llvm-project/mlir/test/Transforms/memref-bound-check.mlir

85 lines
3.5 KiB
MLIR
Raw Normal View History

Introduce memref bound checking. Introduce analysis to check memref accesses (in MLFunctions) for out of bound ones. It works as follows: $ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ #map0 = (d0, d1) -> (d0, d1) #map1 = (d0, d1) -> (d0 * 128 - d1) mlfunc @test() { %0 = alloc() : memref<9x9xi32> %1 = alloc() : memref<128xi32> for %i0 = -1 to 9 { for %i1 = -1 to 9 { %2 = affine_apply #map0(%i0, %i1) %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32> %4 = affine_apply #map1(%i0, %i1) %5 = load %1[%4] : memref<128xi32> } } return } - Improves productivity while manually / semi-automatically developing MLIR for testing / prototyping; also provides an indirect way to catch errors in transformations. - This pass is an easy way to test the underlying affine analysis machinery including low level routines. Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256. While on this: - create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/ - fix a bug in AffineAnalysis.cpp::toAffineExpr TODO: extend to non-constant loop bounds (straightforward). Will transparently work for all accesses once floordiv, mod, ceildiv are supported in the AffineMap -> FlatAffineConstraints conversion. PiperOrigin-RevId: 219397961
2018-10-31 08:43:06 +08:00
// RUN: mlir-opt %s -memref-bound-check -split-input-file -verify | FileCheck %s
// -----
// CHECK-LABEL: mlfunc @test() {
mlfunc @test() {
%zero = constant 0 : index
%minusone = constant -1 : index
%sym = constant 111 : index
%A = alloc() : memref<9 x 9 x i32>
%B = alloc() : memref<111 x i32>
for %i = -1 to 10 {
for %j = -1 to 10 {
Introduce memref bound checking. Introduce analysis to check memref accesses (in MLFunctions) for out of bound ones. It works as follows: $ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ #map0 = (d0, d1) -> (d0, d1) #map1 = (d0, d1) -> (d0 * 128 - d1) mlfunc @test() { %0 = alloc() : memref<9x9xi32> %1 = alloc() : memref<128xi32> for %i0 = -1 to 9 { for %i1 = -1 to 9 { %2 = affine_apply #map0(%i0, %i1) %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32> %4 = affine_apply #map1(%i0, %i1) %5 = load %1[%4] : memref<128xi32> } } return } - Improves productivity while manually / semi-automatically developing MLIR for testing / prototyping; also provides an indirect way to catch errors in transformations. - This pass is an easy way to test the underlying affine analysis machinery including low level routines. Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256. While on this: - create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/ - fix a bug in AffineAnalysis.cpp::toAffineExpr TODO: extend to non-constant loop bounds (straightforward). Will transparently work for all accesses once floordiv, mod, ceildiv are supported in the AffineMap -> FlatAffineConstraints conversion. PiperOrigin-RevId: 219397961
2018-10-31 08:43:06 +08:00
%idx = affine_apply (d0, d1) -> (d0, d1)(%i, %j)
// Out of bound access.
%x = load %A[%idx#0, %idx#1] : memref<9 x 9 x i32>
// expected-error@-1 {{'load' op memref out of upper bound access along dimension #1}}
// expected-error@-2 {{'load' op memref out of lower bound access along dimension #1}}
// expected-error@-3 {{'load' op memref out of upper bound access along dimension #2}}
// expected-error@-4 {{'load' op memref out of lower bound access along dimension #2}}
// This will access 0 to 110 - hence an overflow.
%idy = affine_apply (d0, d1) -> (10*d0 - d1 + 19)(%i, %j)
%y = load %B[%idy] : memref<111 x i32>
}
}
for %k = 0 to 10 {
Introduce memref bound checking. Introduce analysis to check memref accesses (in MLFunctions) for out of bound ones. It works as follows: $ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ #map0 = (d0, d1) -> (d0, d1) #map1 = (d0, d1) -> (d0 * 128 - d1) mlfunc @test() { %0 = alloc() : memref<9x9xi32> %1 = alloc() : memref<128xi32> for %i0 = -1 to 9 { for %i1 = -1 to 9 { %2 = affine_apply #map0(%i0, %i1) %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32> %4 = affine_apply #map1(%i0, %i1) %5 = load %1[%4] : memref<128xi32> } } return } - Improves productivity while manually / semi-automatically developing MLIR for testing / prototyping; also provides an indirect way to catch errors in transformations. - This pass is an easy way to test the underlying affine analysis machinery including low level routines. Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256. While on this: - create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/ - fix a bug in AffineAnalysis.cpp::toAffineExpr TODO: extend to non-constant loop bounds (straightforward). Will transparently work for all accesses once floordiv, mod, ceildiv are supported in the AffineMap -> FlatAffineConstraints conversion. PiperOrigin-RevId: 219397961
2018-10-31 08:43:06 +08:00
// In bound.
%u = load %B[%zero] : memref<111 x i32>
// Out of bounds.
%v = load %B[%sym] : memref<111 x i32> // expected-error {{'load' op memref out of upper bound access along dimension #1}}
// Out of bounds.
%w = load %B[%minusone] : memref<111 x i32> // expected-error {{'load' op memref out of lower bound access along dimension #1}}
}
return
}
// CHECK-LABEL: mlfunc @test_
mlfunc @test_mod_floordiv_ceildiv() {
%zero = constant 0 : index
%A = alloc() : memref<128 x 64 x 64 x i32>
for %i = 0 to 256 {
for %j = 0 to 256 {
%idx = affine_apply (d0, d1, d2) -> (d0 mod 128 + 1, d1 floordiv 4 + 1, d2 ceildiv 4)(%i, %j, %j)
%x = load %A[%idx#0, %idx#1, %idx#2] : memref<128 x 64 x 64 x i32>
// expected-error@-1 {{'load' op memref out of upper bound access along dimension #1}}
// expected-error@-2 {{'load' op memref out of upper bound access along dimension #2}}
// expected-error@-3 {{'load' op memref out of upper bound access along dimension #3}}
%idy = affine_apply (d0, d1, d2) -> (d0 mod 128, d1 floordiv 4, d2 ceildiv 4 - 1)(%i, %j, %j)
%y = load %A[%idy#0, %idy#1, %idy#2] : memref<128 x 64 x 64 x i32> // expected-error {{'load' op memref out of lower bound access along dimension #3}}
// CHECK-EMPTY
} // CHECK }
} // CHECK }
return
}
// CHECK-LABEL: mlfunc @test_no_out_of_bounds()
mlfunc @test_no_out_of_bounds() {
%zero = constant 0 : index
%A = alloc() : memref<257 x 256 x i32>
%C = alloc() : memref<257 x i32>
%B = alloc() : memref<1 x i32>
for %i = 0 to 256 {
for %j = 0 to 256 {
// All of these accesses are in bound; check that no errors are emitted.
// CHECK: %3 = affine_apply #map4(%i0, %i1)
// CHECK-NEXT: %4 = load %0[%3#0, %c0] : memref<257x256xi32>
// CHECK-NEXT: %5 = affine_apply #map5(%i0, %i0)
// CHECK-NEXT: %6 = load %2[%5] : memref<1xi32>
%idx = affine_apply (d0, d1) -> ( 64 * (d0 ceildiv 64), d1 floordiv 4 + d1 mod 4)(%i, %j)
// Without GCDTightenInequalities(), the upper bound on the region
// accessed along first memref dimension would have come out as d0 <= 318
// (instead of d0 <= 256), and led to a false positive out of bounds.
%x = load %A[%idx#0, %zero] : memref<257 x 256 x i32>
%idy = affine_apply (d0, d1) -> (d0 floordiv 256)(%i, %i)
%y = load %B[%idy] : memref<1 x i32>
} // CHECK-NEXT }
}
return
}