Add pass to convert kwargs to args + populate optional args. (pytorch#10857)

Summary:

Adds a pass to convert kwargs to args and populate optional args.

For example:
```
# Before:
slice_copy.Tensor(x, 1, end=3) # dim = 1, start is optional = none, end is a kwarg = 3
# After:
slice_copy.Tensor(x, 1, None, 3, 1)
```

Reviewed By: zonglinpeng

Differential Revision: D74510388

Author: hsharma35

backends/cadence/aot/TARGETS

@@ -367,6 +367,7 @@ python_unittest(
         "fbsource//third-party/pypi/parameterized:parameterized",
         "//caffe2:torch",
         "//executorch/backends/cadence/aot:compiler",
+        "//executorch/backends/cadence/aot:graph_builder",
         "//executorch/backends/cadence/aot:ops_registrations",
         "//executorch/backends/cadence/aot:pass_utils",
         "//executorch/backends/cadence/aot:simplify_ops",

backends/cadence/aot/simplify_ops.py

@@ -16,9 +16,10 @@
     CadencePassAttribute,
     register_cadence_pass,
 )
-
 from executorch.exir.dialects._ops import ops as exir_ops
+from executorch.exir.dialects.edge._ops import EdgeOpOverload
 from executorch.exir.pass_base import ExportPass, ProxyValue
+from torch.fx.operator_schemas import get_signature_for_torch_op
 
 
 @register_cadence_pass(CadencePassAttribute(opt_level=0))
@@ -109,8 +110,44 @@ def call_operator(self, op, args, kwargs, meta):
         return super().call_operator(op, new_args, kwargs, meta)
 
 
+@register_cadence_pass(CadencePassAttribute(opt_level=0))
+class BindOptionalArgsPass(ExportPass):
+    """Bind all optional args and kwargs."""
+
+    def call_operator(self, op, args, kwargs, meta):
+        if not isinstance(op, EdgeOpOverload):
+            return super().call_operator(op, args, kwargs, meta)
+        assert callable(op)
+
+        torch_op_schemas = get_signature_for_torch_op(op._op)
+        if len(torch_op_schemas) == 0:
+            return super().call_operator(op, args, kwargs, meta)
+
+        matched_schemas = []
+        # Iterate through all of the schema until we find one that matches
+        # If one matches, populate `new_args_and_kwargs` with the new args/kwargs
+        # values. If none matches, `new_args_and_kwargs` will be None
+        for candidate_signature in torch_op_schemas:
+            try:
+                candidate_signature.bind(*args, **kwargs)
+                matched_schemas.append(candidate_signature)
+            except TypeError:
+                continue
+
+        if len(matched_schemas) != 1:
+            # Did not match any schema. Cannot normalize
+            return super().call_operator(op, args, kwargs, meta)
+
+        sig = matched_schemas[0]
+        bound_args = sig.bind(*args, **kwargs)
+        bound_args.apply_defaults()
+
+        return super().call_operator(op, bound_args.args, bound_args.kwargs, meta)
+
+
 # This class encapsulates all the functions that simplify the op's args
 class CadenceSimplifyOpsInGraph:
     passes = [
         SimplifySliceOpPass,
+        BindOptionalArgsPass,
     ]

backends/cadence/aot/tests/test_simplify_ops_passes.py

@@ -13,8 +13,12 @@
 import executorch.backends.cadence.aot.ops_registrations  # noqa
 import torch
 from executorch.backends.cadence.aot.compiler import export_to_edge
+from executorch.backends.cadence.aot.graph_builder import single_op_builder
 from executorch.backends.cadence.aot.pass_utils import count_node
-from executorch.backends.cadence.aot.simplify_ops import SimplifySliceOpPass
+from executorch.backends.cadence.aot.simplify_ops import (
+    BindOptionalArgsPass,
+    SimplifySliceOpPass,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from parameterized.parameterized import parameterized
 from torch.fx.passes.infra.pass_base import PassResult
@@ -112,3 +116,33 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         self.assertEqual(
             count_node(graph_after_passes, exir_ops.edge.aten.full.default), 1
         )
+
+    def test_simplify_slice_op_args(self) -> None:
+        x = torch.rand(4, 5)
+        gm = single_op_builder(
+            placeholders=(x,),
+            op=exir_ops.edge.aten.slice_copy.Tensor,
+            args=(x, 1),
+            kwargs={"end": 3},
+        )
+        self.assertEqual(
+            [
+                (n.args[1:], n.kwargs)
+                for n in gm.graph.find_nodes(
+                    op="call_function", target=exir_ops.edge.aten.slice_copy.Tensor
+                )
+            ],
+            [((1,), {"end": 3})],
+        )
+
+        gm = BindOptionalArgsPass().call(gm).graph_module
+
+        self.assertEqual(
+            [
+                (n.args[1:], n.kwargs)
+                for n in gm.graph.find_nodes(
+                    op="call_function", target=exir_ops.edge.aten.slice_copy.Tensor
+                )
+            ],
+            [((1, None, 3, 1), {})],
+        )