75 lines
3.3 KiB
MLIR
75 lines
3.3 KiB
MLIR
// RUN: mlir-hlo-opt %s -mhlo-sink-constants-to-control-flow | FileCheck %s
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// Tests sinking constants to a while loop.
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// CHECK-LABEL: func @sink_const_to_while
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func @sink_const_to_while(%arg0: tensor<i64>) -> tensor<i64> {
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// CHECK-NEXT: mhlo.while
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%c0 = mhlo.constant dense<1> : tensor<i64>
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%c1 = mhlo.constant dense<2> : tensor<i64>
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%0 = "mhlo.while"(%arg0) ( {
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^bb0(%arg1: tensor<i64>):
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// CHECK: %[[ARG1A:.+]]: tensor<i64>
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// CHECK: %[[C0:.+]] = mhlo.constant dense<1> : tensor<i64>
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// CHECK: "mhlo.compare"(%[[C0]], %[[ARG1A]])
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%1 = "mhlo.compare"(%c0, %arg1) {comparison_direction = "LT"} : (tensor<i64>, tensor<i64>) -> tensor<i1>
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"mhlo.return"(%1) : (tensor<i1>) -> ()
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}, {
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^bb0(%arg1: tensor<i64>):
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// CHECK: %[[ARG1B:.+]]: tensor<i64>
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// CHECK-DAG: %[[C1:.+]] = mhlo.constant dense<2> : tensor<i64>
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// CHECK-DAG: %[[ADD0:.+]] = mhlo.add %[[ARG1B]], %[[ARG1B]]
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%2 = mhlo.add %arg1, %arg1 : tensor<i64>
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// CHECK: %[[ADD1:.+]] = mhlo.add %[[C1]], %[[ADD0]]
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%3 = mhlo.add %c1, %2 : tensor<i64>
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// CHECK: %[[ADD2:.+]] = mhlo.add %[[C1]], %[[ADD1]]
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%4 = mhlo.add %c1, %3 : tensor<i64>
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"mhlo.return"(%4) : (tensor<i64>) -> ()
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}) : (tensor<i64>) -> tensor<i64>
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return %0 : tensor<i64>
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}
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// Tests sinking constants to a conditional op.
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// CHECK-LABEL: func @sink_const_to_conditional
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func @sink_const_to_conditional(%arg0: tensor<i64>) -> tensor<i64> {
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%c0 = mhlo.constant dense<1> : tensor<i64>
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%c1 = mhlo.constant dense<2> : tensor<i64>
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%0 = "mhlo.compare"(%arg0, %c0) {comparison_direction = "LT"} : (tensor<i64>, tensor<i64>) -> tensor<i1>
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%1 = "mhlo.tuple"(%arg0) : (tensor<i64>) -> tuple<tensor<i64>>
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// CHECK: mhlo.if
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%2 = "mhlo.if"(%0, %1, %1) ( {
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^bb0(%arg1: tuple<tensor<i64>>):
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// CHECK: %[[C0:.+]] = mhlo.constant dense<1> : tensor<i64>
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%3 = "mhlo.get_tuple_element"(%arg1) {index = 0 : i32} : (tuple<tensor<i64>>) -> tensor<i64>
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// CHECK: %[[ADD0:.+]] = mhlo.add %[[C0]],
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%4 = mhlo.add %c0, %3 : tensor<i64>
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%5 = "mhlo.tuple"(%4) : (tensor<i64>) -> tuple<tensor<i64>>
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"mhlo.return"(%5) : (tuple<tensor<i64>>) -> ()
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}, {
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^bb0(%arg1: tuple<tensor<i64>>):
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// CHECK: %[[C1:.+]] = mhlo.constant dense<2> : tensor<i64>
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%6 = "mhlo.get_tuple_element"(%arg1) {index = 0 : i32} : (tuple<tensor<i64>>) -> tensor<i64>
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// CHECK: %[[ADD1:.+]] = mhlo.add %[[C1]],
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%7 = mhlo.add %c1, %6 : tensor<i64>
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%8 = "mhlo.tuple"(%7) : (tensor<i64>) -> tuple<tensor<i64>>
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"mhlo.return"(%8) : (tuple<tensor<i64>>) -> ()
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}) : (tensor<i1>, tuple<tensor<i64>>, tuple<tensor<i64>>) -> tuple<tensor<i64>>
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%9 = "mhlo.get_tuple_element"(%2) {index = 0 : i32} : (tuple<tensor<i64>>) -> tensor<i64>
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return %9 : tensor<i64>
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}
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func @sink_const_to_sort(%arg0: tensor<16xf32>) {
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%c0 = constant dense<1.0> : tensor<f32>
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// CHECK: "mhlo.sort"
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%0 = "mhlo.sort"(%arg0) ( {
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^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>):
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// CHECK: constant dense<1.000000e+00>
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%1 = "mhlo.divide"(%arg1, %c0) : (tensor<f32>, tensor<f32>) -> tensor<f32>
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%2 = "mhlo.divide"(%arg2, %c0) : (tensor<f32>, tensor<f32>) -> tensor<f32>
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%3 = "mhlo.compare"(%1, %2) {comparison_direction = "GT"} : (tensor<f32>, tensor<f32>) -> tensor<i1>
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"mhlo.return"(%3) : (tensor<i1>) -> ()
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}) {is_stable = true} : (tensor<16xf32>) -> tensor<16xi32>
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return
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}
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