[mlir] Remove dialect specific bufferization passes (#93488)

These passes have been depreciated for a long time and replaced by
one-shot bufferization. These passes are also unsafe because they do not
check for read-after-write conflicts.

Author: Groverkss

mlir/include/mlir/Dialect/Arith/Transforms/Passes.h

@@ -24,9 +24,6 @@ namespace arith {
 class WideIntEmulationConverter;
 class NarrowTypeEmulationConverter;
 
-/// Create a pass to bufferize arith.constant ops.
-std::unique_ptr<Pass> createConstantBufferizePass(uint64_t alignment = 0);
-
 /// Adds patterns to emulate wide Arith and Function ops over integer
 /// types into supported ones. This is done by splitting original power-of-two
 /// i2N integer types into two iN halves.

mlir/include/mlir/Dialect/Arith/Transforms/Passes.td

@@ -11,22 +11,6 @@
 
 include "mlir/Pass/PassBase.td"
 
-def ArithBufferizePass : Pass<"arith-bufferize", "ModuleOp"> {
-  let summary = "Bufferize Arith dialect ops.";
-  let description = [{
-    This pass bufferizes arith dialect ops.
-
-    This pass needs to be a module pass because it inserts memref.global
-    ops into the module, which cannot be done safely from a function pass due to
-    multi-threading. Most other bufferization passes can run in parallel at
-    function granularity.
-  }];
-  let options = [
-    Option<"alignment", "alignment", "unsigned", /*default=*/"0",
-           "Create global memrefs with a specified alignment">,
-  ];
-}
-
 def ArithExpandOpsPass : Pass<"arith-expand"> {
   let summary = "Legalize Arith ops to be convertible to LLVM.";
   let dependentDialects = ["vector::VectorDialect"];

mlir/include/mlir/Dialect/Bufferization/Transforms/Passes.h

@@ -221,9 +221,6 @@ createPromoteBuffersToStackPass(std::function<bool(Value)> isSmallAlloc);
 /// insert_slice ops.
 std::unique_ptr<Pass> createEmptyTensorEliminationPass();
 
-/// Create a pass that bufferizes ops from the bufferization dialect.
-std::unique_ptr<Pass> createBufferizationBufferizePass();
-
 //===----------------------------------------------------------------------===//
 // Registration
 //===----------------------------------------------------------------------===//

mlir/include/mlir/Dialect/Bufferization/Transforms/Passes.td

@@ -350,11 +350,6 @@ def FinalizingBufferize : Pass<"finalizing-bufferize", "func::FuncOp"> {
   let constructor = "mlir::bufferization::createFinalizingBufferizePass()";
 }
 
-def BufferizationBufferize : Pass<"bufferization-bufferize", "func::FuncOp"> {
-  let summary = "Bufferize the `bufferization` dialect";
-  let constructor = "mlir::bufferization::createBufferizationBufferizePass()";
-}
-
 def DropEquivalentBufferResults : Pass<"drop-equivalent-buffer-results", "ModuleOp">  {
   let summary = "Remove MemRef return values that are equivalent to a bbArg";
   let description = [{

mlir/include/mlir/Dialect/Linalg/Passes.h

@@ -22,10 +22,6 @@ namespace func {
 class FuncOp;
 } // namespace func
 
-namespace bufferization {
-struct OneShotBufferizationOptions;
-} // namespace bufferization
-
 #define GEN_PASS_DECL
 #include "mlir/Dialect/Linalg/Passes.h.inc" // IWYU pragma: keep
 

mlir/include/mlir/Dialect/Linalg/Passes.td

@@ -89,16 +89,6 @@ def LinalgInlineScalarOperandsPass : Pass<"linalg-inline-scalar-operands"> {
   ];
 }
 
-def LinalgBufferizePass : Pass<"linalg-bufferize"> {
-  let summary = "Bufferize the linalg dialect";
-  let dependentDialects = [
-    "affine::AffineDialect",
-    "bufferization::BufferizationDialect",
-    "linalg::LinalgDialect",
-    "memref::MemRefDialect",
-  ];
-}
-
 def LinalgGeneralizeNamedOpsPass : Pass<"linalg-generalize-named-ops"> {
   let summary = "Convert named ops into generic ops";
   let dependentDialects = ["linalg::LinalgDialect"];

mlir/include/mlir/Dialect/Shape/Transforms/Passes.h

@@ -47,13 +47,6 @@ void populateShapeRewritePatterns(RewritePatternSet &patterns);
 void populateRemoveShapeConstraintsPatterns(RewritePatternSet &patterns);
 std::unique_ptr<OperationPass<func::FuncOp>> createRemoveShapeConstraintsPass();
 
-// Bufferizes shape dialect ops.
-//
-// Note that most shape dialect ops must be converted to std before
-// bufferization happens, as they are intended to be bufferized at the std
-// level.
-std::unique_ptr<OperationPass<func::FuncOp>> createShapeBufferizePass();
-
 /// Outline the shape computation part by adding shape.func and populate
 /// conrresponding mapping infomation into ShapeMappingAnalysis.
 std::unique_ptr<OperationPass<ModuleOp>> createOutlineShapeComputationPass();

mlir/include/mlir/Dialect/Shape/Transforms/Passes.td

@@ -103,11 +103,4 @@ def ShapeToShapeLowering : Pass<"shape-to-shape-lowering", "func::FuncOp"> {
   let constructor = "mlir::createShapeToShapeLowering()";
 }
 
-// TODO: Generalize this to allow any type conversions desired.
-def ShapeBufferize : Pass<"shape-bufferize", "func::FuncOp"> {
-  let summary = "Bufferize the shape dialect.";
-  let constructor = "mlir::createShapeBufferizePass()";
-  let dependentDialects = ["bufferization::BufferizationDialect",
-                           "memref::MemRefDialect"];
-}
 #endif // MLIR_DIALECT_SHAPE_TRANSFORMS_PASSES

mlir/include/mlir/Dialect/Tensor/Transforms/Passes.h

@@ -21,9 +21,6 @@ namespace tensor {
 /// Creates an instance of the `tensor` subset folding pass.
 std::unique_ptr<Pass> createFoldTensorSubsetOpsPass();
 
-/// Creates an instance of the `tensor` dialect bufferization pass.
-std::unique_ptr<Pass> createTensorBufferizePass();
-
 //===----------------------------------------------------------------------===//
 // Registration
 //===----------------------------------------------------------------------===//

mlir/include/mlir/Dialect/Tensor/Transforms/Passes.td

@@ -27,9 +27,4 @@ def FoldTensorSubsetOps : Pass<"fold-tensor-subset-ops"> {
   ];
 }
 
-def TensorBufferize : Pass<"tensor-bufferize", "func::FuncOp"> {
-  let summary = "Bufferize the `tensor` dialect";
-  let constructor = "mlir::tensor::createTensorBufferizePass()";
-}
-
 #endif // MLIR_DIALECT_TENSOR_TRANSFORMS_PASSES