[Mlir-commits] [mlir] 880021d - [mlir][sparse] reenable asan for sampled mm integration test
Aart Bik
llvmlistbot at llvm.org
Thu Dec 9 12:08:07 PST 2021
Author: Aart Bik
Date: 2021-12-09T12:07:56-08:00
New Revision: 880021df132b36d69ae12c36dddb79c9e79f72fe
URL: https://github.com/llvm/llvm-project/commit/880021df132b36d69ae12c36dddb79c9e79f72fe
DIFF: https://github.com/llvm/llvm-project/commit/880021df132b36d69ae12c36dddb79c9e79f72fe.diff
LOG: [mlir][sparse] reenable asan for sampled mm integration test
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D115364
Added:
Modified:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
Removed:
################################################################################
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
index 5480c264a6d46..fe15ec161f557 100755
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
@@ -28,9 +28,6 @@
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s
-// Interop between linalg/sparse leaves some issues to be revolved:
-// UNSUPPORTED: asan
-
#SM = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
#trait_sampled_dense_dense = {
@@ -72,10 +69,7 @@ module {
func @sampled_dd(%args: tensor<8x8xf64, #SM>,
%arga: tensor<8x8xf64>,
%argb: tensor<8x8xf64>) -> tensor<8x8xf64> {
- %d = arith.constant 0.0 : f64
-
- %0 = linalg.init_tensor [8, 8] : tensor<8x8xf64>
- %1 = linalg.fill(%d, %0) : f64, tensor<8x8xf64> -> tensor<8x8xf64>
+ %1 = arith.constant dense<0.0> : tensor<8x8xf64>
%2 = linalg.generic #trait_sampled_dense_dense
ins(%args, %arga, %argb: tensor<8x8xf64, #SM>,
tensor<8x8xf64>, tensor<8x8xf64>)
@@ -94,11 +88,8 @@ module {
//
func @sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
%arga: tensor<8x8xf64>,
- %argb: tensor<8x8xf64>) -> tensor<8x8xf64> {
- %d = arith.constant 0.0 : f64
-
- %0 = linalg.init_tensor [8, 8] : tensor<8x8xf64>
- %1 = linalg.fill(%d, %0) : f64, tensor<8x8xf64> -> tensor<8x8xf64>
+ %argb: tensor<8x8xf64>) -> (tensor<8x8xf64>, tensor<8x8xf64>) {
+ %1 = arith.constant dense<0.0> : tensor<8x8xf64>
%2 = linalg.generic #trait_matmul
ins(%arga, %argb : tensor<8x8xf64>, tensor<8x8xf64>)
outs(%1 : tensor<8x8xf64>) {
@@ -108,17 +99,16 @@ module {
linalg.yield %q : f64
} -> tensor<8x8xf64>
- %3 = linalg.init_tensor [8, 8] : tensor<8x8xf64>
- %4 = linalg.fill(%d, %3) : f64, tensor<8x8xf64> -> tensor<8x8xf64>
- %5 = linalg.generic #trait_scale
+ %3 = arith.constant dense<0.0> : tensor<8x8xf64>
+ %4 = linalg.generic #trait_scale
ins(%2, %args : tensor<8x8xf64>, tensor<8x8xf64, #SM>)
- outs(%4 : tensor<8x8xf64>) {
+ outs(%3 : tensor<8x8xf64>) {
^bb0(%t: f64, %s: f64, %x: f64):
%r = arith.mulf %t, %s : f64
linalg.yield %r : f64
} -> tensor<8x8xf64>
- return %5 : tensor<8x8xf64>
+ return %4, %2 : tensor<8x8xf64>, tensor<8x8xf64>
}
//
@@ -140,9 +130,9 @@ module {
%0 = call @sampled_dd(%s, %a, %b)
: (tensor<8x8xf64, #SM>,
tensor<8x8xf64>, tensor<8x8xf64>) -> tensor<8x8xf64>
- %1 = call @sampled_dd_unfused(%s, %a, %b)
+ %1, %2 = call @sampled_dd_unfused(%s, %a, %b)
: (tensor<8x8xf64, #SM>,
- tensor<8x8xf64>, tensor<8x8xf64>) -> tensor<8x8xf64>
+ tensor<8x8xf64>, tensor<8x8xf64>) -> (tensor<8x8xf64>, tensor<8x8xf64>)
// Verify the outputs.
//
@@ -158,6 +148,7 @@ module {
//
%m0 = bufferization.to_memref %0 : memref<8x8xf64>
%m1 = bufferization.to_memref %1 : memref<8x8xf64>
+ %m2 = bufferization.to_memref %2 : memref<8x8xf64>
%v0 = vector.transfer_read %m0[%c0, %c0], %d0
: memref<8x8xf64>, vector<8x8xf64>
%v1 = vector.transfer_read %m1[%c0, %c0], %d0
@@ -169,6 +160,7 @@ module {
sparse_tensor.release %s : tensor<8x8xf64, #SM>
memref.dealloc %m0 : memref<8x8xf64>
memref.dealloc %m1 : memref<8x8xf64>
+ memref.dealloc %m2 : memref<8x8xf64>
return
}
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