Add `RecomposeComplexOps` declaration + fix typos in pass name (#1950)

The `RecomposeComplexOps` pass currently does not have a TableGen
declaration and it is using the base class of `DecomposeComplexOps`,
which causes `--mlir-print-ir-after-all` to create wrong pass
labels. This commit fixes that as well as some minor typos in the name
of the pass.

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

@@ -106,7 +106,7 @@ std::unique_ptr<OperationPass<ModuleOp>> createRefinePublicReturnPass();
 std::unique_ptr<OperationPass<func::FuncOp>>
 createDecomposeComplexOpsPass(ArrayRef<std::string> legalOps);
 
-std::unique_ptr<OperationPass<func::FuncOp>> createRecomposeComplexOps();
+std::unique_ptr<OperationPass<func::FuncOp>> createRecomposeComplexOpsPass();
 
 std::unique_ptr<OperationPass<ModuleOp>>
 createReifyShapeCalculationsPass(StringRef extraLibrary);

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

@@ -244,6 +244,29 @@ def DecomposeComplexOps : Pass<"torch-decompose-complex-ops", "func::FuncOp"> {
   }];
 }
 
+def RecomposeComplexOps : Pass<"torch-recompose-complex-ops", "func::FuncOp"> {
+  let summary = "Recompose torch operations that have been decomposed by TorchScript";
+  let constructor = "mlir::torch::Torch::createRecomposeComplexOpsPass()";
+  let description = [{
+    There are certain ops that TorchScript will split into multiple ops that
+    prevent optimizations in Torch-MLIR from taking place. In this pass such
+    sequences of ops are identified and combined into a higher level op,
+    preserving the original behavior, while allowing new optimizations to happen.
+
+    An example is the handling of the indexing operation in PyTorch. The following
+
+    ```
+    input_tensor[1:2, :] = 7
+    ```
+
+    will get split into a series of `slice` ops to get the sub-tensor, then an
+    in-place copy to overwrite the sub-tensor with the value 7. This type of
+    pattern prevents the `MaximizeValueSemantics` pass from succeeding. So,
+    using `RecomposeComplexOps`, the series of slices + copy is identified
+    and turned into a single `index_put` operation.
+  }];
+}
+
 def ReifyShapeCalculations : Pass<"torch-reify-shape-calculations", "ModuleOp"> {
   let summary = "Reify shape calculations.";
   let constructor = [{

lib/Dialect/Torch/Transforms/Passes.cpp

@@ -107,7 +107,7 @@ void mlir::torch::Torch::createTorchSimplificationPipeline(
   // Clean up again to avoid needing to to back around the fixed-point
   // iteration.
   pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
-  pm.addNestedPass<func::FuncOp>(createRecomposeComplexOps());
+  pm.addNestedPass<func::FuncOp>(createRecomposeComplexOpsPass());
   // Reduce variants of ops to a smaller set of primitives.
   pm.addNestedPass<func::FuncOp>(
       createReduceOpVariantsPass(options.extraLibrary));

lib/Dialect/Torch/Transforms/RecomposeComplexOps.cpp

@@ -74,10 +74,9 @@ public:
 } // namespace
 
 namespace {
-class RecomposeComplexOps
-    : public DecomposeComplexOpsBase<RecomposeComplexOps> {
+class RecomposeComplexOpsPass
+    : public RecomposeComplexOpsBase<RecomposeComplexOpsPass> {
 public:
-  RecomposeComplexOps() = default;
   void runOnOperation() override {
     MLIRContext *context = &getContext();
     RewritePatternSet patterns(context);
@@ -98,6 +97,6 @@ public:
 } // namespace
 
 std::unique_ptr<OperationPass<func::FuncOp>>
-mlir::torch::Torch::createRecomposeComplexOps() {
-  return std::make_unique<RecomposeComplexOps>();
+mlir::torch::Torch::createRecomposeComplexOpsPass() {
+  return std::make_unique<RecomposeComplexOpsPass>();
 }