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1// RUN: mlir-opt %s --transform-preload-library='transform-library-paths=%p/match_matmul_common.mlir' --transform-interpreter --verify-diagnostics2 3module attributes { transform.with_named_sequence } {4  transform.named_sequence @_match_matmul_like(5      %entry: !transform.any_op {transform.readonly},6      %rank: !transform.param<i64> {transform.readonly})7      -> (!transform.any_op, !transform.any_op, !transform.param<i64>,8          !transform.type, !transform.type, !transform.type,9          !transform.param<i64>, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>)10 11  transform.named_sequence @match_matmul(%entry: !transform.any_op {transform.readonly})12      -> (!transform.any_op, !transform.any_op, !transform.param<i64>,13          !transform.type, !transform.type, !transform.type) {14    transform.match.operation_name %entry ["linalg.matmul", "linalg.generic"] : !transform.any_op15    %c3 = transform.param.constant 3 : i64 -> !transform.param<i64>16    %fill, %matmul, %dims, %lhs_type, %rhs_type, %res_type, %kinds:4 =17      transform.include @_match_matmul_like failures(propagate) (%entry, %c3)18        : (!transform.any_op, !transform.param<i64>)19        -> (!transform.any_op, !transform.any_op, !transform.param<i64>,20            !transform.type, !transform.type, !transform.type,21            !transform.param<i64>, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>)22 23    transform.yield %fill, %matmul, %dims, %lhs_type, %rhs_type, %res_type24        : !transform.any_op, !transform.any_op, !transform.param<i64>, !transform.type, !transform.type, !transform.type25  }26 27  transform.named_sequence @print_matmul(28      %fill: !transform.any_op {transform.readonly},29      %matmul: !transform.any_op {transform.readonly},30      %dims: !transform.param<i64> {transform.readonly},31      %lhs_type: !transform.type {transform.readonly},32      %rhs_type: !transform.type {transform.readonly},33      %res_type: !transform.type {transform.readonly}) {34    transform.debug.emit_remark_at %fill, "fill" : !transform.any_op35    transform.debug.emit_remark_at %matmul, "matmul" : !transform.any_op36    transform.debug.emit_param_as_remark %dims, "dimensions" at %matmul : !transform.param<i64>, !transform.any_op37    transform.debug.emit_param_as_remark %lhs_type, "LHS type" at %matmul : !transform.type, !transform.any_op38    transform.debug.emit_param_as_remark %rhs_type, "RHS type" at %matmul : !transform.type, !transform.any_op39    transform.debug.emit_param_as_remark %res_type, "result type" at %matmul : !transform.type, !transform.any_op40    transform.yield41  }42 43  transform.named_sequence @__transform_main(%root: !transform.any_op {transform.consumed}) {44    transform.foreach_match in %root45      @match_matmul -> @print_matmul46      : (!transform.any_op) -> !transform.any_op47    transform.yield48  }49}50 51func.func @matmul_simple(%lhs: tensor<10x20xf16>, %rhs: tensor<20x15xf32>) -> tensor<10x15xf64>{52  %cst = arith.constant 0.0 : f6453  %empty = tensor.empty() : tensor<10x15xf64>54  // expected-remark @below {{fill}}55  %fill = linalg.fill ins(%cst : f64) outs(%empty : tensor<10x15xf64>) -> tensor<10x15xf64>56  // expected-remark @below {{matmul}}57  // expected-remark @below {{dimensions 10 : i64, 15 : i64, 20 : i64}}58  // expected-remark @below {{LHS type f16}}59  // expected-remark @below {{RHS type f32}}60  // expected-remark @below {{result type f64}}61  %result = linalg.matmul ins(%lhs, %rhs: tensor<10x20xf16>, tensor<20x15xf32>) outs(%fill: tensor<10x15xf64>) -> tensor<10x15xf64>62  return %result : tensor<10x15xf64>63}64 65func.func @matmul_with_extra_ops_in_func(%lhs: tensor<10x20xf32>, %rhs: tensor<20x15xf32>) -> tensor<10x15xf32> {66  %cst = arith.constant 0.0 : f3267  %empty = tensor.empty() : tensor<10x15xf32>68 69  // expected-remark @below {{fill}}70  %fill = linalg.fill ins(%cst : f32) outs(%empty : tensor<10x15xf32>) -> tensor<10x15xf32>71 72  %real_lhs = linalg.mul73    ins(%lhs, %lhs : tensor<10x20xf32>, tensor<10x20xf32>) outs(%lhs : tensor<10x20xf32>) -> tensor<10x20xf32>74 75  // expected-remark @below {{matmul}}76  // expected-remark @below {{dimensions 10 : i64, 15 : i64, 20 : i64}}77  // expected-remark @below {{LHS type f32}}78  // expected-remark @below {{RHS type f32}}79  // expected-remark @below {{result type f32}}80  %result = linalg.matmul ins(%real_lhs, %rhs: tensor<10x20xf32>, tensor<20x15xf32>) outs(%fill: tensor<10x15xf32>) -> tensor<10x15xf32>81  return %result : tensor<10x15xf32>82}83 84func.func @matmul_generic(%lhs: tensor<10x20xf16>, %rhs: tensor<20x15xf32>) -> tensor<10x15xf64>{85  %cst = arith.constant 0.0 : f6486  %empty = tensor.empty() : tensor<10x15xf64>87  // expected-remark @below {{fill}}88  %fill = linalg.fill ins(%cst : f64) outs(%empty : tensor<10x15xf64>) -> tensor<10x15xf64>89  // expected-remark @below {{matmul}}90  // expected-remark @below {{dimensions 10 : i64, 15 : i64, 20 : i64}}91  // expected-remark @below {{LHS type f16}}92  // expected-remark @below {{RHS type f32}}93  // expected-remark @below {{result type f64}}94  %result = linalg.generic {95    indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>,96                     affine_map<(d0, d1, d2) -> (d2, d1)>,97                     affine_map<(d0, d1, d2) -> (d0, d1)>],98    iterator_types = ["parallel", "parallel", "reduction"]99  } ins(%lhs, %rhs: tensor<10x20xf16>, tensor<20x15xf32>) outs(%fill: tensor<10x15xf64>) {100  ^bb(%arg0: f16, %arg1: f32, %arg2: f64):101    %0 = arith.extf %arg0 : f16 to f32102    %1 = arith.mulf %0, %arg1 : f32103    %2 = arith.extf %1 : f32 to f64104    %3 = arith.addf %2, %arg2 : f64105    linalg.yield %3 : f64106  }-> tensor<10x15xf64>107  return %result : tensor<10x15xf64>108}109