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1// RUN: mlir-opt --transform-interpreter --split-input-file --verify-diagnostics %s | FileCheck %s2 3#map = affine_map<(d0, d1) -> (d0, d1)>4#map1 = affine_map<(d0, d1) -> (d0)>5#map2 = affine_map<(d0, d1) -> (d1, d0)>6 7func.func @not_a_copy_expect_no_match(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>) {8 // expected-note @below {{when applied to this op}}9 linalg.generic {10 indexing_maps = [#map, #map], 11 iterator_types = ["parallel", "parallel"]}12 ins(%arg0 : memref<?x?xf32>) outs(%arg1 : memref<?x?xf32>) {13 ^bb0(%in: f32, %out: f32):14 %0 = arith.addf %in, %out : f3215 linalg.yield %0 : f3216 }17 return18}19 20func.func @transpose_op_expect_no_match(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>) {21 // expected-note @below {{when applied to this op}}22 linalg.generic {23 indexing_maps = [#map, #map2], 24 iterator_types = ["parallel", "parallel"]} 25 ins(%arg0 : memref<?x?xf32>) outs(%arg1 : memref<?x?xf32>) {26 ^bb0(%in: f32, %out: f32):27 linalg.yield %in : f3228 }29 return30}31 32func.func @copy_with_up_cast(%arg0: memref<?x?xf16>, %arg1: memref<?x?xf32>) {33 // expected-note @below {{when applied to this op}}34 linalg.generic {35 indexing_maps = [#map, #map], 36 iterator_types = ["parallel", "parallel"]} 37 ins(%arg0 : memref<?x?xf16>) outs(%arg1 : memref<?x?xf32>) {38 ^bb0(%in: f16, %out: f32):39 %0 = arith.extf %in : f16 to f3240 linalg.yield %0 : f3241 }42 return43}44 45func.func @copy_with_down_cast(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf16>) {46 // expected-note @below {{when applied to this op}}47 linalg.generic {48 indexing_maps = [#map, #map], 49 iterator_types = ["parallel", "parallel"]} 50 ins(%arg0 : memref<?x?xf32>) outs(%arg1 : memref<?x?xf16>) {51 ^bb0(%in: f32, %out: f16):52 %0 = arith.truncf %in : f32 to f1653 linalg.yield %0 : f1654 }55 return56}57 58module attributes {transform.with_named_sequence} {59 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {60 %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op61 // expected-error @below {{failed to apply}}62 %1 = transform.structured.specialize %0 : (!transform.any_op) -> !transform.any_op63 transform.yield64 }65}66 67// -----68 69#map = affine_map<(d0, d1) -> (d0, d1)>70 71func.func @specialize_trivial_copy_memref(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>) {72 linalg.generic {73 indexing_maps = [#map, #map], 74 iterator_types = ["parallel", "parallel"]} 75 ins(%arg0 : memref<?x?xf32>) outs(%arg1 : memref<?x?xf32>) {76 ^bb0(%in: f32, %out: f32):77 linalg.yield %in : f3278 }79 return80}81 82// CHECK-LABEL: specialize_trivial_copy_memref83// CHECK-SAME: %[[ARG0:.+]]: memref<?x?xf32>, %[[ARG1:.+]]: memref<?x?xf32>84// CHECK-NOT: linalg.generic85// CHECK: linalg.copy ins(%[[ARG0]] : memref<?x?xf32>) outs(%[[ARG1]] : memref<?x?xf32>)86 87#map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>88 89func.func @specialize_trivial_copy_tensor(%arg0: tensor<?x?x?xf32>, 90 %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {91 %0 = linalg.generic {92 indexing_maps = [#map1, #map1], 93 iterator_types = ["parallel", "parallel", "parallel"]}94 ins(%arg0 : tensor<?x?x?xf32>) outs(%arg1 : tensor<?x?x?xf32>) {95 ^bb0(%in: f32, %out: f32):96 linalg.yield %in : f3297 } -> tensor<?x?x?xf32>98 return %0 : tensor<?x?x?xf32>99}100 101// CHECK-LABEL: specialize_trivial_copy_tensor102// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?xf32>103// CHECK-NOT: linalg.generic104// CHECK: %{{.+}} = linalg.copy ins(%[[ARG0]] : tensor<?x?x?xf32>) outs(%[[ARG1]] : tensor<?x?x?xf32>)105 106func.func @already_trivial_copy_memref(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>) {107 linalg.copy ins(%arg0: memref<?x?xf32>) outs(%arg1: memref<?x?xf32>)108 return109}110 111// CHECK-LABEL: already_trivial_copy_memref112// CHECK-SAME: %[[ARG0:.+]]: memref<?x?xf32>, %[[ARG1:.+]]: memref<?x?xf32>113// CHECK: linalg.copy ins(%[[ARG0]] : memref<?x?xf32>) outs(%[[ARG1]] : memref<?x?xf32>)114 115func.func @already_trivial_copy_tensor(%arg0: tensor<?x?x?xf32>,116 %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {117 %0 = linalg.copy ins(%arg0: tensor<?x?x?xf32>) outs(%arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32>118 return %0 : tensor<?x?x?xf32>119}120 121// CHECK-LABEL: already_trivial_copy_tensor122// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?xf32>123// CHECK: %{{.+}} = linalg.copy ins(%[[ARG0]] : tensor<?x?x?xf32>) outs(%[[ARG1]] : tensor<?x?x?xf32>)124 125module attributes {transform.with_named_sequence} {126 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {127 %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op128 %1 = transform.structured.specialize %0 : (!transform.any_op) -> !transform.any_op129 transform.yield130 }131}132 133// -----134 135#map = affine_map<(d0, d1) -> ()>136#map1 = affine_map<(d0, d1) -> (d0, d1)>137func.func @linalg_generic_fill(%arg0: tensor<7x7xf32>) -> tensor<7x7xf32> {138 %cst = arith.constant 0.000000e+00 : f32139 %0 = linalg.generic {indexing_maps = [#map, #map1], iterator_types = ["parallel", "parallel"]} ins(%cst : f32) outs(%arg0 : tensor<7x7xf32>) {140 ^bb0(%in: f32, %out: f32):141 linalg.yield %in : f32142 } -> tensor<7x7xf32>143 return %0 : tensor<7x7xf32>144}145// CHECK-LABEL: linalg_generic_fill146// CHECK-SAME: %[[ARG0:.+]]: tensor<7x7xf32>) -> tensor<7x7xf32>147// CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32148// CHECK: %{{.*}} = linalg.fill ins(%[[CST]] : f32) outs(%[[ARG0]] : tensor<7x7xf32>) -> tensor<7x7xf32>149 150module attributes {transform.with_named_sequence} {151 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {152 %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op153 %1 = transform.structured.specialize %0 : (!transform.any_op) -> !transform.any_op154 transform.yield155 }156}157 158// -----159 160#map = affine_map<(d0, d1) -> (d0, d1)>161func.func @linalg_generic_inlined_constant_fill(%arg0: tensor<7x7xf32>) -> tensor<7x7xf32> {162 %cst = arith.constant 0.000000e+00 : f32163 %0 = linalg.generic {indexing_maps = [#map], iterator_types = ["parallel", "parallel"]} outs(%arg0 : tensor<7x7xf32>) {164 ^bb0(%out: f32):165 linalg.yield %cst : f32166 } -> tensor<7x7xf32>167 return %0 : tensor<7x7xf32>168}169 170// CHECK-LABEL: linalg_generic_inlined_constant_fill171// CHECK-SAME: %[[ARG0:.+]]: tensor<7x7xf32>) -> tensor<7x7xf32>172// CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32173// CHECK: %{{.*}} = linalg.fill ins(%[[CST]] : f32) outs(%[[ARG0]] : tensor<7x7xf32>) -> tensor<7x7xf32>174 175module attributes {transform.with_named_sequence} {176 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {177 %0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op178 %1 = transform.structured.specialize %0 : (!transform.any_op) -> !transform.any_op179 transform.yield180 }181}182