[mlir] update types in remaining Linalg TransformOps test

All ops now support explicit type specification, update types to use
`!transform.any_op` instead of `!pdl.operation` for consistency.

Depends On D144515

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D150592

mlir/test/Dialect/Linalg/convert-conv2d-to-img2col.mlir

@@ -16,10 +16,10 @@ func.func @conv_non_static(%arg0: tensor<?x?x?x?xf32>, %arg1: tensor<3x3x4x16xf3
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!pdl.operation) -> !pdl.operation
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
   // expected-error@below {{failed to apply}}
-  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
+  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 // -----
@@ -88,11 +88,11 @@ func.func @conv_16433136(%arg0: tensor<1x16x16x4xf32>, %arg1: tensor<3x3x4x16xf3
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %img2col_tensor_producer, %transformed = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
-  transform.print %img2col_tensor_producer {name = "tensor_producer"}: !pdl.operation
-  transform.print %transformed {name = "transformed"}: !pdl.operation
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %img2col_tensor_producer, %transformed = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+  transform.print %img2col_tensor_producer {name = "tensor_producer"}: !transform.any_op
+  transform.print %transformed {name = "transformed"}: !transform.any_op
 }
 
 // -----
@@ -167,9 +167,9 @@ func.func @depthwise_conv_hwc_114x16x3(%input: tensor<1x114x114x16xf32>, %filter
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.depthwise_conv_2d_nhwc_hwc"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.depthwise_conv_2d_nhwc_hwc"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 // -----
@@ -209,9 +209,9 @@ func.func @batch_nhwc_conv(%arg0: tensor<8x16x16x4xf32>, %arg1: tensor<3x3x4x16x
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 // -----
@@ -272,9 +272,9 @@ func.func @batch_nchw_conv(%arg0: tensor<8x4x16x16xf32>, %arg1: tensor<16x4x3x3x
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.conv_2d_nchw_fchw"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.conv_2d_nchw_fchw"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %1:2 = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 // -----
@@ -308,9 +308,9 @@ func.func @conv_integer_extend(%arg0: tensor<1x16x16x4xi8>, %arg1: tensor<3x3x4x
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %img2col_tensor_producer, %transformed = transform.structured.convert_conv2d_to_img2col %0 : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
-  transform.print %img2col_tensor_producer {name = "tensor_producer"}: !pdl.operation
-  transform.print %transformed {name = "transformed"}: !pdl.operation
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %img2col_tensor_producer, %transformed = transform.structured.convert_conv2d_to_img2col %0 : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+  transform.print %img2col_tensor_producer {name = "tensor_producer"}: !transform.any_op
+  transform.print %transformed {name = "transformed"}: !transform.any_op
 }

mlir/test/Dialect/Linalg/hoisting.mlir

@@ -75,11 +75,11 @@ func.func @hoist_vector_transfer_pairs(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_vector_transfers %0
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
@@ -164,11 +164,11 @@ func.func @hoist_vector_transfer_pairs_disjoint(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_vector_transfers %0
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
@@ -209,11 +209,11 @@ func.func @hoist_vector_transfer_pairs_in_affine_loops(%memref0: memref<64x64xi3
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_vector_transfers %0
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
 }
 
 // -----
@@ -298,11 +298,11 @@ func.func @hoist_vector_transfer_pairs_tensor(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_tensor_subsets %0
-    : (!pdl.operation) -> ()
+    : (!transform.any_op) -> ()
 }
 
 // -----
@@ -393,11 +393,11 @@ func.func @hoist_vector_transfer_pairs_disjoint_tensor(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_tensor_subsets %0
-    : (!pdl.operation) -> ()
+    : (!transform.any_op) -> ()
 }
 
 // -----
@@ -510,11 +510,11 @@ func.func @hoist_vector_transfer_pairs_tensor_and_slices(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_tensor_subsets %0
-    : (!pdl.operation) -> ()
+    : (!transform.any_op) -> ()
 }
 
 // -----
@@ -557,11 +557,11 @@ func.func @hoist_vector_transfer_write_pairs_disjoint_tensor(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_tensor_subsets %0
-    : (!pdl.operation) -> ()
+    : (!transform.any_op) -> ()
 }
 
 // -----
@@ -670,11 +670,11 @@ func.func @hoist_vector_transfer_pairs_tensor_and_slices_static_large_tensor(
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_tensor_subsets %0
-    : (!pdl.operation) -> ()
+    : (!transform.any_op) -> ()
 }
 
 // -----
@@ -716,9 +716,9 @@ func.func @hoist_vector_transfer_read() {
 }
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
+^bb1(%arg1: !transform.any_op):
   %0 = transform.structured.match ops{["func.func"]} in %arg1
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
   transform.structured.hoist_redundant_vector_transfers %0
-    : (!pdl.operation) -> !pdl.operation
+    : (!transform.any_op) -> !transform.any_op
 }

mlir/test/Dialect/Linalg/multisize-tiling-full.mlir

@@ -3,18 +3,18 @@
 
 // This implements a 2D multisize tiling with target sizes [3, 10].
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!pdl.operation) -> !pdl.operation
-  %t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!pdl.operation) -> !pdl.operation
-  %2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !pdl.operation, !pdl.operation
-  %3:2 = transform.structured.tile %2#0 [%1#0] : (!pdl.operation, !pdl.operation) -> (!pdl.operation, !pdl.operation)
-  %4:2 = transform.structured.tile %2#1 [%1#1] : (!pdl.operation, !pdl.operation) -> (!pdl.operation, !pdl.operation)
-  %5 = merge_handles %3#0, %4#0 : !pdl.operation
-  %tt:3 = replicate num(%5) %t#0, %t#1, %t#2 : !pdl.operation, !pdl.operation, !pdl.operation, !pdl.operation
-  %6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !pdl.operation, !pdl.operation
-  transform.structured.tile %6#0 [0, %tt#0] : (!pdl.operation, !pdl.operation) -> (!pdl.operation, !pdl.operation)
-  transform.structured.tile %6#1 [0, %tt#1] : (!pdl.operation, !pdl.operation) -> (!pdl.operation, !pdl.operation)
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!transform.any_op) -> !transform.any_op
+  %t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!transform.any_op) -> !transform.any_op
+  %2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !transform.any_op, !transform.any_op
+  %3:2 = transform.structured.tile %2#0 [%1#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
+  %4:2 = transform.structured.tile %2#1 [%1#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
+  %5 = merge_handles %3#0, %4#0 : !transform.any_op
+  %tt:3 = replicate num(%5) %t#0, %t#1, %t#2 : !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op
+  %6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !transform.any_op, !transform.any_op
+  transform.structured.tile %6#0 [0, %tt#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
+  transform.structured.tile %6#1 [0, %tt#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 func.func private @elem(%arg0: f32, %arg1: index, %arg2: index) -> f32
@@ -103,18 +103,18 @@ func.func @two_d(%arg0: tensor<10x34xf32>,
 // -----
 
 transform.sequence failures(propagate) {
-^bb1(%arg1: !pdl.operation):
-  %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-  %1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!pdl.operation) -> !transform.param<i64>
-  %t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!pdl.operation) -> !transform.param<i64>
-  %2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !pdl.operation, !transform.param<i64>
-  %3:2 = transform.structured.tile %2#0 [%1#0] : (!pdl.operation, !transform.param<i64>) -> (!pdl.operation, !pdl.operation)
-  %4:2 = transform.structured.tile %2#1 [%1#1] : (!pdl.operation, !transform.param<i64>) -> (!pdl.operation, !pdl.operation)
-  %5 = merge_handles %3#0, %4#0 : !pdl.operation
-  %tt:3 = replicate num(%5) %t#0, %t#1, %t#2 : !pdl.operation, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>
-  %6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !pdl.operation, !transform.param<i64>
-  transform.structured.tile %6#0 [0, %tt#0] : (!pdl.operation, !transform.param<i64>) -> (!pdl.operation, !pdl.operation)
-  transform.structured.tile %6#1 [0, %tt#1] : (!pdl.operation, !transform.param<i64>) -> (!pdl.operation, !pdl.operation)
+^bb1(%arg1: !transform.any_op):
+  %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+  %1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!transform.any_op) -> !transform.param<i64>
+  %t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!transform.any_op) -> !transform.param<i64>
+  %2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !transform.any_op, !transform.param<i64>
+  %3:2 = transform.structured.tile %2#0 [%1#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
+  %4:2 = transform.structured.tile %2#1 [%1#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
+  %5 = merge_handles %3#0, %4#0 : !transform.any_op
+  %tt:3 = replicate num(%5) %t#0, %t#1, %t#2 : !transform.any_op, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>
+  %6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !transform.any_op, !transform.param<i64>
+  transform.structured.tile %6#0 [0, %tt#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
+  transform.structured.tile %6#1 [0, %tt#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
 }
 
 func.func private @elem(%arg0: f32, %arg1: index, %arg2: index) -> f32

mlir/test/Dialect/Linalg/tile-conv.mlir

@@ -10,9 +10,9 @@ func.func @conv(%arg0 : memref<?x?xf32>, %arg1 : memref<?x?xf32>, %arg2 : memref
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.conv_2d"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loop:2 = transform.structured.tile %0 [2, 3] : (!pdl.operation) -> (!pdl.operation, !pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.conv_2d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loop:2 = transform.structured.tile %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
 }
 
 //       CHECK: func @conv

mlir/test/Dialect/Linalg/tile-indexed.mlir

@@ -12,9 +12,9 @@ func.func @indexed_vector(%arg0: memref<50xindex>) {
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loop = transform.structured.tile %0 [10] : (!pdl.operation) -> (!pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loop = transform.structured.tile %0 [10] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
 }
 
 // TILE-10n25-DAG: [[$MAP:#[a-zA-Z0-9_]*]] = affine_map<(d0, d1) -> (d0 + d1)>
@@ -42,9 +42,9 @@ func.func @indexed_matrix(%arg0: memref<50x50xindex>) {
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loop:2 = transform.structured.tile %0 [10, 25] : (!pdl.operation) -> (!pdl.operation, !pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loop:2 = transform.structured.tile %0 [10, 25] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
 }
 
 // TILE-10n25-DAG: [[$MAP:#[a-zA-Z0-9_]*]] = affine_map<(d0, d1) -> (d0 + d1)>

mlir/test/Dialect/Linalg/tile-tensors.mlir

@@ -28,9 +28,9 @@ func.func @matmul_tensors(
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!pdl.operation) -> (!pdl.operation, !pdl.operation, !pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
 }
 
 // -----
@@ -59,9 +59,9 @@ func.func @generic_op_tensors(
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!pdl.operation) -> (!pdl.operation, !pdl.operation, !pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
 }
 
 // CHECK-LABEL: func @generic_op_tensors
@@ -130,7 +130,7 @@ func.func @fold_extract_slice(
 }
 
 transform.sequence failures(propagate) {
-  ^bb0(%arg1: !pdl.operation):
-    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!pdl.operation) -> !pdl.operation
-    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!pdl.operation) -> (!pdl.operation, !pdl.operation, !pdl.operation, !pdl.operation)
+  ^bb0(%arg1: !transform.any_op):
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops:3 = transform.structured.tile %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
 }