1// RUN: mlir-opt %s -transform-interpreter -split-input-file -verify-diagnostics | FileCheck %s 2 3// CHECK: #[[$MAP:.*]] = affine_map<(d0, d1) -> (d1, d0)> 4 5// CHECK-LABEL: @interchange_generic 6func.func @interchange_generic(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> { 7 8 // CHECK: linalg.generic 9 // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]] 10 %0 = linalg.generic { 11 indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>], 12 iterator_types = ["parallel", "parallel"] 13 } ins(%arg0 : tensor<?x?xf32>) outs(%arg1 : tensor<?x?xf32>) { 14 ^bb0(%arg2: f32, %arg3: f32): 15 %1 = math.exp %arg2 : f32 16 linalg.yield %1 : f32 17 } -> tensor<?x?xf32> 18 return %0 : tensor<?x?xf32> 19} 20 21module attributes {transform.with_named_sequence} { 22 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { 23 %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op 24 transform.structured.interchange %0 iterator_interchange = [1, 0] : (!transform.any_op) -> !transform.any_op 25 transform.yield 26 } 27} 28 29// ----- 30 31func.func @interchange_matmul(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>) -> tensor<?x?xf32> { 32 // expected-note @below {{when applied to this op}} 33 %0 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> 34 return %0 : tensor<?x?xf32> 35} 36 37module attributes {transform.with_named_sequence} { 38 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { 39 %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op 40 // expected-error @below {{transform applied to the wrong op kind}} 41 transform.structured.interchange %0 iterator_interchange = [1, 0] : (!transform.any_op) -> !transform.any_op 42 transform.yield 43 } 44} 45 46// ----- 47 48func.func @too_many_iters(%0: tensor<?x?xf32>, %1: tensor<?x?xf32>) -> tensor<?x?xf32> { 49 %r = linalg.generic { 50 indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>], 51 iterator_types = ["parallel", "parallel"] 52 } ins(%0: tensor<?x?xf32>) outs(%1: tensor<?x?xf32>) { 53 ^bb0(%2: f32, %3: f32): 54 %4 = arith.mulf %2, %2 : f32 55 linalg.yield %4 : f32 56 } -> tensor<?x?xf32> 57 return %r : tensor<?x?xf32> 58} 59 60module attributes {transform.with_named_sequence} { 61 transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) { 62 %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op 63 // expected-error @below {{"iterator_interchange" has length (3) different from the number of loops in the target operation (2)}} 64 transform.structured.interchange %0 iterator_interchange = [2,1,0] : (!transform.any_op) -> !transform.any_op 65 transform.yield 66 } 67} 68