[mlir][TD] Fix the order of return handles (#76929)

Replace (in tests and docs): %forall, %tiled = transform.structured.tile_using_forall with (updated order of return handles): %tiled, %forall = transform.structured.tile_using_forall Similar change is applied to (in the TD tutorial): transform.structured.fuse_into_containing_op This update makes sure that the tests/documentation are consistent with the Op specifications. Follow-up for #67320 which updated the order of the return handles for `tile_using_forall`.

Author: banach-space

mlir/docs/Tutorials/transform/Ch1.md

@@ -261,7 +261,7 @@ transform.sequence failures(propagate) {
 
  // The actual tiling transformation takes tile sizes as attributes. It
  // produces a handle to the loop generated during tiling.
- %loop, %tiled_max =
+ %tiled_max, %loop =
  transform.structured.tile_using_forall %max tile_sizes [8, 32]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 
@@ -271,12 +271,12 @@ transform.sequence failures(propagate) {
  // important. We could also use "transform.merge_handles" to obtain a single
  // handle to all operations and give it to `fuse_into_containing_op` that
  // would take care of the ordering in this case.
- %loop_0, %tiled_add =
+ %add_fused, %loop_0 =
  transform.structured.fuse_into_containing_op %add into %loop
  : (!transform.any_op, !transform.any_op)
  -> (!transform.any_op, !transform.any_op)
- %loop_1, %tiled_matmul =
- transform.structured.fuse_into_containing_op %arg1 into %loop
+ %matmul_fused, %loop_1 =
+ transform.structured.fuse_into_containing_op %arg1 into %loop_0
  : (!transform.op<"linalg.matmul">, !transform.any_op)
  -> (!transform.any_op, !transform.any_op)
 
@@ -304,7 +304,7 @@ transform.sequence failures(propagate) {
 
  // The actual tiling transformation takes tile sizes as attributes. It
  // produces a handle to the loop generated during tiling.
- %loop, %tiled = transform.structured.tile_using_forall %max tile_sizes [8, 32]
+ %tiled, %loop  = transform.structured.tile_using_forall %max tile_sizes [8, 32]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 
  // We can now fuse the other operations into the loop. Here, we fuse
@@ -318,7 +318,7 @@ transform.sequence failures(propagate) {
  : (!transform.any_op, !transform.any_op)
  -> (!transform.any_op, !transform.any_op)
  %matmul_fused, %loop_1 =
- transform.structured.fuse_into_containing_op %arg1 into %loop
+ transform.structured.fuse_into_containing_op %arg1 into %loop_0
  : (!transform.op<"linalg.matmul">, !transform.any_op)
  -> (!transform.any_op, !transform.any_op)
 
@@ -327,7 +327,7 @@ transform.sequence failures(propagate) {
  // "max" operation. This illustrates the precise targeting with the transform
  // dialect. Otherwise, it is difficult to differentiate "add" and "max", both
  // of which having the same kind.
- %loop_2, %tiled_2 =
+ %tiled_2, %loop_2 =
  transform.structured.tile_using_forall %add_fused tile_sizes [4, 4]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
  %matmul_fused_2, %loop_3 =
@@ -338,7 +338,7 @@ transform.sequence failures(propagate) {
  // Since outlining is currently only implemented for region-holding operations
  // such as loops, use tiling to size 1 to materialize the outer loop that is
  // going to be outlined.
- %outline_target, %_ =
+ %_, %outline_target =
  transform.structured.tile_using_forall %tiled_2 tile_sizes [1]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
  transform.structured.fuse_into_containing_op %matmul_fused_2

mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td

@@ -1911,8 +1911,8 @@ def TileUsingForallOp :
  tiled operations, which can all be empty.
 
  These two returned handles point to:
- - the new scf.forall op,
- - the tiled op that implements TilingInterface.
+ - the tiled op that implements TilingInterface,
+ - the new scf.forall op.
 
  #### Example using `num_threads`
 

mlir/test/Dialect/GPU/transform-gpu-failing.mlir

@@ -144,7 +144,7 @@ func.func @map_nested_forall_to_threads_not_buffer(%x: tensor<32x32xf32>, %y: te
 module attributes {transform.with_named_sequence} {
  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
  %matmul = transform.structured.match ops{["linalg.matmul"]} in %arg0 : (!transform.any_op) -> !transform.any_op
- %forall, %tiled = transform.structured.tile_using_forall %matmul num_threads [2, 3, 1] (mapping = [ #gpu.thread<y>, #gpu.thread<x>, #gpu.thread<z> ] )
+ %tiled, %forall = transform.structured.tile_using_forall %matmul num_threads [2, 3, 1] (mapping = [ #gpu.thread<y>, #gpu.thread<x>, #gpu.thread<z> ] )
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
  %funcop = transform.structured.match ops{["gpu.launch"]} in %arg0 : (!transform.any_op) -> !transform.any_op
  // expected-error @below {{only bufferized scf.forall can be mapped}}

mlir/test/Dialect/Linalg/tile-to-forall.mlir

@@ -389,7 +389,7 @@ module attributes {transform.with_named_sequence} {
  module attributes {transform.with_named_sequence} {
  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
  %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
- %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [7]
+ %tiled_generic, %forall = transform.structured.tile_using_forall %0 num_threads [7]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
  transform.yield
  }
@@ -445,7 +445,7 @@ module attributes {transform.with_named_sequence} {
  module attributes {transform.with_named_sequence} {
  transform.named_sequence @__transform_main(%IN_MAT2: !transform.any_op {transform.readonly}) {
  %0 = transform.structured.match ops{["linalg.generic"]} in %IN_MAT2 : (!transform.any_op) -> !transform.any_op
- %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [4]
+ %tiled_generic, %forall = transform.structured.tile_using_forall %0 num_threads [4]
  : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
  transform.yield
  }

mlir/test/Examples/transform/Ch1/invalidation-1.mlir

@@ -19,7 +19,7 @@ transform.sequence failures(propagate) {
  %arg2: !transform.op<"linalg.elemwise_binary">):
  // The actual tiling transformation takes tile sizes as attributes.
  // expected-note @below {{invalidated by this transform op that consumes its operand #0 and invalidates all handles to payload IR entities associated with this operand and entities nested in them}}
- %loop, %tiled = transform.structured.tile_using_forall %arg1 tile_sizes [4, 32]
+ %tiled, %loop = transform.structured.tile_using_forall %arg1 tile_sizes [4, 32]
  : (!transform.op<"linalg.matmul">) -> (!transform.any_op, !transform.any_op)
 
  // This is trying to use an invalidated handle leading to undefined behavior.
@@ -64,7 +64,7 @@ transform.sequence failures(propagate) {
 
  // The actual tiling transformation takes tile sizes as attributes.
  // expected-note @below {{invalidated by this transform op that consumes its operand #0 and invalidates all handles to payload IR entities associated with this operand and entities nested in them}}
- %loop, %tiled = transform.structured.tile_using_forall %arg1 tile_sizes [4, 32]
+ %tiled, %loop = transform.structured.tile_using_forall %arg1 tile_sizes [4, 32]
  : (!transform.op<"linalg.matmul">) -> (!transform.any_op, !transform.any_op)
 
  // Consuming an operand invalidates the consumed handle and any other handle that is