[Pipeline] Use dedicated simplification pipeline for TorchDynamo frontend (#3376)

Discord Thread:
https://discord.com/channels/636084430946959380/1238330633328005243

## Context: 

[This](https://github.com/llvm/torch-mlir/blob/main/python/torch_mlir/fx.py#L61)
was updated to support e2e tests for the TorchDynamo frontend in
Torch-MLIR, where we run FX decompositions and import the FX IR to
generate Torch dialect, followed by
`torch-function-to-torch-backend-pipeline`, skipping only the shape/type
refinement for now. However, we should be able to skip many of the torch
simplification passes, as depicted in the [frontend
roadmap](https://github.com/llvm/torch-mlir/blob/main/docs/images/roadmap_frontend.png).

Based on IREE's TorchDynamo
[pipeline](https://github.com/iree-org/iree/blob/main/compiler/plugins/input/Torch/InputConversion/Passes.cpp#L29),
the only two passes we seem to require are: `ReduceOpVariantsPass` and
`DecomposeComplexOpsPass`. This is inline with our findings as well
based on initial exploration.

This PR creates a dedicated frontend simplification pipeline for
TorchDynamo / FX Importer which calls only `ReduceOpVariantsPass` and
`DecomposeComplexOpsPass`. We rely on the e2e fx_importer tests to
ensure we're not regressing by removing many of the passes that were
historically needed for TorchScript.

One notable change here is that we do not call the
`LowerToBackendContractPass` anymore, which used to call
`TorchSimplificationPipeline` iteratively until VerifyBackendContract
was clean. Some of this was required for the shape/type refinement to
converge, which seems a non-issue for Dynamo frontend. Do we anticipate
this (the iterative invocation of TorchSimplificationPipeline followed
by VerifyBackendContract) to be worth retaining in the Dynamo frontend
pipeline? If so, I can make those changes, PLMK.

.gitignore

@@ -11,6 +11,7 @@ externals/pytorch/
 libtorch*
 
 /build/
+.build-cache/
 /setup_build/
 __pycache__
 *.pyc

include/torch-mlir/Dialect/Torch/Transforms/Passes.h

@@ -73,6 +73,11 @@ struct TorchLoweringPipelineOptions
 void createTorchScriptModuleToTorchBackendPipeline(
     OpPassManager &pm, const TorchLoweringPipelineOptions &options);
 
+/// Creates a pipeline that lowers the graph IR that is produced by
+/// TorchDynamo export into the form expected by torch-verify-backend-contract.
+void createTorchDynamoExportToTorchBackendPipeline(
+    OpPassManager &pm, const TorchLoweringPipelineOptions &options);
+
 /// Creates a pipeline that lowers a flat list of funcs and global slots
 /// with the torch and aten dialects and mutable arrays and converts it to
 /// the form required by torch-verify-backend-contract.

lib/Dialect/Torch/Transforms/Passes.cpp

@@ -17,6 +17,10 @@ void mlir::torch::registerTorchPasses() {
       "torchscript-module-to-torch-backend-pipeline",
       "Pipeline lowering TorchScript object graph IR to Torch backend form.",
       mlir::torch::Torch::createTorchScriptModuleToTorchBackendPipeline);
+  mlir::PassPipelineRegistration<Torch::TorchLoweringPipelineOptions>(
+      "torchdynamo-export-to-torch-backend-pipeline",
+      "Pipeline lowering TorchDynamo exported graph IR to Torch backend form.",
+      mlir::torch::Torch::createTorchDynamoExportToTorchBackendPipeline);
   mlir::PassPipelineRegistration<Torch::TorchLoweringPipelineOptions>(
       "torch-function-to-torch-backend-pipeline",
       "Pipeline lowering a Torch function to Torch backend form.",
@@ -59,6 +63,18 @@ void mlir::torch::Torch::createTorchScriptModuleToTorchBackendPipeline(
   createTorchFunctionToTorchBackendPipeline(pm, options);
 }
 
+void mlir::torch::Torch::createTorchDynamoExportToTorchBackendPipeline(
+    OpPassManager &pm, const TorchLoweringPipelineOptions &options) {
+  pm.addNestedPass<func::FuncOp>(
+      createReduceOpVariantsPass(options.extraLibrary));
+  pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
+  if (options.decompose) {
+    pm.addNestedPass<func::FuncOp>(
+        Torch::createDecomposeComplexOpsPass(options.backendLegalOps));
+    pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
+  }
+}
+
 void mlir::torch::Torch::createTorchFunctionToTorchBackendPipeline(
     OpPassManager &pm, const TorchLoweringPipelineOptions &options) {
   // Incorporate user annotations and remove signature Python-isms.

python/torch_mlir/fx.py

@@ -27,7 +27,6 @@ def _module_lowering(
     verbose,
     output_type,
     torch_mod,
-    backend_legal_ops=None,
     extra_library_file_name=None,
 ):
 
@@ -35,23 +34,13 @@ def _module_lowering(
         if verbose:
             print(torch_mod)
         return torch_mod
-    # TODO: pass backend_legal_ops/extra_library_file_name by caller
-    if backend_legal_ops is None:
-        backend_legal_ops = []
+    # TODO: pass extra_library_file_name by caller
     if extra_library_file_name is None:
         extra_library_file_name = ""
-    option_string = (
-        "{backend-legal-ops="
-        + ",".join(backend_legal_ops)
-        + " extra-library="
-        + extra_library_file_name
-        + " shape-dtype-refine="
-        + ("false" if not backend_legal_ops and not extra_library_file_name else "true")
-        + "}"
-    )
+    option_string = "{extra-library=" + extra_library_file_name + "}"
     run_pipeline_with_repro_report(
         torch_mod,
-        f"builtin.module(torch-function-to-torch-backend-pipeline{option_string})",
+        f"builtin.module(torchdynamo-export-to-torch-backend-pipeline{option_string})",
         "Lowering TorchFX IR -> Torch Backend IR",
         enable_ir_printing=verbose,
     )