File: bufferize.mlir

package info (click to toggle)
llvm-toolchain-13 1%3A13.0.1-11
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 1,418,840 kB
  • sloc: cpp: 5,290,826; ansic: 996,570; asm: 544,593; python: 188,212; objc: 72,027; lisp: 30,291; f90: 25,395; sh: 24,898; javascript: 9,780; pascal: 9,398; perl: 7,484; ml: 5,432; awk: 3,523; makefile: 2,913; xml: 953; cs: 573; fortran: 539
file content (103 lines) | stat: -rw-r--r-- 5,416 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
// RUN: mlir-opt %s -scf-bufferize | FileCheck %s

// CHECK-LABEL:   func @if(
// CHECK-SAME:             %[[PRED:.*]]: i1,
// CHECK-SAME:             %[[TRUE_TENSOR:.*]]: tensor<?xf32>,
// CHECK-SAME:             %[[FALSE_TENSOR:.*]]: tensor<?xf32>) -> tensor<?xf32> {
// CHECK:           %[[RESULT_MEMREF:.*]] = scf.if %[[PRED]] -> (memref<?xf32>) {
// CHECK:             %[[TRUE_MEMREF:.*]] = memref.buffer_cast %[[TRUE_TENSOR]] : memref<?xf32>
// CHECK:             scf.yield %[[TRUE_MEMREF]] : memref<?xf32>
// CHECK:           } else {
// CHECK:             %[[FALSE_MEMREF:.*]] = memref.buffer_cast %[[FALSE_TENSOR]] : memref<?xf32>
// CHECK:             scf.yield %[[FALSE_MEMREF]] : memref<?xf32>
// CHECK:           }
// CHECK:           %[[RESULT_TENSOR:.*]] = memref.tensor_load %[[RESULT_MEMREF:.*]] : memref<?xf32>
// CHECK:           return %[[RESULT_TENSOR]] : tensor<?xf32>
// CHECK:         }
func @if(%pred: i1, %true_val: tensor<?xf32>, %false_val: tensor<?xf32>) -> tensor<?xf32> {
  %0 = scf.if %pred -> (tensor<?xf32>) {
    scf.yield %true_val : tensor<?xf32>
  } else {
    scf.yield %false_val : tensor<?xf32>
  }
  return %0 : tensor<?xf32>
}

// CHECK-LABEL:   func @for(
// CHECK-SAME:              %[[TENSOR:.*]]: tensor<f32>,
// CHECK-SAME:              %[[LB:.*]]: index, %[[UB:.*]]: index,
// CHECK-SAME:              %[[STEP:.*]]: index) -> tensor<f32> {
// CHECK:           %[[MEMREF:.*]] = memref.buffer_cast %[[TENSOR]] : memref<f32>
// CHECK:           %[[RESULT_MEMREF:.*]] = scf.for %[[VAL_6:.*]] = %[[LB]] to %[[UB]] step %[[STEP]] iter_args(%[[ITER:.*]] = %[[MEMREF]]) -> (memref<f32>) {
// CHECK:             %[[TENSOR_ITER:.*]] = memref.tensor_load %[[ITER]] : memref<f32>
// CHECK:             %[[MEMREF_YIELDED:.*]] = memref.buffer_cast %[[TENSOR_ITER]] : memref<f32>
// CHECK:             scf.yield %[[MEMREF_YIELDED]] : memref<f32>
// CHECK:           }
// CHECK:           %[[VAL_8:.*]] = memref.tensor_load %[[VAL_9:.*]] : memref<f32>
// CHECK:           return %[[VAL_8]] : tensor<f32>
// CHECK:         }
func @for(%arg0: tensor<f32>, %lb: index, %ub: index, %step: index) -> tensor<f32> {
  %ret = scf.for %iv = %lb to %ub step %step iter_args(%iter = %arg0) -> tensor<f32> {
    scf.yield %iter : tensor<f32>
  }
  return %ret : tensor<f32>
}

// Check whether this converts at all.
//
// It would previously fail altogether.
// CHECK-LABEL:   func @if_correct_recursive_legalization_behavior
// CHECK: "test.munge_tensor"
func @if_correct_recursive_legalization_behavior(%pred: i1, %tensor: tensor<f32>) -> tensor<f32> {
  %0 = scf.if %pred -> (tensor<f32>) {
    %1 = "test.munge_tensor"(%tensor) : (tensor<f32>) -> (tensor<f32>)
    scf.yield %1: tensor<f32>
  } else {
    %1 = "test.munge_tensor"(%tensor) : (tensor<f32>) -> (tensor<f32>)
    scf.yield %1 : tensor<f32>
  }
  return %0 : tensor<f32>
}

// CHECK-LABEL:   func @for_correct_recursive_legalization_behavior(
// CHECK-SAME:                                                      %[[TENSOR:.*]]: tensor<f32>,
// CHECK-SAME:                                                      %[[INDEX:.*]]: index) -> tensor<f32> {
// CHECK:           %[[MEMREF:.*]] = memref.buffer_cast %[[TENSOR]] : memref<f32>
// CHECK:           %[[RESULT:.*]] = scf.for %[[IV:.*]] = %[[INDEX]] to %[[INDEX]] step %[[INDEX]] iter_args(%[[MEMREF_ITER:.*]] = %[[MEMREF]]) -> (memref<f32>) {
// CHECK:             %[[TENSOR_ITER:.*]] = memref.tensor_load %[[MEMREF_ITER]] : memref<f32>
// CHECK:             %[[TENSOR_MUNGED:.*]] = "test.munge_tensor"(%[[TENSOR_ITER]]) : (tensor<f32>) -> tensor<f32>
// CHECK:             %[[MEMREF_MUNGED:.*]] = memref.buffer_cast %[[TENSOR_MUNGED]] : memref<f32>
// CHECK:             scf.yield %[[MEMREF_MUNGED]] : memref<f32>
// CHECK:           }
// CHECK:           %[[TENSOR:.*]] = memref.tensor_load %[[RESULT:.*]] : memref<f32>
// CHECK:           return %[[TENSOR]] : tensor<f32>
// CHECK:         }
func @for_correct_recursive_legalization_behavior(%arg0: tensor<f32>, %index: index) -> tensor<f32> {
  %ret = scf.for %iv = %index to %index step %index iter_args(%iter = %arg0) -> tensor<f32> {
    %0 = "test.munge_tensor"(%iter) : (tensor<f32>) -> (tensor<f32>)
    scf.yield %0 : tensor<f32>
  }
  return %ret : tensor<f32>
}

// CHECK-LABEL:   func @bufferize_while(
// CHECK-SAME: %[[ARG0:.*]]: i64, %[[ARG1:.*]]: i64, %[[ARG2:.*]]: tensor<f32>
// CHECK: %[[M:.*]] = memref.buffer_cast %[[ARG2]] : memref<f32>
// CHECK: %[[RES1:.*]]:3 = scf.while (%{{.*}} = %[[ARG0]], %{{.*}} = %[[M]]) : (i64, memref<f32>) -> (i64, i64, memref<f32>)
// CHECK: scf.condition(%{{.*}}) %{{.*}}, %{{.*}}, %{{.*}} : i64, i64, memref<f32>
// CHECK: ^bb0(%{{.*}}: i64, %{{.*}}: i64, %{{.*}}: memref<f32>):
// CHECK: scf.yield %{{.*}}, %{{.*}} : i64, memref<f32>
// CHECK:  %[[RES2:.*]] = memref.tensor_load %[[RES1]]#2 : memref<f32>
// CHECK:  return %[[RES1]]#1, %[[RES2]] : i64, tensor<f32>
func @bufferize_while(%arg0: i64, %arg1: i64, %arg2: tensor<f32>) -> (i64, tensor<f32>) {
  %c2_i64 = constant 2 : i64
  %0:3 = scf.while (%arg3 = %arg0, %arg4 = %arg2) : (i64, tensor<f32>) -> (i64, i64, tensor<f32>) {
    %1 = cmpi slt, %arg3, %arg1 : i64
    scf.condition(%1) %arg3, %arg3, %arg4 : i64, i64, tensor<f32>
  } do {
  ^bb0(%arg5: i64, %arg6: i64, %arg7: tensor<f32>):
    %1 = muli %arg6, %c2_i64 : i64
    scf.yield %1, %arg7 : i64, tensor<f32>
  }
  return %0#1, %0#2 : i64, tensor<f32>
}