get compile config back to EdgeProgramManager.transform (#3500)

Summary:
Pull Request resolved: #3500

This diff introduces the compile configuration into the `EdgeProgramManager.transform` method, ensuring that the constructor and transform function of` EdgeProgramManager` maintain consistent verification configuration. The default verification configuration of `EdgeProgramManager.transform` will now match that of its constructor.

This update brings two key improvements:
1. Enhanced Verification for the transform Function: With this update, we can now customize all necessary configuration verifiers within the `transform` function.
2. Improved Consistency within the `EdgeProgramManager` Class: Post-update, all verifiers within the same `EdgeProgramManager` will have identical functionality. This not only makes the logic more intuitive but also reduces redundancy in user settings.

Reviewed By: JacobSzwejbka, larryliu0820

Differential Revision: D56804195

fbshipit-source-id: 768e697088e3a6cc46cf6ff4515c89a9122494e4

examples/cadence/aot/export_example.py

@@ -54,8 +54,7 @@ def export_model(model, example_inputs):
 
     # Run a couple required passes for quant/dequant ops
     cadence_prog_manager = edge_prog_manager.transform(
-        [ReplacePT2QuantWithCadenceQuant(), ReplacePT2DequantWithCadenceDequant()],
-        check_ir_validity=False,
+        [ReplacePT2QuantWithCadenceQuant(), ReplacePT2DequantWithCadenceDequant()]
     )
 
     exec_prog = cadence_prog_manager.to_executorch()

exir/program/_program.py

@@ -761,14 +761,14 @@ def __init__(
 
         Constructs an EdgeProgramManager from an existing set of exported programs in edge dialect.
         """
-        config = compile_config or EdgeCompileConfig()
+        self.compile_config = compile_config or EdgeCompileConfig()
         if not isinstance(edge_programs, dict):
             edge_programs = {"forward": edge_programs}
         for name, program in edge_programs.items():
             try:
                 EXIREdgeDialectVerifier(
-                    check_edge_ops=config._use_edge_ops,
-                    enable=config._check_ir_validity,
+                    enable=self.compile_config._check_ir_validity,
+                    check_edge_ops=self.compile_config._use_edge_ops,
                 )(program.graph_module)
             except ExportError as e:
                 logging.info(f"Input program {name} is not in aten dialect.")
@@ -800,8 +800,7 @@ def exported_program(self, method_name: str = "forward") -> ExportedProgram:
     def transform(
         self,
         passes: Union[Sequence[PassType], Dict[str, Sequence[PassType]]],
-        check_ir_validity: bool = True,
-        # We should also probably add check_edge_ops here as well
+        compile_config: Optional[EdgeCompileConfig] = None,
     ) -> "EdgeProgramManager":
         """
         Transforms the program according to the provided passes.
@@ -813,31 +812,38 @@ def transform(
                 will be transformed with the provided passes. If it is a
                 dictionary, only method names specified in the dictionary will be
                 transformed with their corresponding passes.
+            compile_config: Compile config to use for veriy the correctness of model
+                graph after each pass. If not specified, the compile config of the
+                calling EdgeProgramManager will be used. It will be used in as compile
+                config of returned EdgeProgramManager.
 
         Returns:
             EdgeProgramManager: A copy of the calling EdgeProgramManager with the
             transformations applied.
         """
+        compile_config = compile_config or self.compile_config
         new_programs: Dict[str, ExportedProgram] = {}
         if isinstance(passes, dict):
             for name, program in self._edge_programs.items():
                 if name in passes.keys():
                     new_programs[name] = _transform(program, *passes[name])
-                    EXIREdgeDialectVerifier(enable=check_ir_validity)(
-                        new_programs[name].graph_module
-                    )
+                    EXIREdgeDialectVerifier(
+                        enable=compile_config._check_ir_validity,
+                        check_edge_ops=compile_config._use_edge_ops,
+                    )(new_programs[name].graph_module)
                 else:
                     new_programs[name] = copy.deepcopy(program)
 
         else:  # apply passes to every method
             for name, program in self._edge_programs.items():
                 new_programs[name] = _transform(program, *passes)
-                EXIREdgeDialectVerifier(enable=check_ir_validity)(
-                    new_programs[name].graph_module
-                )
-        config = EdgeCompileConfig(_check_ir_validity=check_ir_validity)
+                EXIREdgeDialectVerifier(
+                    enable=compile_config._check_ir_validity,
+                    check_edge_ops=compile_config._use_edge_ops,
+                )(new_programs[name].graph_module)
+
         return EdgeProgramManager(
-            new_programs, copy.deepcopy(self._config_methods), config
+            new_programs, copy.deepcopy(self._config_methods), compile_config
         )
 
     def to_backend(

exir/tests/test_passes.py

@@ -336,7 +336,7 @@ def forward(self, x_raw, h, c):
             compile_config=exir.EdgeCompileConfig(_check_ir_validity=False),
         )
 
-        new_prog = edge_prog.transform([SpecPropPass()], check_ir_validity=False)
+        new_prog = edge_prog.transform([SpecPropPass()])
 
         new_gm_res = ToOutVarPass()(new_prog.exported_program().graph_module)
         self.assertIsNotNone(new_gm_res)
@@ -679,7 +679,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
             ),
             compile_config=exir.EdgeCompileConfig(_check_ir_validity=False),
         )
-        new_prog = prog.transform([EdgeToBackendOpsPass()], check_ir_validity=False)
+        new_prog = prog.transform([EdgeToBackendOpsPass()])
         self.assertIsNotNone(new_prog.exported_program().graph_module)
         converted_gm = new_prog.exported_program().graph_module
 
@@ -806,15 +806,15 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
             compile_config=exir.EdgeCompileConfig(_check_ir_validity=False),
         )
 
-        new_prog = prog.transform([EdgeToBackendOpsPass()], check_ir_validity=False)
+        new_prog = prog.transform([EdgeToBackendOpsPass()])
         gm = new_prog.exported_program().graph_module
         gm.print_readable()
         *_, ones, out = gm.graph.nodes
         print(f"Before ExportPass: {ones.format_node()}")
         self.assertTrue(isinstance(ones.meta["val"].shape[0], torch.SymInt))
         self.assertTrue(len(ones.meta["val"].shape[0].node.expr.free_symbols) > 0)
 
-        new_prog = new_prog.transform([ExportPass()], check_ir_validity=False)
+        new_prog = new_prog.transform([ExportPass()])
         gm = new_prog.exported_program().graph_module
         gm.print_readable()
         *_, ones, out = gm.graph.nodes

exir/tests/test_quant_fusion_pass.py

@@ -59,9 +59,7 @@ def forward(self, x, y):
         config = EdgeCompileConfig(_check_ir_validity=False)
         m = to_edge(export(m, example_inputs), compile_config=config)
         # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-        m = m.transform(
-            [QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
-        )
+        m = m.transform([QuantFusionPass(_fix_node_meta_val=True)])
         # check that we are using functional variant of q/dq/add
         FileCheck().check(
             "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default"
@@ -100,9 +98,7 @@ def forward(self, x, y):
         config = EdgeCompileConfig(_check_ir_validity=False)
         m = to_edge(export(m, example_inputs), compile_config=config)
         # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-        m = m.transform(
-            [QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
-        )
+        m = m.transform([QuantFusionPass(_fix_node_meta_val=True)])
         # check that we are using functional variant of q/dq/add/reshape
         # make sure we only have two quant and one dequant since the q/dq around reshape
         # should be fused
@@ -157,9 +153,7 @@ def forward(self, x, y):
         config = EdgeCompileConfig(_check_ir_validity=False)
         m = to_edge(export(m, example_inputs), compile_config=config)
         # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-        m = m.transform(
-            [QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
-        )
+        m = m.transform([QuantFusionPass(_fix_node_meta_val=True)])
         # check that we are using functional variant of q/dq/add/slice
         # make sure we only have one quant and one dequant since the q/dq around slice
         # should be fused
@@ -206,7 +200,7 @@ def forward(self, x, y):
         config = EdgeCompileConfig(_check_ir_validity=False)
         m = to_edge(export(m, example_inputs), compile_config=config)
         # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-        m = m.transform([QuantFusionPass()], check_ir_validity=False)
+        m = m.transform([QuantFusionPass()])
         # check that we are using functional variant of q/dq/cat
         FileCheck().check_count(
             "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_tensor_default",
@@ -301,9 +295,7 @@ def forward(self, indices):
             )
             m = to_edge(export(m, example_inputs), compile_config=compile_config)
             # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-            m = m.transform(
-                [QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
-            )
+            m = m.transform([QuantFusionPass(_fix_node_meta_val=True)])
             # check that we are using functional variant of q/dq/cat
             FileCheck().check(
                 "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_channel_default",
@@ -359,9 +351,7 @@ def forward(self, indices):
             )
             m = to_edge(export(m, example_inputs), compile_config=compile_config)
             # QuantFusionPass should be part of to_executorch() config, separating it out so that we can check the graph.
-            m = m.transform(
-                [QuantFusionPass(_fix_node_meta_val=True)], check_ir_validity=False
-            )
+            m = m.transform([QuantFusionPass(_fix_node_meta_val=True)])
             # check that we are using functional variant of q/dq/cat
             FileCheck().check(
                 "executorch_exir_dialects_edge__ops_quantized_decomposed_quantize_per_channel_default",