
     deps = [
         "//caffe2:torch",

exir/passes/__init__.py

@@ -52,6 +52,7 @@
 from executorch.exir.passes.scalar_to_tensor_pass import ScalarToTensorPass
 from executorch.exir.passes.spec_prop_pass import SpecPropPass
 from executorch.exir.passes.sym_shape_eval_pass import SymShapeEvalPass
+from executorch.exir.passes.sym_to_tensor_pass import SymToTensorPass
 from torch import fx
 from torch._subclasses import FakeTensor
 from torch.fx.passes.infra.pass_base import PassBase, PassResult
@@ -475,6 +476,7 @@ def dead_code_elimination_pass(graph_module: torch.fx.GraphModule) -> PassResult
         NormalizeTransposePass(),
         ReplaceBrokenOpsWithFunctionalOpsPass(),
         ScalarToTensorPass(),
+        SymToTensorPass(),
         RemoveMixedTypeOperators(),
         RemoveNoopPass(),
         dead_code_elimination_pass,

exir/passes/symint_to_tensor_pass.py renamed to exir/passes/sym_to_tensor_pass.py

@@ -14,7 +14,7 @@
 from torch.utils._pytree import PyTree
 
 
-class SymIntToTensorPass(ExportPass):
+class SymToTensorPass(ExportPass):
     """
     The dispatcher implicitly converts SymInt/SymFloats to tensors, but
     sometimes this doesn't comply with the operator's schema which Executorch

exir/tests/TARGETS

@@ -233,7 +233,7 @@ python_unittest(
         "//executorch/exir/passes:replace_edge_with_backend_pass",
         "//executorch/exir/passes:scalar_to_tensor_pass",
         "//executorch/exir/passes:spec_prop_pass",
-        "//executorch/exir/passes:symint_to_tensor_pass",
+        "//executorch/exir/passes:sym_to_tensor_pass",
         "//executorch/extension/pybindings:portable",  # @manual
     ],
 )

exir/tests/test_passes.py

@@ -40,7 +40,7 @@
 from executorch.exir.passes.replace_edge_with_backend_pass import EdgeToBackendOpsPass
 from executorch.exir.passes.scalar_to_tensor_pass import ScalarToTensorPass
 from executorch.exir.passes.spec_prop_pass import SpecPropPass
-from executorch.exir.passes.symint_to_tensor_pass import SymIntToTensorPass
+from executorch.exir.passes.sym_to_tensor_pass import SymToTensorPass
 from executorch.exir.tensor import TensorSpec
 from executorch.exir.tests.common import register_additional_test_aten_ops
 from executorch.exir.tests.control_flow_models import FTCondDeadCode, FTMapBasic
@@ -834,11 +834,22 @@ def f(x: torch.Tensor) -> torch.Tensor:
         prog = exir.capture(
             f, inputs, exir.CaptureConfig(enable_dynamic_shape=True)
         ).to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
-        prog = prog.transform(SymIntToTensorPass())
+        prog = prog.transform(SymToTensorPass())
 
+        FileCheck().check(
+            "executorch_exir_dialects_edge__ops_aten_scalar_tensor_default"
+        ).run(prog.exported_program.graph_module.code)
         self.assertTrue(torch.allclose(f(torch.ones(6)), prog(torch.ones(6))))
         self.assertTrue(torch.allclose(f(torch.zeros(6)), prog(torch.zeros(6))))
 
+        # This pass should also be part of to_edge, so checking again after to_edge
+        prog = exir.capture(
+            f, inputs, exir.CaptureConfig(enable_dynamic_shape=True)
+        ).to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
+        FileCheck().check(
+            "executorch_exir_dialects_edge__ops_aten_scalar_tensor_default"
+        ).run(prog.exported_program.graph_module.code)
+
     def test_replace_edge_with_backend_pass(self) -> None:
         def f(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
             z = x + y