forked from OSchip/llvm-project
72 lines
2.6 KiB
MLIR
72 lines
2.6 KiB
MLIR
// RUN: mlir-opt %s -pass-pipeline="func.func(linalg-detensorize{aggressive-mode})" | FileCheck %s -check-prefix=DET-ALL
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// RUN: mlir-opt %s -pass-pipeline="func.func(linalg-detensorize)" | FileCheck %s -check-prefix=DET-CF
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#map0 = affine_map<() -> ()>
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#attrs = {
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indexing_maps = [#map0, #map0, #map0],
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iterator_types = []
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}
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func.func @main(%farg0: tensor<i32>, %farg1: tensor<i32>) -> tensor<i32> attributes {} {
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cf.br ^bb1(%farg0 : tensor<i32>)
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^bb1(%0: tensor<i32>): // 2 preds: ^bb0, ^bb2
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%1 = linalg.init_tensor [] : tensor<i1>
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%2 = linalg.generic #attrs
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ins(%0, %farg1 : tensor<i32>, tensor<i32>)
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outs(%1 : tensor<i1>) {
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^bb0(%arg0: i32, %arg1: i32, %arg2: i1):
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%8 = arith.cmpi slt, %arg0, %arg1 : i32
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linalg.yield %8 : i1
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} -> tensor<i1>
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%3 = tensor.extract %2[] : tensor<i1>
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cf.cond_br %3, ^bb2(%0 : tensor<i32>), ^bb3(%0 : tensor<i32>)
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^bb2(%4: tensor<i32>): // pred: ^bb1
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%5 = linalg.init_tensor [] : tensor<i32>
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%6 = linalg.generic #attrs
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ins(%4, %4 : tensor<i32>, tensor<i32>)
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outs(%5 : tensor<i32>) {
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^bb0(%arg0: i32, %arg1: i32, %arg2: i32):
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%8 = arith.addi %arg0, %arg1 : i32
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linalg.yield %8 : i32
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} -> tensor<i32>
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cf.br ^bb1(%6 : tensor<i32>)
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^bb3(%7: tensor<i32>): // pred: ^bb1
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return %7 : tensor<i32>
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}
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// Test aggresively detensoring all detensorable ops.
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//
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// DET-ALL-LABEL: func @main
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// DET-ALL-SAME: (%{{.*}}: tensor<i32>, %{{.*}}: tensor<i32>)
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// DET-ALL: tensor.extract {{.*}}
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// DET-ALL: cf.br ^[[bb1:.*]](%{{.*}} : i32)
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// DET-ALL: ^[[bb1]](%{{.*}}: i32)
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// DET-ALL: arith.cmpi slt, {{.*}}
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// DET-ALL: cf.cond_br {{.*}}, ^[[bb2:.*]](%{{.*}} : i32), ^[[bb3:.*]](%{{.*}} : i32)
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// DET-ALL: ^[[bb2]](%{{.*}}: i32)
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// DET-ALL: arith.addi {{.*}}
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// DET-ALL: cf.br ^[[bb1]](%{{.*}} : i32)
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// DET-ALL: ^[[bb3]](%{{.*}}: i32)
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// DET-ALL: tensor.from_elements {{.*}}
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// DET-ALL: return %{{.*}} : tensor<i32>
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// Test detensoring only ops involed in control-flow.
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//
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// DET-CF-LABEL: func @main
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// DET-CF-SAME: (%{{.*}}: tensor<i32>, %{{.*}}: tensor<i32>)
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// DET-CF: tensor.extract {{.*}}
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// DET-CF: cf.br ^[[bb1:.*]](%{{.*}} : i32)
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// DET-CF: ^[[bb1]](%{{.*}}: i32)
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// DET-CF: arith.cmpi slt, {{.*}}
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// DET-CF: cf.cond_br {{.*}}, ^[[bb2:.*]](%{{.*}} : i32), ^[[bb3:.*]](%{{.*}} : i32)
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// DET-CF: ^[[bb2]](%{{.*}}: i32)
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// DET-CF: arith.addi {{.*}}
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// DET-CF: cf.br ^[[bb1]](%{{.*}} : i32)
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// DET-CF: ^[[bb3]](%{{.*}}: i32)
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// DET-CF: tensor.from_elements %{{.*}} : tensor<i32>
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// DET-CF: return %{{.*}} : tensor<i32>
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